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ycombinator_s24

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Silurian

silurian

https://silurian.ai/

Kirkland, WA, USA

Silurian is building foundation models for simulating Earth, starting with weather. From assessing the risk of wildfires to predicting the energy grid load, we provide an infrastructure layer for our planet. Our frontier models push the boundaries of what can be simulated on Earth and improve decision making across vital sectors including energy, insurance, agriculture, and logistics.

Foundation models to simulate Earth

Industrials

Industrials -> Climate

S24

Active

Early

https://www.ycombinator.com/companies/silurian

https://yc-oss.github.io/api/batches/s24/silurian.json

{"code":"ETIMEDOUT","name":"Error","message":"Timeout waiting for dependencies(PuppeteerControl) to be ready for CrawlerHost."}

Kisho

kisho

https://kisho.app

San Francisco, CA, USA

Kisho is an AI data scientist that lives inside a Jupyter Notebook. It enables anyone to perform advanced data analysis and build ML models using natural language - no coding required.

The AI Data Scientist - a Jupyter Notebook that writes itself.

B2B

Unspecified

S24

Active

Early

https://www.ycombinator.com/companies/kisho

https://yc-oss.github.io/api/batches/s24/kisho.json

Title: Y Combinator | File Not Found URL Source: Warning: Target URL returned error 404: Not Found Markdown Content: 404 --- [Back to the homepage]( support please contact [software@ycombinator.com](mailto:software@ycombinator.com)

MinusX

minusx

https://minusx.ai

San Francisco, CA, USA; Remote

MinusX is a chrome extension that adds a side chat to your analytics apps (Jupyter, Metabase, Grafana, Tableau, etc). Given an instruction, our agent operates your apps - by clicking & typing, just like you do - to analyze data and answer queries. We believe an AI Data Scientist is a scientist, not yet-another-new-analytics-platform. MinusX interoperates with you in tools you already love and use, and as a matter of philosophy, gets out of the way.

AI Data Scientist for Jupyter and Metabase

B2B

B2B -> Analytics

S24

Active

Early

https://www.ycombinator.com/companies/minusx

https://yc-oss.github.io/api/batches/s24/minusx.json

Title: MinusX: AI Data Scientist for Jupyter and Metabase | Y Combinator URL Source: Markdown Content: ### AI Data Scientist for Jupyter and Metabase MinusX is a chrome extension that adds a side chat to your analytics apps (Jupyter, Metabase, Grafana, Tableau, etc). Given an instruction, our agent operates your apps - by clicking & typing, just like you do - to analyze data and answer queries. We believe an AI Data Scientist is a scientist, not yet-another-new-analytics-platform. MinusX interoperates with you in tools you already love and use, and as a matter of philosophy, gets out of the way. MinusX Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Vivek Aithal, Founder Co-founder & CEO of MinusX. Spent the last 3 years as a research engineer building the world's best open-source autonomous driving agent at comma.ai. Currently building a data science agent that can sit in your browser and use all your data tools. UC Berkeley and IIT Kharagpur grad. ### Sreejith Puthanpurayil, Founder Co-Founder & CTO of MinusX. Previous stints include Ads Delivery & Ranking at Meta, Ride-hailing backend & infra at Gojek, & full stack at Elanic, a social c2c marketplace (acquired by Share Chat) ### Arpit Saxena, Founder Ex-Google (Google Pay), GreyOrange Robotics, Udaan.com; Software and Systems Engineer building warehouse automation solutions for km sized warehouses ### Company Launches [### MinusX: AI Data Scientist for Jupyter and Metabase]( **TL;DR** --------- MinusX is a Chrome Extension that adds a side chat to Jupyter and Metabase. Given an instruction, our agent operates the apps— via clicking and typing— to analyze data and answer queries. We strongly believe that you already have all the tools you need; you just need someone like MinusX to use them! Checkout [**minusx.ai**]( for more info. [ **Asks** -------- 1. Install our [**Chrome extension**]( 2. Take MinusX for a spin in our [**playground**]( 3. We’re working on supporting more tools. Want us to hurry up, or don't see your favorite tool in our list? Here’s a [**google form**]( you can fill out so that we can notify you when we support your tool! **Features** ------------ ### 1\. Generate Hypotheses and Explore data ### 2\. Interop with MinusX to modify existing Jupyter notebooks or Metabase Questions ### 3\. Select a region and ask questions, or ask for modifications **Pain** -------- * Lack of data analyst/data scientist bandwidth is a certified pain. * If you’re a programmer, you just want answers. If you’re a product manager, you just want answers. If you’re an analyst/scientist, you want 10 clones of yourself. * Any new fancy “talk-to-data” platform is a whole thing. You have to migrate your data, and you have to convince your whole team to move— just to start using it. * Working in ChatGPT / Claude requires constant copy-pasting. Also, you want to inter-operate with AI, make corrections when it messes up, and guide it rather than just admonish it in chat. * More importantly, they’re still just chat! No AI system today can really use analytics software - click and type - to get you that data you needed 5 minutes ago. **Our Approach** ---------------- > ### **_An AI Data Scientist is a Scientist, not yet-another-new-analytics-platform_** * Advanced agents should just work with tools you already use and get out of the way. * MinusX integrates seamlessly into workflows. You can invoke it only when you need it to do something. * Whether you’re a data analyst, programmer, or product manager, you can use MinusX to speed up your workflows instantly. * We believe the path to advanced agents runs through specialized, useful intermediaries. **Team** -------- We love to build stuff. We met about a decade ago in the drowsy hinterlands of IIT Kharagpur and have been building things together at work, on side projects, and at hackathons ever since. [**Vivek**]( was most recently a Research Engineer working on self-driving cars at [**comma.ai**]( [**Sreejith**]( was a Senior Engineer in the Meta shops ads ranking team optimizing Facebook Shops Ads delivery & core infrastructure, and [**Arpit**]( was building a warehouse robot fleet as a Product Engineer at Udaan. We have extensive experience in machine learning, data infrastructure, and systems engineering needed to build the best, most delightful class of Data Science agents you'll ever use. **Ask(ing again!)** ------------------- 1. Install our [**Chrome extension**]( 2. Take MinusX for a spin in our [**playground**]( 3. We’re working on supporting more tools. Want us to hurry up, or don't see your favorite tool in our list? Here’s a [**google form**]( you can fill out so we can notify you when we support your tool! If you have any questions or comments, you can join our [**discord**]( or ping me anytime at [**vivek@minusx.ai**](mailto:vivek@minusx.ai). Hope you enjoy using MinusX as much as we enjoy building it! ### ❤️

Pharos

pharos

https://pharos.health/

San Francisco, CA, USA

Pharos automates hospital quality reporting, saving millions in labour costs and helping to prevent avoidable patient harm. Today, clinicians spend thousands of hours manually pulling complex facts out of medical records for mandatory reporting and quality improvement. Our AI pulls those facts out of unstructured medical records automatically. We automate reporting and show staff where avoidable patient harm is happening.

Automate hospital reporting and prevent patient harm with AI

Healthcare

Healthcare -> Healthcare IT

S24

Active

Early

https://www.ycombinator.com/companies/pharos

https://yc-oss.github.io/api/batches/s24/pharos.json

Title: Pharos: Automate hospital reporting and prevent patient harm with AI | Y Combinator URL Source: Markdown Content: ### Automate hospital reporting and prevent patient harm with AI Pharos automates hospital quality reporting, saving millions in labour costs and helping to prevent avoidable patient harm. Today, clinicians spend thousands of hours manually pulling complex facts out of medical records for mandatory reporting and quality improvement. Our AI pulls those facts out of unstructured medical records automatically. We automate reporting and show staff where avoidable patient harm is happening. Pharos Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Felix Brann, Founder CEO at Pharos. Previously VP Data Science at vital.io and VP Quantitative Research at JP. Morgan. Obsessed with sepsis: ### Matthew Jones, Founder Founder and CTO at Pharos. Previously I was part of the founding team of Market2x, a rural trucking SAAS startup, growing that from inception to international expansion. The rest of my career has been as a software engineer at various health tech companies. ### Company Launches [### 🏥 Pharos - Automate reporting and prevent patient harm with AI]( **tl;dr:** _The data hospital teams need to improve patient safety is buried in unstructured medical records. Today, clinicians spend thousands of hours manually ‘abstracting’ it for reporting and analysis. We automate the entire process and use the data to show them where and why avoidable harm is happening._ Hi folks! We’re Felix and Matthew, and we’re building [Pharos]( The problem: ------------ Avoidable harm happens in hospitals **all the time**. Wards are busy, clinician turnover is high, and an aging population means increasingly complex patients. Sepsis alone kills 350,000 patients a year in the US, and a significant number of those deaths are preventable. Hospitals have teams dedicated to preventing harm. They track avoidable events, identify the process failures that cause them, and report performance data to clinical registries. This means identifying harm events, risk factors and process adherence from patient journeys composed of pages of unstructured clinical notes. Today, this is an entirely manual process. Producing structured quality metrics from a single complex patient case can take up to **8 hours of clinical time**. A single hospital can spend **$5m per year** extracting this data, and it still arrives weeks after discharge, on a small sample of their patients. The solution: ------------- Our AI extracts the data quality teams need from **every patient record in real-time**. It produces verifiable quality metrics, with references into the original medical record. We use this data to: * **Automate reporting** for clinical registries and value-based reimbursement contracts, saving thousands of clinical hours. * **Identify and surface process failures** that are contributing to patient harm, letting teams take action on issues like sepsis, hospital-acquired infections, and pressure ulcers. * **Measure the impact of quality improvement projects** in real-time rather than months after implementation. Why us? ------- [Felix]( and [Matthew]( spent the past 5 years deploying patient and clinician-facing AI into over 70 hospitals together. As VP of Data Science, Felix published papers in major medical journals on sepsis prediction and medical record summarization using LLMs. Matthew has years of experience integrating software into EHRs and previously built another startup from inception to international expansion. Alex joined the team after working as a doctor in the UK and then as a medical AI researcher at Imperial College London and Meta’s Reality Labs. He experienced this problem firsthand, spending years of his residency frustrated at the manual abstraction required for quality improvement. We believe enabling quality teams with AI represents a huge opportunity to save lives and prevent harm. Our ask: -------- Please reach out to [felix@pharos.health](mailto:felix@pharos.health) if you know the following people! * Anyone working at a senior level at a US hospital (we’ll ask them for an intro to their quality team) * Anyone working in healthcare with a title that includes “Quality”, “Patient Safety,” or “(Sepsis, Stroke, …) Coordinator” * Academics and clinicians working at the intersection of data and clinical quality ### Hear from the founders #### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?) Felix and Matthew worked together for nearly 5 years at [Vital.io]( a company deploying AI models into hospitals. While piloting clinical adoption of a predictive sepsis model, they realized that enabling quality staff with AI represents a huge opportunity to improve patient outcomes. #### What is your long-term vision? If you truly succeed, what will be different about the world? We believe in a future where AI catches medical mistakes everywhere in the hospital, before they become serious. We want to be the lighthouse for our hospitals, supporting clinicians and reducing patient harm.

Distro

distro

https://distro.app

New York, NY, USA

Distro is the all-in-one AI-powered sales platform for counter staff and inside sales at industrial wholesale distributors (HVAC/R, plumbing, electrical, and more).

The AI co-pilot for sales reps at industrial wholesale distributors.

B2B

B2B -> Supply Chain and Logistics

S24

Active

Early

https://www.ycombinator.com/companies/distro

https://yc-oss.github.io/api/batches/s24/distro.json

Title: Distro: The AI co-pilot for sales reps at industrial wholesale distributors. | Y Combinator URL Source: Markdown Content: Distro: The AI co-pilot for sales reps at industrial wholesale distributors. | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( Distro ====== The AI co-pilot for sales reps at industrial wholesale distributors. [S24]( Active [artificial-intelligence]( York]( * * * [Company]( [Jobs](  [ * * * ### The AI co-pilot for sales reps at industrial wholesale distributors. Distro is the all-in-one AI-powered sales platform for counter staff and inside sales at industrial wholesale distributors (HVAC/R, plumbing, electrical, and more). Distro Founded:2022 Team Size:4 Location:New York Group Partner:[Nicolas Dessaigne](  []( "LinkedIn profile") ### Active Founders ### Jason Sullivan, Founder Jason is the founder and CEO of Distro, the all-in-one AI co-pilot for counter staff and inside sales at industrial wholesale distributors. He is a repeat founder, having previously co-founded Vested. Before Vested, he was CTO at Elementus, Tech Lead at Coatue, and Senior Software Engineer at PeerIQ. In a prior life, Jason was a credit derivatives trader. Jason holds an MS in Computer Science from Stanford and a BA in Cognitive Science from Yale. Jason Sullivan [Distro](  []( "LinkedIn profile") ### Company Launches [### 🏭🤖 Distro - Bringing point-of-sale AI to industrial distribution]( [Distro]( is the AI sales co-pilot designed for industrial wholesale distributors. We created Distro out of a passion for developing software for the “real economy,” and in particular for the trades. The Distro team is based in, and loves, NYC! 🗽 ### 😅 **The Problem** Distributors, particularly those mid-size and smaller, face a long list of point-of-sale challenges these days. _🧠 Brain drain_: the most experienced reps are at or near retirement and are taking a great deal of tribal knowledge with them. _🔧 Complex sales_: quoting entire systems, load calculations, replacing legacy parts and equipment. _📦 Inventory challenges_: growing SKU counts, supply chain disruptions, decreased inventorying by contractors. _🎓 Training and retention_: counter reps, in particular, are difficult to hire, train and retain. These issues are amplified by the increasing importance of counter and inside sales relative to the rest of the sales organization–there has been a whopping 13 percentage point shift\* towards counter staff and inside sales influencing purchasing decisions, moving away from territory managers/outside sales. To top it all off, there is the ever-present and growing threat of larger players that have the resources to throw money and bodies at the aforementioned problems. _\*_ 2023-2024 State of the Channel, HARDI (Heating, Air-conditioning & Refrigeration Distributors International) ### 🔍 **Our Approach** What began as an academic curiosity about how to apply AI to distribution evolved into our team spending countless hours with distributor reps across the country over the course of a year, going deep on their day-to-day challenges, and building a distributor-centric solution from the ground up in partnership with several leading distributors. This experience–fully immersing ourselves in a distribution vertical in order to go far beyond a superficial understanding of that vertical’s product universe and sales workflows–has shaped our product philosophy and overall approach. Some of our learnings: 📍 _Meet reps where they are_: don’t try to push reps to adapt to a totally new paradigm. Adapt our workflows to how things really work at the counter. 🚀 _Effortless onboarding_: distributor IT teams don’t need another tech project to distract them. Build solutions that avoid the need for long implementations. 🔒 _Data sanctity_: distributors can spend a lot of time, energy, and money curating their data. Complete data security and privacy are necessary to protect that advantage. 🛠️ _Enhance, don’t replace_: the human element is the key to a distributor’s value-add to its contractor customers. We’re building Iron Man’s suit, not the Terminator. ### 💡 **Our Solution** Our platform helps counter and inside sales reps work more efficiently by transforming complex customer requests into real-time product information and quotes. With Distro, reps can quote faster, boost conversion rates, and increase customer retention. We support distributors in sectors like HVAC/R, plumbing, electrical, and more. ### 🙏 **Asks** 🤝 Connect with us: If you are a founder in the distribution, manufacturing, or contractor spaces, we’d love to share learnings. 📣 Customer intros: distributors, contractors, and OEMs, particularly in HVAC/R, plumbing, and electrical. Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

Stempad

stempad

https://www.stempad.io

You can think of Stempad as a Notion for science. It is the world's first true pen-and-paper alternative to fast scientific writing and collaborating. Quickly switch between different forms of technical visualization with the ease of a whiteboard and the convenience of your keyboard. Stempad allows you to share your work, collaborate in real time, store your data, annotate, write papers, plan, takes notes, create presentations, and so much more. Our vision is to make it easier and faster for students and scientists to digitize and share their scientific ideas.

Notion for science

B2B

B2B -> Productivity

S24

Active

Early

https://www.ycombinator.com/companies/stempad

https://yc-oss.github.io/api/batches/s24/stempad.json

Title: Stempad: Notion for science | Y Combinator URL Source: Markdown Content: ### Notion for science You can think of Stempad as a Notion for science. It is the world's first true pen-and-paper alternative to fast scientific writing and collaborating. Quickly switch between different forms of technical visualization with the ease of a whiteboard and the convenience of your keyboard. Stempad allows you to share your work, collaborate in real time, store your data, annotate, write papers, plan, takes notes, create presentations, and so much more. Our vision is to make it easier and faster for students and scientists to digitize and share their scientific ideas. ### Latest News Stempad Founded:2024 Team Size:1 Location: ### Active Founders ### Ralph Rouhana, Founder Hey, I'm Ralph 👋 I founded Stempad in early 2024 to help me take notes in my final year of school. After getting it to several hundred users and a few paying subscribers, I saw the potential for schools, research teams, pharmaceutical companies, tutoring companies, and more. I've previously interned at BioRender (W18), Microsoft, and 5 other companies. ### Company Launches [### Stempad: Scientific writing at the speed of thought]( **_Tl;dr:_** Stempad is an online editor and platform that streamlines writing and sharing scientific documents fast. Take notes, write research papers, create and conduct exams, collaborate in real-time, share your work with the world, and more. [_Try it out today._]( Hi everyone, I’m [Ralph]( I’m on a mission to improve the way teachers, students, and scientists document and share their ideas. **The Problem** --------------- Handwriting (via paper/tablet/board), a medium that is often substandard and that many struggle with, is currently the only viable way to do fast or impromptu scientific writing. * Students often resort to text editors unoptimized for science, such as Notion or Word, to take notes and write assignments. * Scientists use PowerPoint, wrestle with slow and expensive legacy software, and resort to handwriting to take notes, create writeups, or make presentations. * Remote tutors and their students require expensive tablets, styluses, and specialty software for a real-time digital whiteboard experience. * Professors often upload low quality scans of their messy handwritten class notes. The list could go on. The ability to quickly and collaboratively document scientific ideas with a keyboard is a huge QOL and productivity boost for people and institutions doing science. **Stempad To The Rescue 🔬** ---------------------------- You can think of Stempad as a **Notion for Science**. It is the world's first true pen-and-paper alternative for fast scientific writing. Quickly switch between different forms of technical visualization with the ease of a stylus and the convenience of your keyboard. Stempad allows users to save, export and share their work, collaborate in real time, create and grade assignments, conduct remote exams, write research papers, take notes, create presentations, and so much more. **My Asks** ----------- * Introduce me to educators, students, scientists, and decision makers **at schools, pharmaceutical companies, research teams, edtech companies, tutoring companies, summer schools, and relevant STEM programs.** [Click here](mailto:ralph@stempad.io?subject=Introducing%20you%20to%20Ralph%20at%20Stempad). * If you or any founders you know have B2B SaaS products in the education and science industry, I’d love to learn from you. [Click here](mailto:ralph@stempad.io?subject=Founder%20Intro). * [Sign u](mailto:ralph@stempad.io?subject=Founder%20Intro)[p]( use it next to others, and spread the word :)

Azalea Robotics Corporation

azalea-robotics-corporation

https://azalearobotics.com/

Berkeley, CA, USA

Azalea Robotics automates airport baggage handling with intelligent robot operations. The global market for airport baggage handling systems is $20+ billion and growing, presenting a significant opportunity for innovation and market disruption in this sector. Passenger air traffic volume is increasing, driving demand for efficient and reliable baggage handling at airports and putting immense pressure on existing infrastructure. In 2023 alone, airports processed approximately 4.5 billion bags, highlighting the need for advanced solutions to manage this load effectively. Azalea Robotics provides state-of-the-art robotic systems that enhance efficiency, reduce mishandling, and improve passenger experience through more reliable operations. Baggage handling is a critical component of airline ground operations, yet it is fraught with challenges. The work is physically demanding, often leading to long-term injuries among workers. Traditional baggage handling involves repetitive lifting and maneuvering of heavy loads, which can result in long-term health issues. Azalea Robotics addresses these challenges by automating the most strenuous tasks, thereby reducing the risk of injury and enhancing operational efficiency.

Automating airport baggage handling with robots.

Industrials

Industrials -> Manufacturing and Robotics

S24

Active

Early

https://www.ycombinator.com/companies/azalea-robotics-corporation

https://yc-oss.github.io/api/batches/s24/azalea-robotics-corporation.json

Title: Azalea Robotics Corporation: Automating airport baggage handling with robots. | Y Combinator URL Source: Markdown Content: ### Automating airport baggage handling with robots. Azalea Robotics automates airport baggage handling with intelligent robot operations. The global market for airport baggage handling systems is $20+ billion and growing, presenting a significant opportunity for innovation and market disruption in this sector. Passenger air traffic volume is increasing, driving demand for efficient and reliable baggage handling at airports and putting immense pressure on existing infrastructure. In 2023 alone, airports processed approximately 4.5 billion bags, highlighting the need for advanced solutions to manage this load effectively. Azalea Robotics provides state-of-the-art robotic systems that enhance efficiency, reduce mishandling, and improve passenger experience through more reliable operations. Baggage handling is a critical component of airline ground operations, yet it is fraught with challenges. The work is physically demanding, often leading to long-term injuries among workers. Traditional baggage handling involves repetitive lifting and maneuvering of heavy loads, which can result in long-term health issues. Azalea Robotics addresses these challenges by automating the most strenuous tasks, thereby reducing the risk of injury and enhancing operational efficiency. Azalea Robotics Corporation Founded:2023 Team Size:2 Location:Berkeley, CA ### Active Founders ### David Millard, Founder David is a roboticist and software engineer with a background in mathematics and computer science. He previously worked as a software engineer at Google X on the Everyday Robots project, Microsoft, and at IronOx (W16). David's doctoral research focused on robotic systems manipulating non-rigid objects and was funded by a NASA Space Technology Research Fellowship. He has published research with the NASA Jet Propulsion Lab, Ames Research Center, and Google DeepMind. ### John B. Stroud, Founder John B. is a finance and operations professional with experience in airline operations, management consulting, and large-scale operations finance. He has a full-time MBA from Kellogg School of Management at Northwestern University in finance and strategy. From his time at United Airlines, John B. understands the inner workings of major international airlines and the inherent challenges of running manual baggage handling systems that he brings to Azalea Robotics. ### Company Launches [### Azalea Robotics - Robots moving bags at airports]( **TL;DR** - [**Azalea Robotics**]( is building robots to handle baggage between touchpoints at airports. Our robots work around the clock, never get tired, and never lose or damage your bag after check-in. **The Team** - [David]( and [John B.]( met in undergrad at the University of Georgia and have been close friends for 12 years. David has a PhD in Computer Science from USC and is an expert in soft-body robotic manipulation. John B. has an MBA from Kellogg and extensive experience in airline ground operations. They founded Azalea Robotics at the intersection of their combined strengths to modernize bag-handling systems at airports. **The Problem** - Airport baggage handling is broken. It requires an immense amount of back-breaking labor, using decades-old infrastructure at airports, all while passengers increasingly choose to cram everything into a carry-on because they don’t trust airlines to deliver their luggage on time and in one piece. Airlines and airports have an increasingly hard time hiring these workers and are plagued by frequent system outages and customer confusion and complaints during large weather events. **The Solution** - Robotic systems work around the clock, never get tired and damage your bag, never misidentify bags, and are significantly cheaper to deploy than manual labor. Our technology allows large robotic arms to handle all bag types and intelligently improve with every bag transferred. Check out a sneak peek of our system in action! [ **Our Customers** - We sell our systems to airports and airlines around the world. Depending on the size of their airport presence (i.e., is this a hub for a given airline?), airlines will either outsource or hire in-house baggage handling for their customers. Airports are typically public entities run by the local city or metropolitan area and can be more or less hands-on with baggage handling, depending on their passenger volume. Worldwide, airports and airlines spend $20B+ to handle 4.5B+ bags (and growing) every year! **Our Ask** - Everyone has a nightmare baggage story, and we’d love to hear yours at [mishandled@azalearobotics.com](mailto:mishandled@azalearobotics.com)! Otherwise, if you're interested in learning more or have someone you think we should talk to, let us know at [founders@azalearobotics.com](mailto:founders@azalearobotics.com)!

Weavel

weavel

https://weavel.ai

San Francisco, CA, USA

Weavel automates prompt engineering, delivering the best prompts 50x faster than humans. Simply input your prompt and receive optimized prompts with highest accuracy. Boost your prompt's accuracy by an average 20% in less than 5 minutes. Andrew and Jun built 10+ LLM-based products, open-sourced a prompt engineering platform, and co-authored a paper at a NeurIPS workshop in 2023. Hyun Jie worked on data analytics and optimization at Chartmetric and DevRev, and focused on growth marketing at Liner.

Automate prompt engineering & get best prompts 50x faster

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/weavel

https://yc-oss.github.io/api/batches/s24/weavel.json

Title: Weavel: Automate prompt & LLM engineering, 50x times faster than a human | Y Combinator URL Source: Markdown Content: ### Automate prompt & LLM engineering, 50x times faster than a human Weavel automates prompt and LLM engineering, delivering best prompts and algorithms 50x times faster. We do this by using LLMs and search algorithms to replace the manual trial-and-error of prompt engineering, but more efficiently - it is 3 times faster than the leading open source project. Weavel Founded:2023 Team Size:3 Location:San Francisco ### Active Founders ### Andrew Chung, Founder Andrew is co-founder and CEO of Weavel. Andrew previously led product + engineering teams for two years, and has experience in building various applications in AI, VR, web, and mobile. Prior to that, Andrew studied electrical & computer engineering at Seoul National University before taking leave of absence in his junior year to focus on building things. ### Hyun Jie Jung, Founder HyunJie is co-founder of Weavel, specializing in growth and data analytics. She studied data science and media at UC Berkeley and has experience working at Liner, Chartmetric, and DevRev, where she focused on marketing and data analysis. ### Junyoung Park, Founder Jun is co-founder of Weavel. Jun previously worked as researcher at NLP-focused AI lab and has experience in building various applications with LLM. Prior to that, Jun studied computer science & engineering at Seoul National University. ### Company Launches [### Weavel - Ape 🐒 Your first AI Prompt Engineer]( **☕️ TL;DR** ------------ * **Ape** is the ultimate **AI prompt engineer** 🐒, designed to optimize your prompts by reducing cost and latency while increasing performance. * Ape achieves an **impressive 94.5%** on the GSM8K benchmark, surpassing Vanilla (54.5%), CoT (87.5%) and DSPy (90.0%). * **Easy to set up evaluation**: Ape can auto-generate evaluation code and use LLMs as a judge, or you can use your own eval metrics. * Get set up in less than 15 minutes and see the difference. * [Schedule a meeting]( to discover more. Let's chat! 🙂 **🔒 Problem** -------------- You’re an engineer of an LLM app, trying to get the prompts just right. Every time you type something in, the output changes—so you tweak a word here and there, and it changes again. Sometimes the outputs looks better, sometimes not. But you’re never sure. Hours go by, all spent on prompt engineering. Getting the outputs you want can feel like an endless game of trial and error. And you’re not alone. Over the past few weeks, we’ve talked to over 100 YC companies, and a lot of them are facing the same challenges: * **Measuring output quality is hard** (You’re heavily relying on manual evaluations at the moment.) * **Prompt engineering does not work as you want** (You hate spending 5-7 hours a day searching for that one great prompt.) **🔑 Solution** --------------- We solve the problem with one simple formula: ``` good input + right guidance = better prompts ``` Today, we launch Ape, your first **AI Prompt Engineer**. Inspired by DSPy, Reflexion, Expel and other research papers, Ape iteratively improves your prompts. Here’s how Ape works: 1️⃣ Log your inputs and outputs to Weavel (with a single line of code!) 2️⃣ Let Ape filter the logs into datasets. 3️⃣ Ape then generates evaluation code and uses LLMs as judges for complex tasks. 4️⃣ As more production data is added, Ape continues refining and improving prompt performance. ### **How to use** **Create a Dataset** Change just one line of code to start logging LLM calls with the Weavel Python SDK. The SDK supports sync/async OpenAI chat completions and OpenAI structured outputs. You can also import existing data or manually create a dataset. **Create a Prompt** Write a prompt that corresponds to your dataset. You can add an existing prompt as the base version, or if you prefer, create a blank prompt and provide a brief description for Ape to create a prompt from scratch. **Optimize Prompts** To optimize your prompt using Ape, fill in the necessary information (e.g. JSON schema as you want) and then run the optimization process. An enhanced version of your prompt will be created and available soon. Ta-da! It’s that easy. Ape outperforms with a remarkable 94.5% score on the GSM8K benchmark, surpassing Vanilla (54.5%), CoT (87.5%) and DSPy (90.0%). With Ape, you can optimize the prompt engineering process, saving tons of time and cost while increasing performance. Ape is **open source**. [Check out our repository on GitHub.]( (We’d appreciate a star 🌟) **🚀 The Team** --------------- From left to right: [**Jun**]( [**Andrew**]( [**HyunJie**]( and [**Toby**]( — together we’re building Weavel. **Andrew** and **Jun** built 10+ LLM-based products, open-sourced a prompt engineering platform, and co-authored a paper at a NeurIPS workshop last year. **HyunJie** worked on data analytics and optimization at Chartmetric and DevRev, and focused on growth marketing at Liner. Then **Toby** joined, a full-stack engineer who worked at several early stage teams, shipping 5+ products. **🙏 Ask** ---------- * Try Ape! [Schedule]( a walkthrough with the Weavel team or email [hyunjie@weavel.ai](mailto:hyunjie@weavel.ai). * Share thoughts on our [Discord]( or DM us on [Twitter]( * If you know anyone struggling with prompt engineering or evaluations for LLM apps, connect them with us! * Copy & paste blurb: A YC company named Weavel has developed an AI prompt engineer (Ape in short) which continuously improves your prompts. It’ll save tons of time for you. You can grab a time [here]( for a demo from the founders.

David AI

david-ai

https://www.withdavid.ai/

San Francisco, CA, USA

Data for multimodal AI

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/david-ai

https://yc-oss.github.io/api/batches/s24/david-ai.json

Title: David AI: Data for multimodal AI | Y Combinator URL Source: Markdown Content: ### Data for multimodal AI David AI Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Tomer Cohen, Founder Co-founder and CEO at David AI. Previously, Chief of Staff at Scale AI and Consultant at McKinsey & Company. ### Ben Wiley, Founder Co-founder and CTO at David AI. Previously, at Scale AI - Head of Engineering for Scale’s Public Sector GenAI Platform. Before that - SWE at Microsoft.

Zephr

zephr

https://www.zephr.ai/

San Francisco, CA, USA

Zephr is an AI customer success manager that lets you manage hundreds of customers with ease. Our AI monitors customer health, identifies expansion opportunities and churn, and automates repetitive tasks.

AI customer success manager

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/zephr

https://yc-oss.github.io/api/batches/s24/zephr.json

Title: Zephr: AI customer success manager | Y Combinator URL Source: Markdown Content: ### AI customer success manager Zephr is an AI customer success manager that lets you manage hundreds of customers with ease. Our AI monitors customer health, identifies expansion opportunities and churn, and automates repetitive tasks. Zephr Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Bill Chen, Founder Co-founder of Zephr. Born in Shanghai, I grew up mainly in Vancouver, Canada. I earned my bachelor's in CS from Columbia. Before Zephr, I worked at Retool (W17) as a Deployed Engineer. ### William Hu, Founder Building Zephr, an AI customer success manager. Previously @ Retool, Robinhood. ### Company Launches [### Zephr - Your AI customer success manager]( Hello YC! We are William and Bill, the team behind [Zephr]( TL;DR ----- * Zephr is an **AI customer success manager** that lives in Slack. Zephr automates manual tasks like writing emails, creating Linear tickets, and updating Salesforce records. * **Want a global view?** Zephr comes with a customer health dashboard and automatically identifies expansion opportunities and churn. * **Have a large team?** Motivate them with our CSM leaderboard. The Problem ----------- Customer success teams drive post-sale engagement, ensuring customer satisfaction, retention, and growth. Unlike customer support, customer success is proactive and contributes directly to revenue goals. However, the jobs of CSMs are operationally heavy, with most of their time spent on repetitive tasks rather than strategic initiatives. This is where Zephr comes in! Introducing Zephr! ------------------ Zephr is the first AI customer success manager. Zephr lives in Slack and automates routine tasks, such as writing emails, escalating tickets, and updating Salesforce records. With Zephr, you can manage 100 customers with ease. In addition to the Slack bot, Zephr comes with a lightweight customizable customer health dashboard. Zephr monitors customer health and automatically identifies expansion opportunities and risky accounts. Have a large team? Zephr provides a leaderboard to keep your team engaged. Our AI automates all the boring stuff, so CSMs can focus on what matters: being the face of the company and building relationships that drive measurable value. Zephr is not just making it easier for customer success teams—we're redefining what customer success can be. The Team -------- We met at a high school research camp a decade ago, became coworkers at Retool, and are now co-founders! Bill was a member of the customer success team at Retool, so he has experienced these challenges first-hand. William, on the other hand, was an engineer at Retool and enjoys solving these problems with software. The Ask 🙏 ---------- If you're setting up a B2B success motion or know someone who is, [come talk to us]( We'd love to see how our tool could fit into your workflow.

Poka Labs

poka-labs

https://www.pokalabs.com/

San Francisco, CA, USA

Poka Labs is developing an AI platform to automate operations tasks in chemical manufacturing, beginning with production scheduling. Traditionally, these tasks are performed manually using spreadsheets. Our software seamlessly integrates with existing data sources such as data historians, emails, and PDFs to automate analytics, scheduling, changes, and communication within a single platform. Malay and Andrew met while pursuing their MBAs at Harvard Business School. Malay previously worked as an engineer in the specialty chemical industry, saving his employers over $100 million across US, China, and German plants. Andrew worked as a software engineer on data infrastructure at Meta and optimization problems at a seed-stage startup. He also completed a Masters degree at Harvard specializing in Machine Learning.

The modern operating system for chemical manufacturing.

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/poka-labs

https://yc-oss.github.io/api/batches/s24/poka-labs.json

Title: Poka Labs: The modern operating system for chemical manufacturing. | Y Combinator URL Source: Markdown Content: ### The modern operating system for chemical manufacturing. Poka Labs is developing an AI platform to automate operations tasks in chemical manufacturing, beginning with production scheduling. Traditionally, these tasks are performed manually using spreadsheets. Our software seamlessly integrates with existing data sources such as data historians, emails, and PDFs to automate analytics, scheduling, changes, and communication within a single platform. Malay and Andrew met while pursuing their MBAs at Harvard Business School. Malay previously worked as an engineer in the specialty chemical industry, saving his employers over $100 million across US, China, and German plants. Andrew worked as a software engineer on data infrastructure at Meta and optimization problems at a seed-stage startup. He also completed a Masters degree at Harvard specializing in Machine Learning. ### Jobs at Poka Labs San Francisco, CA, US / New York, NY, US $140K - $160K 1.00% - 2.00% 3+ years Poka Labs Founded:2023 Team Size:2 Location:San Francisco ### Active Founders ### Andrew Bass, Founder Andrew is the Co-Founder and CTO of Poka Labs. Before Poka, he worked on critical data infrastructure systems at Meta, as well as optimization software at a Series A startup (acquired) that helped mobility companies boost their revenue 40%. He has both an MBA and MS degree at Harvard where he focused on ML systems. ### Malay Shah, Founder Malay is the Co-Founder and CEO of Poka Labs. He earned degrees in Chemical Engineering and Economics from NC State and an MBA from Harvard Business School. With a background in the specialty chemicals industry, Malay has held various positions in operations and engineering working across plants in US, Germany, and China. His work in deploying chemical expertise with advanced analytics has saved his previous employers tens of millions of dollars. ### Company Launches [### Poka Labs: The Modern Operating System for Chemical Manufacturing]( ### Summary: * We help chemical manufacturers automate their production planning and scheduling without the need for spreadsheets or complex implementations * Schedule a demo - [ Hi everyone! We’re Andrew and Malay — the founders of Poka Labs. ### ❌ Problem Production planning is the “brains” of chemical operations. Yet even today, the $5.6 trillion chemical industry relies on spreadsheets and humans to manage the process. This leaves plants to constantly fight fires in order to meet customer orders on time and maximize manufacturing margins. Any change, such as inventory delays, labor shortages, or unexpected maintenance, further stresses operations. Existing systems, such as ERPs, are too rigid in their data inputs to adapt to these types of changes. ### ✅ Our Solution: Adaptive Production Planning with AI Poka Labs integrates with existing information (data historians, emails, PDFs, ERPs, etc) to put chemical production scheduling on **autopilot**. Our software automates analytics, scheduling, changes, and communication within one platform that anyone can use. With Poka Labs, chemical plants can: * Maximize revenue * Minimize transition costs * Eliminate messy spreadsheets * Increase visibility ### 🎉 Our Story [Malay]( is a chemical engineer who has worked in chemical plants across 3 continents. He experienced these issues firsthand and saved his prior employers over $100+ million on process improvement and production planning projects. He met [Andrew]( while they were pursuing their MBA at Harvard Business School. Andrew worked as a software engineer on data infrastructure systems at Meta before working on optimization problems at a seed-stage startup. He also completed a Masters degree at Harvard specializing in ML. Together, we’re passionate about deploying modern software in the chemical industry. ### ❓ The Ask * If you work in chemical manufacturing, we’d love to chat! Contact [malay@pokalabs.com](mailto:malay@pokalabs.com) * Share this post! Is there anyone in your network that deals with planning for chemicals? We’d love to chat with them * _Copy & paste blurb_: A team of Harvard grads created an AI-powered production planning platform designed for the chemical industry. It automates scheduling, changes, and analytics in one platform. Put your plant on autopilot with Poka Labs. Contact [malay@pokalabs.com](mailto:malay@pokalabs.com) to see a demo from the founders.

Lilac Labs

lilac-labs

https://www.drive-thru.ai/

San Francisco, CA, USA

At Lilac, we automate the person taking order at the drive thru with a voice AI. We're building this for Quick Service Restaurants (QSRs) dealing with an historical labor shortage and rising wages. Previous attempts at drive-thru voice ordering are costly to implement and have failed to deliver the accuracy and latency needed. It's now possible to build a voice interface that passes the threshold for a great customer experience. In the United States, there are 200,000 Drive-Thrus handling 6 Billion visits a year. At 3 minutes per order, that's 34,000 human years spent on taking orders annually. Per location, on average we can deliver around $100,000 of value in terms of labor savings, upsell revenue lift, and training costs.

We automate the person taking orders at drive-thrus with a voice AI

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/lilac-labs

https://yc-oss.github.io/api/batches/s24/lilac-labs.json

Title: Lilac Labs: We automate the person taking orders at drive-thrus with a voice AI | Y Combinator URL Source: Markdown Content: ### We automate the person taking orders at drive-thrus with a voice AI At Lilac, we automate the person taking order at the drive thru with a voice AI. We're building this for Quick Service Restaurants (QSRs) dealing with an historical labor shortage and rising wages. Previous attempts at drive-thru voice ordering are costly to implement and have failed to deliver the accuracy and latency needed. It's now possible to build a voice interface that passes the threshold for a great customer experience. In the United States, there are 200,000 Drive-Thrus handling 6 Billion visits a year. At 3 minutes per order, that's 34,000 human years spent on taking orders annually. Per location, on average we can deliver around $100,000 of value in terms of labor savings, upsell revenue lift, and training costs. Lilac Labs Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Tony Kam, Co-Founder / CEO Tony is the co-founder and CEO of Lilac Labs. Tony studied EECS at UC Berkeley where focus on operating systems. Before Lilac, Tony worked at Tesla as an engineer, where he owned the display and touch component of the infotainment system. Tony also worked on the performance and reliability of driving visualization. Prior to that, Tony worked on manufacturing automation at Intel and robotics simulation at CloudMinds. ### Shelden Shi, Co-Founder / CTO Shelden is the Co-Founder and CTO of Lilac Labs. Shelden studied CS and CogSci at UC Berkeley, where he conducted research training ML models to predict emotions via audio data. Before Lilac, Shelden was the founding engineer at Symbolic, leading the development of a Fintech lending platform with ~$1B in AUM and 30k monthly active users. Prior to that, Shelden worked at Flatiron Health, an oncology data unicorn, where he trained and built the evaluation pipeline for cancer diagnostic models. ### Company Launches [### Lilac Labs: Drive-thru Order Taking with Voice AI]( **TLDR: Lilac Voice is an AI team member that takes orders at your drive-thru.** -------------------------------------------------------------------------------- ❌ **Problem:** **The quick service restaurant (QSR) industry is desperate for solutions to reduce labor costs.** ---------------------------------------------------------------------------------------------------------------- Grappling with rising wages, high staff turnover, and an unprecedented labor shortage, quick-service restaurants (QSRs) have increased prices to maintain profitability, but have ran into the limit of what consumers are willing to accept. Drive-thru’s makes up 70% of QSR revenue as a channel and is a significant opportunity for automation. In the U.S., there are 200,000 Drive-Thrus that handle 6 billion visits a year. ✅ **Solution: We automate the person taking orders at the drive thru with a voice AI.** --------------------------------------------------------------------------------------- Lilac Voice is a multi-lingual AI agent that takes orders from customer through the drive-thru speaker post and sends it directly into the kitchen. It’s perfectly trained, understands the menu, and can answer questions about ingredients and allergies. With Lilac Voice, QSR’s with drive-thrus can: 1) save labor cost of up to 1 full-time employee, 2) boost revenue through consistent and relevant upsell, 3) improve the customer experience with faster speed of service and higher order accuracy, and 4) improve staff retention! As an example: In CA, as of April 1st, the fast food minimum wage grew from $16 to $20. For a drive-thru operating 16 hours a day, 365 days a year, that’s $100,000+ in labor savings alone. **🙋Our Ask: How you can help.** -------------------------------- **Share this post!** We’re looking for more customers to onboard for this Summer! We’d love intros to franchisee operators, restaurant groups, or leadership at corporate chain. **Quick blurb to copy & paste:** Lilac Labs is offering free pilots for their voice AI drive-thru solution. The team consists of ex-Tesla engineers and Berkeley researchers. Learn more at [ For a demo and free pilot, contact [tony@lilaclabs.ai](mailto:tony@lilaclabs.ai). \- [Tony]( and [Shelden](

Remade

remade

https://www.remade.ai/

San Francisco, CA, USA

Remade uses AI to create studio-quality videos. For example, ScentBird, a fragrance subscription service, uses Remade to create TikTok ad hooks and increase conversion. Traditional videography is labour-intensive, slow, and expensive. Enterprises spend thousands on it, while smaller businesses often can't afford it. Remade reduces the cost of professional videos by 100x and cuts delivery time from weeks to 15 minutes. Using AI and social media data, we personalize content creation and optimize product ads. Our mission is to streamline visual content generation across multiple industries, making it faster and more accessible for businesses.

Automating Video Ad Workflows using AI

B2B

B2B -> Marketing

S24

Active

Early

https://www.ycombinator.com/companies/remade

https://yc-oss.github.io/api/batches/s24/remade.json

Title: Remade: Automating Video Ad Workflows using AI | Y Combinator URL Source: Markdown Content: ### Automating Video Ad Workflows using AI Remade uses AI to create studio-quality videos. For example, ScentBird, a fragrance subscription service, uses Remade to create engaging TikTok ad hooks and increase conversion. Traditional videography is labour-intensive, slow, and expensive. Enterprises spend thousands on it, while smaller businesses often can't afford it. Remade reduces the cost of professional videos by 100x and cuts delivery time from weeks to 15 minutes. Using AI and social media data, we personalize content creation and optimize product ads. Our mission is to streamline visual content generation across multiple industries, making it faster and more accessible for businesses. Remade Founded:2024 Team Size:4 Location:San Francisco ### Active Founders ### Alex Matthews, Founder Alex is the CEO of Remade, a company enabling businesses to automate their entire visual content marketing using AI. Remade's web application transforms basic, low quality photos of any product into professional hooks. Alex holds a BA in Computer Science from the University of Cambridge. He has contributed to earning £700k+ in revenue/ funding in past ventures. ### Christos Antonopoulos, Founder Christos Antonopoulos is the co-founder of Remade. Remade transforms basic, low quality photos of any product into professional advertisement videos . He holds a BA and MEng in Information & Computer Engineering from the University of Cambridge and has research contributions in Machine Learning for Medical Diagnosis and Natural Language Interfaces. ### Blendi Bylygbashi, Founder Blendi is the co-founder of Remade, a company focused on professional photography using AI. He holds a BA and an MEng in Information and Computer Engineering from the University of Cambridge. At Transport for London, he developed deep learning models for CCTV event detection. His research on intra-cranial hypertension was published in the Lancet Neurology Journal. He also managed the BlenDigi YouTube channel, growing it to almost 1 million subscribers and generating $200,000 in ad revenue. ### Rehan Sheikh, Founder Rehan is the CTO and co-founder of Remade, a company focused on professional photography using diffusion models. He holds a BA and MEng in Information & Computer Engineering from the University of Cambridge! ### Company Launches [### Remade: Automating video ad workflows using AI]( [Launch Video]( **Tl;DR: Remade automates visual marketing workflows. Lifestyle product brands generate TikTok hooks that land 130% higher clickthrough rate.** **Try it now:** [** Hi everyone! We're Alex, Rehan, Chris, and Blendi — the founders of [Remade]( We are excited to announce our product image-to-video workflow, enabling the transformation of low-quality product images into video hooks that sell. How it works: ------------- 1. **Upload an image of your product** 2. **Use “AI Backgrounds” to create a scene for your product video.** 3. **Generate your TikTok hook** [TikTok Hook]( Use Cases --------- **Marketing Teams** Marketing teams use Remade to generate short-form product reels in minutes. We replace a process that corporations outsource to marketing agencies for thousands of dollars in 3-clicks. **Marketplaces** Marketplaces use Remade’s Enterprise API to quickly generate product videos for their catalogs. These videos help sellers showcase products with dynamic, attention-grabbing content, which is proven to boost conversion, reduce bounce rate, and enhance the shopping experience. **Delivery Platforms** Delivery platforms use Remade to generate videos for their food listings, enabling a TikTok-style User Experience. **👋**Asks: How you can help ---------------------------- Warm intros to Heads of Image Catalogue at Delivery platforms such as Zomato, Uber Eats, Deliveroo, Glovo and Grubhub. Warm Intros to CMO’s / Heads of Content of lifestyle product brands. Email us at [founders@remade.ai](mailto:founders@remade.ai) for 24/7 support. **Try it here:** [** ### Other Company Launches ### Remade: GenAI product photography for businesses Generate studio-quality product photoshoots from your smartphone. [Read Launch ›]( #### YC Sign Photo

XTraffic

xtraffic

https://XTraffic.com/

Dallas, TX, USA

XTraffic is at the intersection of advancements in sensor technology and affordability. Where it would previously cost a city up to $100,000 per intersection to create intelligent traffic lights, we can accomplish the same for pennies on the dollar. This means entire cities can affordably upgrade their infrastructure - and some already are. We are live in multiple Texas cities, with both ongoing and successful pilots, corridors of multiple intersections, and soon to be entire cities. Our customers enjoy less traffic, better safety, and data on which to build their future.

Technology for cities to automate and manage their traffic lights.

Government

Government

S24

Active

Early

https://www.ycombinator.com/companies/xtraffic

https://yc-oss.github.io/api/batches/s24/xtraffic.json

Title: XTraffic: Technology for cities to automate and manage their traffic lights. | Y Combinator URL Source: Markdown Content: ### Technology for cities to automate and manage their traffic lights. XTraffic is at the intersection of advancements in sensor technology and affordability. Where it would previously cost a city up to $100,000 per intersection to create intelligent traffic lights, we can accomplish the same for pennies on the dollar. This means entire cities can affordably upgrade their infrastructure - and some already are. We are live in multiple Texas cities, with both ongoing and successful pilots, corridors of multiple intersections, and soon to be entire cities. Our customers enjoy less traffic, better safety, and data on which to build their future. XTraffic Founded:2022 Team Size:4 Location:Dallas, TX ### Active Founders ### Luke Adams, Founder Aerospace Engineering + Computer Science. 3 years @ SpaceX wearing many hats on the Starship program. Now, working to bring traffic and city infrastructure into the modern age @ XTraffic! ### Everett Ivy, Founder Hi! I have studied computer science, worked on control systems at Amazon, and been a professional gamer. Now with my friends and cofounders at XTraffic I am making traffic lights smarter. ### Brian Payne, Founder Background in control systems and embedded hardware at Amazon. Love all things robotics, now building hardware and software systems to solve traffic! ### Company Launches [### XTraffic - Making traffic lights smarter and travel times faster]( **Tl;dr:** [XTraffic]( upgrades traffic lights to work together as an intelligent system, communicating and coordinating to reduce traffic and improve safety. The autonomous control of traffic lights gives back to both city officials and their citizens their most valuable resource - time. — Hi everyone, we’re [Everett]( [Luke]( and [Brian]( the founders of XTraffic. **Why Now?** The combination of rapidly advancing technology and smart-city initiatives has created a unique intersection in time where intelligent traffic control is not just possible but affordable. As smart city initiatives are being adopted worldwide, municipalities of all sizes are looking for ways to affordably transition to intelligent infrastructure. XTraffic leverages this trend by providing cities with a scalable, intelligent system that upgrades existing traffic lights into a self-optimizing network. **Market Opportunity** The global smart city market is projected to reach [$3.84 trillion by 2029]( with traffic management as a requirement to aid in driving this growth. Urban areas are expanding, and traffic congestion is a major pain point that costs the U.S. [more than $70.4 billion in 2023]( a 15% increase from 2022. XTraffic is tapping into this immense market opportunity by offering a solution that not only reduces traffic congestion but also enhances safety, reduces emissions, and increases overall quality of life. **Why XTraffic?** Our system isn’t just about less traffic; it’s about smarter use of our infrastructure. XTraffic's approach allows traffic lights to 'talk' to each other, making real-time decisions based on current conditions across an entire network. This holistic view enables our system to adapt dynamically to changing traffic patterns, emergencies, and other factors - this significantly reduces delays and optimizes traffic flow across entire cities. With our solution, cities can avoid the massive costs of overhauling infrastructure. Instead, they can implement an affordable, flexible system that integrates seamlessly with existing technology. This reduces the barrier to entry and allows for rapid deployment, scaling from single intersections to entire metropolitan areas. **Call to Action** We’re excited to be part of Y Combinator, and we’re looking forward to connecting with cities, investors, and partners who share our vision for smarter, safer, and more efficient urban environments. If you’re interested in learning more or discussing opportunities, check out [ or reach out directly to our team. Let’s work together to give people back their most valuable resource: time.

camfer

camfer

https://www.camfer.dev/

San Francisco, CA, USA

We’re building the first AI mechanical engineer that collaborates with humans to do design tasks end-to-end. Human engineers can talk to Camfer to build, test, and iterate 3D designs natively on CAD platforms.

Building the world’s first Al mechanical engineer.

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/camfer

https://yc-oss.github.io/api/batches/s24/camfer.json

Title: camfer: Building the world’s first Al mechanical engineer. | Y Combinator URL Source: Markdown Content: ### Building the world’s first Al mechanical engineer. We’re building the first AI mechanical engineer that collaborates with humans to do design tasks end-to-end. Human engineers can talk to Camfer to build, test, and iterate 3D designs natively on CAD platforms. camfer Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Arya Bastani, Founder/CEO Before working at AWS and graduating from UC Berkeley in 2023, I was president of my high school FRC robotics team - ranked 4th in the world. This is where I met Roth Vann. While studying CS @ Berkeley: I was Chief EECS Engineer on the Formula Electric Racing team, I conducted research in Professor Anant Sahai’s lab doing brainwave (EEG) classification and generation using transformers and stable diffusion, and was President of the Iranian Students Cultural Org. More @ aryabastani.com ### Keaton Elvins, Founder EECS honors grad @ UC Berkeley, helped launch Amazon Q to millions of users ### Roth Vann, Founder Dropped out of UCR to work on ads at Meta. Dropped out of Meta to build Camfer.

Henry

henry-2

http://www.henry.ai

New York, NY, USA

Henry is an AI copilot for commercial real estate (CRE) brokers that seamlessly integrates a brokerage’s internal data set with external sources to generate custom presentations and financial modeling for deals. Our mission is to help CRE brokers close more deals faster, earning more while doing less repetitive work. We’re initially focusing on enabling brokers to generate deal decks in seconds—a task that typically consumes 20+ hours a week across multiple departments within a brokerage.

Generative AI for Commercial Real Estate Professionals

Real Estate and Construction

Real Estate and Construction

S24

Active

Early

https://www.ycombinator.com/companies/henry-2

https://yc-oss.github.io/api/batches/s24/henry-2.json

Title: Henry: Automating Deal Decks for Commercial Real Estate Brokers | Y Combinator URL Source: Markdown Content: ### Automating Deal Decks for Commercial Real Estate Brokers Henry is an AI copilot for commercial real estate (CRE) brokers that seamlessly integrates a brokerage’s internal data set with external sources to generate custom presentations and financial modeling for deals. Our mission is to help CRE brokers close more deals faster, earning more while doing less repetitive work. We’re initially focusing on enabling brokers to generate deal decks in seconds—a task that typically consumes 20+ hours a week across multiple departments within a brokerage. Henry Founded:2024 Team Size:3 Location:New York ### Active Founders ### Sammy Greenwall, Founder, CEO Sammy is the Co-Founder and CEO of Henry, Co-Founder and former CRO of Lev (which he scaled 0 to Series B / $10M+ run rate), and a retired real estate finance professional. Sammy was born and raised in the Bay Area and played college basketball at Swarthmore College. Sammy is passionate about building great products in large and stubborn markets. ### Adam Pratt, Founder 2x Founder, Currently CTO and Co-Founder @ Henry. Previously, Firefighter (Hamilton, NY - Station 19) and Co-Founder @ Halligan (Fire Department Saas Platform). Aquired by Vector Solutions in 2019 ### Company Launches [### Henry - AI copilot for commercial real estate brokers]( Hi everyone! We are Sammy and Adam, and we’re creating an AI copilot that automates the deal deck creation and financial analysis process for CRE (commercial real estate) brokers. For example, [Henry]( can create a full deal package for a broker selling an office building in Dogpatch in minutes instead of weeks. This will ensure that brokers maximize their time in the most value-added part of their business: relationships and sales. Traditional brokers often spend as much as 50% of their time on tasks that do not contribute to their bottom line. From basic financial analysis to marketing presentations to win future business to basic operational support, brokers often struggle with the manual and time-consuming realities of their business. These tasks are an incredibly painful bottleneck for brokers, which interferes with their primary goal of _building relationships to buy and sell property_. We are creating [Henry]( to solve this problem. Henry is an AI copilot that takes all of the messy, unstructured data that defines CRE transactions and consolidates it into clean marketing deliverables & financial analyses in minutes rather than weeks. Long term, we plan on automating the entire deal flow process for brokers to make their cycle time for a deal an order of magnitude faster. You can find an example of what we do below: [ I ([Sammy]( led Lev for the last five years, a 200+ person series B real estate financing marketplace that I co-founded. During this time, I realized that brokers were often bottlenecked by manual processes & antiquated technology, a problem optimally solved with advances in AI-driven technology. This led me to my partnership with [Adam]( who has deep experience in creating AI-enabled solutions for thorny problems that plague traditional businesses. **How you can help:** --------------------- * Know any CRE brokers? We’d love to talk to them about how we can make their lives easier & their paychecks larger. Contact us at [sammy@henry.ai](mailto:sammy@henry.ai)

ACX

acx

https://www.acxtherapeutics.com/

San Francisco, CA, USA

ACX is the only company that has successfully reproduced the compounds that bacteria use to kill microbes for therapeutic development. Our patentable technology, which comprises synthetic compounds that mimic natural substances, has applications in humans, animals, and crops. We are beginning with the elimination of crop pathogens—harmful to pests but beneficial for humans!

Therapeutics inspired by bacteria's natural killing abilities

Healthcare

Healthcare -> Industrial Bio

S24

Active

Early

https://www.ycombinator.com/companies/acx

https://yc-oss.github.io/api/batches/s24/acx.json

Title: ACX: Therapeutics inspired by bacteria's natural killing abilities | Y Combinator URL Source: Markdown Content: ### Therapeutics inspired by bacteria's natural killing abilities ACX is the only company that has successfully recreated synthetically the compounds that bacteria use to kill microbes for therapeutic development. Our patentable technology has applications in humans, animals, and crops. We are beginning with the elimination of crop pathogens—harmful to pests but beneficial for humans! ACX Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Emmanouela Petsolari, Founder Emmanouela is the Co-Founder & CEO of ACX and PhD in Biochemistry and Biophysics from the University of Cambridge. Previously, she held several research positions working in immunology, cancer, malaria vaccine development and viral drug discovery (in institutes like Barts Cancer Institute CRUK, Cambridge University, King’s College London, Institute Curie France and Imperial College London). ### Melina Petsolari, Founder Melina is the Co-founder & CTO of ACX and PhD in Computer Science from King's College London. Previously, she held several research positions spanning digital health, robotics, technology-enable interventions, HCAI and NLP (in institutes like Cambridge University, King’s College London, National Health Service (NHS) in England and Francis Crick Institute). ### Company Launches [### 🧬🦠 ACX – Therapeutics inspired by bacteria's natural killing abilities]( Hi everyone, We are [**ACX**]( We’re two PhD’s in Biochemistry/Biophysics and Computer Science from the University of Cambridge and King’s College London developing a new type of therapy with applications in everything from cancer to agriculture. We have discovered a new molecular weapon that naturally occurs in bacteria to eliminate bad microbes with high specificity. We are harnessing this natural killing mechanism to first provide more efficacious pest control measures. ### **Team:** 👩🏼‍🔬[**Emmanouela Petsolari**]( – Molecular Geneticist and Biochemist with 8 years of research experience in drug discovery and development (from leukemia, ovarian, and breast cancer as well as viral and bacterial infections). 👩🏼‍🔬 [**Melina Petsolari**](  – Computer Scientist and Designer with extensive experience in HCI, AI, and healthcare developing hardware and software for applications in digital health, biotech, and privacy. **❌ Problem:** -------------- ### **_In humans_** Despite billions of dollars being spent each year on cancer therapeutics and cancer research, more than 10 million patients still die every year from the disease. 1. ~90% of cancer-related deaths in patients receiving chemotherapy are caused due to ineffective treatments that have off-target effects ●  Cancer relapse and metastasis formation further lead to less than five-year survival rates ●  Current treatments cause high toxicity and adverse side effects due to a lack of on-target specificity, which further causes disruption of healthy cells ### **_In animal farming and agriculture_** There is more disease impacting our livestock and crops than ever before - and this comes at a time when the human population is also exploding. 1. Manure from livestock and extensive use of limited therapeutics for growth promotion and disease prevention in animal breeding as well as overuse of pesticides in crops ●  One billion kilos of chemicals are used annually to combat crop pests 2. Spread of pathogenic agents that have adapted in previously used medications 3. Failure of commonly used pesticides and insecticides has been documented in nearly 1000 distinct pest species worldwide ●  This leads each year to the world’s food supply facing an up to 30% loss due to insect pests alone, and this number is continuously increasing ✅ **Our Solution:** ------------------- What do these three areas have in common? Existing therapeutics are either no longer effective or have never worked to the extent necessary for achieving positive outcomes. We have discovered a common biological pathway that can be targeted from the human level down to the animal level and even to the crop level to develop robust therapeutics capable of overcoming pathogen and cancer evolution. ### ✅ ✅ **Specifics:** ACX is the only company that has been able to reproduce the mechanism that bacteria use to kill microbes for therapeutics, and we are starting by eliminating crop pathogens: 1. We have _in vitro_ validation data of our therapeutic showing high inhibition and specificity in the cell line 2. We are initially focusing on animal health and crop production due to the experimental validation of our therapeutic's effectiveness on a shared pathogen 3. We are developing drug delivery systems that minimize toxicity and immunogenicity while providing precise spatiotemporal control for targeted drug release 4. Considering the human case, our therapeutic has the potential to treat various cancer types and become a standard-of-care treatment with blockbuster potential Illustration of our solution. Nanoparticles carrying the killer compound (orange) infiltrate the target cell like a Trojan horse and activate drug release upon targeting our newly discovered pathway. ### 💡**Key facts about our solution:** ➔   High killing efficacy ➔   Designed to specifically target malignant cells while preserving the surrounding healthy cells and ensuring no toxicity or adverse side effects ➔   Highly suitable to become a platform solution (i.e., therapeutic development pipeline expanded to multiple disease areas and organisms) ➔   Scalable, stable, and easy to manufacture 👋**Our Asks:** --------------- * Share this post with your network and help spread the word! * If you’re as excited as we are about this novel approach, email us to learn more about it at [emmanouela@acxtherapeutics.com](mailto:emmanouela@acxtherapeutics.com)

ClaimSorted

claimsorted

https://claimsorted.com

ClaimSorted helps insurance companies remove the hassle of managing claims by enabling them to outsource their claim operations to us. This service is known as a Third Party Administrator (TPA). Unlike traditional TPAs, we blend AI and best-in-class experts to deliver a 5-star customer experience, minimise mistakes and speed up claim assessment.

Making it easy for insurance companies to process claims

Fintech

Fintech -> Insurance

S24

Active

Early

https://www.ycombinator.com/companies/claimsorted

https://yc-oss.github.io/api/batches/s24/claimsorted.json

Title: ClaimSorted: Making it easy for insurance companies to process claims | Y Combinator URL Source: Markdown Content: ### Making it easy for insurance companies to process claims ClaimSorted helps insurance companies remove the hassle of managing claims by enabling them to outsource their claim operations to us. This service is known as a Third Party Administrator (TPA). Unlike traditional TPAs, we blend AI and best-in-class experts to deliver a 5-star customer experience, minimise mistakes and speed up claim assessment. ### Jobs at ClaimSorted London, England, GB £86K - £132K GBP 0.50% - 1.00% 3+ years ClaimSorted Founded:2024 Team Size:2 Location: ### Active Founders ### Pavel Gertsberg, Founder Before starting ClaimSorted, Pavel built a pet insurance company, Fluffy, which he scaled to over 20,000 customers working with some of the largest insurers. Before starting his insurance company, Pavel worked as a Head of Growth building marketing, sales and product functions in SaaS and InsurTech companies. ### German Mikulski, Founder Co-Founder and CTO at ClaimSorted. Previously founded Fluffy, a pet insurance company, automating ~70% of back-office processes with AI. Formerly at Deutsche Bank, where he developed Big Data systems processing over $100 million in transactions ### Company Launches [### ClaimSorted: Hassle-free insurance claims with AI]( **TL:DR: We help insurers manage claims efficiently by outsourcing claim operations to us. We then use AI to make the process faster and cheaper.** **🙋 Ask: looking for intros to insurance companies.** ### **Problem** If you've ever submitted an insurance claim and it took ages to get your money back, here's why: **Insurers outsource claims** to claim outsourcing agencies, known as **Third Party Administrators (TPAs)**. Imagine a huge warehouse with **thousands of people using pen and paper** to process millions of claims. That’s why it's so slow. ### **Solution** At [ClaimSorted]( we are an **AI-first TPA for insurance claims**. We automate fraud checks, compliance, claim decision-making, and **deliver payouts in minutes**. Our AI is paired with a team of experts to ensure accuracy. ### **Team** We **previously built an insurance company** and know the struggles of working with TPAs. We aim to make every claim a positive experience for customers and drive cost efficiencies for insurers. _Fun fact, _[_German_]( was the best man at _[_Pavel_]( wedding_ ### **Ask:** **If you know any insurance companies in the US, UK, or EU, please email us at [founders@claimsorted.com](mailto:founders@claimsorted.com)**

RowBoat Labs

rowboat-labs

https://www.rowboatlabs.com

San Francisco, CA, USA

RowBoat Labs offers pre-trained LLM agents for customer support, which continuously learn from usage. Our LLMs are safe and brand-aligned. RowBoat agents seamlessly integrate into your systems and take actions where necessary.

LLM Agents for Customer Support

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/rowboat-labs

https://yc-oss.github.io/api/batches/s24/rowboat-labs.json

Title: RowBoat Labs: LLM agents for customer support in fintech | Y Combinator URL Source: Markdown Content: ### LLM agents for customer support in fintech RowBoat Labs offers pre-trained LLM agents for customer support, which continuously learn from usage. Our LLMs are safe and brand-aligned. RowBoat agents seamlessly integrate into your systems and take actions where necessary. RowBoat Labs Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Arjun Maheswaran, Founder I previously co-founded and served as CTO of Agara, a customer support AI startup that was acquired by Coinbase in 2021. Over the past decade, I've focused primarily on Deep Learning for Natural Language Processing (NLP), at Twitter Cortex, Agara, and Coinbase. ### Ramnique Singh, Founder Co-founder at RowBoat Labs. Helping companies supercharge CX using LLMs. ### Akhilesh Sudhakar, Founder Building LLM agents for customer support at RowBoat Labs. Most recently, led generative AI product for CX at Coinbase. Previously, ML scientist at Agara AI (autonomous customer support). ### Company Launches [### RowBoat Labs - LLM agents for human-like customer support]( **Tl;dr:** [RowBoat]( is a pre-trained customer support LLM agent that seamlessly plugs into your systems, handles customer conversations, and performs tasks just like an expert human agent would. **Problem** ----------- Customer support is one of those rare opportunities for a brand to connect directly with its users. The best brands know this and invest heavily in coaching their human agents to deliver a great support experience. But when it comes to automated support, most solutions rely on LLMs that aren’t specially designed for customer support and can’t learn from experience. This often leaves users stuck with impersonal and long FAQ-style responses in small chat windows, often missing the help they actually need. Internal teams might see some early wins with a public LLM + RAG setup, but that progress usually hits a wall fast. Before long, engineers are spending more time debugging common LLM issues instead of focusing on what actually matters: delivering great customer support. As a result, customer satisfaction rates (measured by surveys) get nowhere close to that of human agents. **Solution** ------------ RowBoat is built and fine-tuned specifically for customer support * **Pre-Trained:** RowBoat is trained on a vast corpus of support conversations and further refined through self-play. It's like hiring a highly experienced customer support agent right from day one. * **Brand-Aligned:** RowBoat automatically indexes your public and internal knowledge, fine-tuning itself to align with your brand. * **Continuous Improvement:** RowBoat learns from every user interaction. When connected to your user metrics, such as resolution rates, RowBoat critiques its own performance to optimize for them continuously. … for internal engineering teams to build exceptional customer experience * **Plug & Play:** A drop-in replacement for GPT-4+ class LLMs, RowBoat offers immediate improvements in resolution accuracy. Our SmartRAG system readily integrates with your existing Elasticsearch or embedding-based retrieval systems for improved grounding. * **Tool Use & Personalization:** Equipped with a library of predefined functions, RowBoat can interact with and perform tasks on internal and external APIs. This makes RowBoat’s conversations highly contextualized to the user. * **Self-hostable:** RowBoat can be hosted inside your company’s cloud, especially for privacy-sensitive use cases. Seamless conversations… … with continuous coaching **Who we are** -------------- We're a team of three engineers who have worked together for the last 7 years. [Arjun]( co-founded Agara, a customer support AI startup where [Ramnique]( and [Akhilesh]( were part of the founding team. In 2021, Agara was acquired by Coinbase, where we built their automated customer support. We have published research and hold patents on LLMs, Reinforcement Learning, embeddings, and customer support. **Our Ask** ----------- If your company has a customer support function, we’d love to connect with your CX or engineering team. Please reach out to us at [founders@rowboatlabs.com](mailto:founders@rowboatlabs.com). We’ll bring an LLM agent trained for your brand to our call 😊

Olive Legal

olive-legal

https://olive.legal

San Francisco, CA, USA

Olive uses AI to summarize client medical records for personal injury lawyers. We're at $5k MRR after launching five weeks ago, and law firms choose us because we double paralegal efficiency. Sam's ex-girlfriend introduced him to Greg back at CMU in 2017, and while that relationship didn't last, their friendship has. After undergrad, Greg went to Harvard Law School, while Sam worked for three years at Jane Street, including a year in Hong Kong where he built out a satellite dev team for the algo options trading desk. Greg graduated, Sam quit, and we founded Olive with a big idea: use AI to make the law more accessible. We started with AI in corporate law given Greg's background, but quickly realized the space was crowded, and turned our attention to the under-competed $65B personal injury market. AI disruption makes a lot of sense in personal injury because the incentives are aligned—plaintiff lawyers are paid on contingency, and therefore love time-saving tools. We have competitors who have proven substantial demand for medical chronologies, but they operate at best on hybrid human/AI approaches with multi-day turnarounds. We think there's space for an AI solution that cuts humans out of the loop entirely with instant turnarounds, and we think we're the right team to do it. Up next, we will capture an increasing share of the value paralegals provide personal injury lawyers. We also see Olive expanding beyond just personal injury—interpreting unstructured medical data is critical for insurers to defend malpractice claims, class action firms to assemble plaintiffs, claimants to appeal insurance denials, providers to improve outcomes, the Social Security Administration to process disability applications speedily—we could go on. We're on a mission to remove barriers to information transfer, and therefore make justice more accessible.

AI medical summaries for personal injury lawyers.

B2B

B2B -> Legal

S24

Active

Early

https://www.ycombinator.com/companies/olive-legal

https://yc-oss.github.io/api/batches/s24/olive-legal.json

Title: Olive Legal: AI medical summaries for personal injury lawyers. | Y Combinator URL Source: Markdown Content: ### AI medical summaries for personal injury lawyers. Olive uses AI to summarize client medical records for personal injury lawyers. We're at $13k MRR after launching eight weeks ago, and law firms choose us because we double paralegal efficiency. Sam's ex-girlfriend introduced him to Greg back at CMU in 2017, and while that relationship didn't last, their friendship has. After undergrad, Greg went to Harvard Law School, while Sam worked for three years at Jane Street, including a year in Hong Kong where he built out a satellite dev team for the algo options trading desk. Greg graduated, Sam quit, and we founded Olive with a big idea: use AI to make the law more accessible. We started with AI in corporate law given Greg's background, but quickly realized the space was crowded, and turned our attention to the under-competed $65B personal injury market. AI disruption makes a lot of sense in personal injury because the incentives are aligned—plaintiff lawyers are paid on contingency, and therefore love time-saving tools. We have competitors who have proven substantial demand for medical chronologies, but they operate at best on hybrid human/AI approaches with multi-day turnarounds. We think there's space for an AI solution that cuts humans out of the loop entirely with instant turnarounds, and we think we're the right team to do it. We're focusing on the medical malpractice niche within personal injury, because there's a massive access to justice problem: medical malpractice lawyers decline most cases under $250k since they're too expensive to litigate. An estimated 80% of medical malpractice victims can't secure representation right now, and we're on a mission to change that by making the litigation process cheaper, at the same time unlocking a massive market of latent demand. Olive Legal Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Greg Volynsky, Founder Co-founder and CEO of Olive. Greg graduated Harvard Law School cum laude, where he focused on administrative law, comparative electoral systems, and avoiding contract law. Greg was a summer associate at Cravath. He bootstrapped his first company, which continues to operate, as a freshman at Carnegie Mellon. Greg was a fellow at BRI Excel Ventures. Greg is interested in 20th century political history, Soviet bard music & climbing. ### Sam Damashek, Founder Sam is the co-founder and CTO of Olive. He worked for three years at Jane Street on the options trading desk writing algorithmic strategies using applied ML, for two years in NYC and then one year in Hong Kong, where he built out a satellite dev team for the Asia options markets. He graduated with a BS in Computer Science from CMU, where for some reason he led a fledging constitutional law debate team, never to victory though frequently to Ohio. ### Company Launches [### Olive Legal: AI summaries of medical records for personal injury lawyers]( **tl;dr:** Olive uses AI to summarize client medical records for personal injury lawyers. We're at $5k MRR after launching five weeks ago, and PI firms choose us because we double the efficiency of their paralegals. Hi everyone! We’re [Sam]( and [Greg]( and we’re the team behind [Olive]( Sam's ex-girlfriend introduced him to Greg back at CMU in 2017, and while that relationship didn't last, our friendship has. After undergrad, Greg (left) went to Harvard Law School ⚖️, while Sam (right) worked for three years at Jane Street, including a year in Hong Kong, where he built out a satellite dev team for the algo options trading desk 📈. Greg graduated, Sam quit, and we founded Olive with a big idea: use AI to make the law more accessible. Given Greg's background, we started with AI in corporate law but quickly realized the space was crowded and turned our attention to the under-competed $65B personal injury market. Why personal injury law? ------------------------ The incentives are aligned—plaintiff lawyers are paid on contingency and, therefore, love time-saving tools. Paralegals are expensive, and LLMs are getting good enough that, with care, they can replace specific paralegal tasks. Why Olive? ---------- We have competitors who have proven substantial demand for medical chronologies, but they operate at best on hybrid human/AI approaches with multi-day turnarounds. We think there's space for an AI solution that cuts humans out of the loop entirely with instant turnarounds, and we think we're the right team to do it. Okay, but actually, why call it Olive 🫒? ----------------------------------------- I guess we liked the color scheme? What’s next? ------------ We will capture an increasing share of the value paralegals provide personal injury lawyers. We also see Olive expanding beyond just personal injury—interpreting unstructured medical data is critical for insurers to defend malpractice claims, class action firms to assemble plaintiffs, claimants to appeal insurance denials, providers to improve outcomes, the Social Security Administration to process disability applications speedily—we could go on. We're on a mission to remove barriers to information transfer, and therefore make justice more accessible. Our ask 🙏 ---------- If you know any personal injury lawyers, send them over to [our website]( or have them [book a demo directly](

Simplex

simplex

https://simplex.sh

San Francisco, CA, USA

Simplex creates on-demand vision datasets rendered from 3D scenes to train AI models. We can create data for any scenario, saving companies millions of hours they’d otherwise spend collecting and labeling real data.

Synthetic datasets for vision models

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/simplex

https://yc-oss.github.io/api/batches/s24/simplex.json

Title: Simplex: Synthetic datasets for vision models | Y Combinator URL Source: Markdown Content: ### Synthetic datasets for vision models Simplex creates on-demand vision datasets rendered from 3D scenes to train AI models. We can create data for any scenario, saving companies millions of hours they’d otherwise spend collecting and labeling real data. Simplex Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Shreya Karpoor, Founder Shreya is the co-founder and CEO of Simplex. She holds a BS and MEng in Electrical Engineering and Computer Science from MIT. She previously built software at Tesla and Viam and researched locomotion and dexterous robotic manipulation at MIT. ### Marco Nocito, Founder Marco is the co-founder and CTO of Simplex. He holds a BS and MEng in Computer Science from MIT. He previously built machine learning models to generate synthetic data at Waymo and built data infrastructure tooling at Viam and Bloomberg. ### Company Launches [### Simplex: on-demand photorealistic vision datasets]( **TL:DR;** Simplex creates photorealistic vision datasets rendered from 3D scenes for AI model training. Submit a request [on our website]( to receive high-quality data and labels. **Data request for the above sample:** _“Generate images and labels of a home kitchen with household objects on a center table. I need a variety of household objects in a variety of lighting conditions. Our desired labels are semantic segmentation and depth maps.”_ Hi everyone, we’re [**Shreya**]( and [**Marco**]( two MIT grads building Simplex. Collecting vision data for model training is time-consuming, costly, and often unsafe. Shreya spent over 200 hours physically operating a robot to collect image training data during her research at MIT. Marco worked on machine learning for synthetic data at Waymo to solve this exact problem. We realized data scarcity wasn’t just an issue in robotics – it affects any company training vision models. When fine-tuning foundation models or building a new dataset from scratch, teams must curate existing data or label and collect data themselves. We resolve the data scarcity problem by generating photorealistic ground truth labeled datasets for **any scenario**. We can generate **millions of varied images** **from 3D scenes** using our physics engine pipeline. Here’s how you’d use Simplex: 1. Fill out our data request form [here]( – it takes less than a minute. 2. Give us feedback on a few sample image/label pairs that we generate. Repeat if necessary. 3. Once you’re satisfied, download your complete dataset. We support semantic segmentation, captions, simulated LiDAR, depth maps, and bounding boxes. You can generate large volumes of randomized scenes or provide a CAD/phone scan model for more specific scenes. **Our Ask** ----------- * If you or someone you know needs vision data, fill out our 30-second data request [form.]( We’re taking a limited number of early customers. * If you have a more complicated request or would otherwise like to contact us, email [shreya@simplex.sh]( **The Team** ------------ [**Shreya**]( Computer science (BS and MEng) at MIT, software engineer at Tesla and Viam. Built simulation pipelines for locomotion and dexterous manipulation research at MIT.  [**Marco**]( Computer science (BS and MEng) at MIT, software engineer at Waymo, Bloomberg, and Viam. Built machine learning models to generate synthetic data at Waymo. #### YC Sign Photo

expand.ai

expand-ai

https://expand.ai/

San Francisco, CA, USA

expand.ai instantly turns any website into a type-safe API you can rely on. You can either request data from any website instantly or let expand.ai build up datasets for you. We take care of the hard parts like dealing with bot protection, scaling browser infrastructure and making sure that we only extract verified, correct information.

Turn any website into an API.

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/expand-ai

https://yc-oss.github.io/api/batches/s24/expand-ai.json

Title: expand.ai: Turn any website into an API. | Y Combinator URL Source: Markdown Content: ### Turn any website into an API. expand.ai instantly turns any website into a type-safe API you can rely on. You can either request data from any website instantly or let expand.ai build up datasets for you. We take care of the hard parts like dealing with bot protection, scaling browser infrastructure and making sure that we only extract verified, correct information. expand.ai Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Tim Suchanek, Founder Having been the first engineer at Prisma and founder of Stellate, I'm passionate about databases, schemas and APIs. Now at expand.ai, we're turning the web into a type-safe API. #### YC Sign Photo ### Hear from the founders #### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?) Tim has been working on developer tools for the last 8 years, being founding engineer at [Prisma]( and then founding [Stellate]( building AI apps, he found that oftentimes getting the right data was the blocker to get started with the project.That’s why he’s building [expand.ai]( - to enable anyone to use the web as a data source to power their AI apps.

Manaflow

manaflow

https://manaflow.ai

San Francisco, CA, USA

Manaflow is a simple way to automate repetitive office work in tables. With one click, you can execute millions of tasks involving data retrieval, gluing APIs, and taking actions side-by-side with your office work co-pilot.

Automate repetitive office work in tables with AI

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/manaflow

https://yc-oss.github.io/api/batches/s24/manaflow.json

Title: Manaflow: AI Workflow Builder for Businesses | Y Combinator URL Source: Markdown Content: Manaflow: AI Workflow Builder for Businesses | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( Manaflow ======== AI Workflow Builder for Businesses [S24]( Active [developer-tools]( Francisco]( * * * [Company]( [Jobs](  [ * * * ### AI Workflow Builder for Businesses Manaflow automates repetitive internal workflows involving data, APIs, and actions. Manaflow provides the infrastructure for businesses to build useful AI agents that can schedule recurring tasks, loop in human approval, and call custom tools. Instead of operations teams manually using internal tools, Manaflow agents listen to English instructions and operate tools in the background, interfacing directly with sources of truth, applications, and databases. Manaflow Founded:2024 Team Size:3 Location:San Francisco Group Partner:[Dalton Caldwell](  []( "LinkedIn profile") []( "Twitter account") ### Active Founders ### Austin Wang, Founder Co-founder & CEO of Manaflow / previously Google, NASA JPL, & Chess.com / Yale Physics / featured on Business Insider & The Economist Austin Wang [Manaflow](  []( "Twitter account") []( "LinkedIn profile") ### Lawrence Chen, Founder Co-founder of Manaflow / prev. Minion AI / Berkeley '24 Lawrence Chen [Manaflow](  []( "Twitter account") []( "LinkedIn profile") ### Wesley Tjangnaka, Founder Co-founder of Manaflow / Stanford CS Wesley Tjangnaka [Manaflow](  []( "Twitter account") []( "LinkedIn profile") ### Company Launches [### Manaflow - Build and manage your dream AI operations team]( ### **🛎️ TL;DR** * [**Manaflow**]( empowers **operation managers** to automate workflows involving data analysis, API calls, and business actions. * You can **command Manaflow agents in English** to execute recurring tasks and manage them on a spreadsheet interface. * Think of us as an **AI-first Zapier alternative** but with natural language and spreadsheets. * **Frustrated with repetitive manual tasks** in your business? We’ll automate them all for you. [**Let’s chat**]( ### **🗂️ The Problem: Too much Excel, too much manual stuff, too much repetition** Are you tired of **juggling countless Excel files and manual workflows for your business**? Do these workflows prevent your business from scaling up? After **conducting over 250 calls**, we've discovered a recurring problem: **small-to-mid-sized businesses (SMBs)** rely heavily on folders of Excel files and third-party apps to **manually execute their day-to-day operations**, which is **time-consuming, error-prone, and a huge bottleneck to scaling**. For instance, in freight forwarders, operations include managing client communications, inventory oversight, and coordinating delivery schedules, most of which are done manually. These **manual processes** not only **decelerate business growth** but also **heighten the risk of mistakes**. Today’s operation managers are blocked by a lack of **technical knowledge,** **customization,** **and** **simplicity** in current workflow automation builders. ### **💡 Introducing MANAFLOW: Automate operations workflows with AI** We are building **Manaflow** specifically for **underdog SMBs to scale** like their tech-enabled, big corporation counterparts, transforming manual spreadsheet and software tasks into **automated end-to-end workflows**. The ideal way to execute workflows is not for a human to manually operate Excel sheets or interface with different software apps but for a human to **merely click a button**. **AI can own end-to-end technical workflows** and convert them into features, while **humans can oversee** them, update them as the business evolves, and tackle higher-level automations. Let’s see this in **action**. ### **📕 Building a Basic Workflow on Manaflow** We’ll begin by building a fun, basic workflow on Manaflow to **send payment reminders to clients** via email. [Manaflow Demo: Building Sending Payment Reminders Workflow]( Next, we’ll go into more specific examples of potential use cases for business customers. ### **📸 Manaflow Workflow #1: Watermark videos and send them to your clients via Gmail** One of our customers uses Manaflow to take in unpolished videos from Google Drive, process them, watermark them with their logo, and then email the final products to their clients — **all in one click of a button**. [Manaflow Demo: Watermarking Video Workflow]( This has **cut their** **20-hour weekly manual workflow down to 20 minutes**, and Manaflow has become a core part of their operations. ### **🛻 Manaflow Workflow #2: Find and email truckers for your shipment logistics** Another customer uses Manaflow to find and email local trucking companies based on the shipment origin and final destination. [Manaflow Demo: Finding Truckers for Logistics Workflow]( This has allowed them to gather rate quotations faster for their clients and has **reduced their manual operations by over 50%.** ### **🙌 One more thing: Collaborate with all stakeholders, including us, to build automations** There are countless workflow automations that you can build on Manaflow. We understand that people have many different ideas and love working in teams. So, we made **real-time collaboration** so all of you can build and automate workflows together on Manaflow. Partnering with us, you will also have **24/7 access to Manaflow’s engineering support staff.** ### 👥 **OUR TEAM** [**Austin Wang**]( Yale Physics, CS & Econ; Prev. SWE @ Google, NASA JPL, [Chess.com]( ML @ Datacy [**Lawrence Chen**]( Berkeley CS; Prev. Founding Eng @ Minion AI, Berkeley RISE Lab [**Wesley Tjangnaka**]( Stanford Math & CS; Prev. Stanford AI Research, ML @ Juniper Networks **🙏 Our Ask** **If you are or know any** **operation managers or businesses** **that run on spreadsheets**, **please let us know or schedule a time with us** [**here**]( Any intros or shoutouts would be super awesome and greatly appreciated. We’d really appreciate a like and subscribe on our [YouTube]( a follow on our [Twitter]( and [LinkedIn]( and some feedback on our [product]( Thank you! Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

Sepal AI

sepal-ai

https://www.sepalai.com

San Francisco, CA, USA

Most data requires domain knowledge that can be hard to source and curate, and publicly available benchmarks are contaminated or too general to be useful to actual product builders. Sepal AI is the data development platform that enables people to build useful datasets. We bring data generation tooling, synthetic data augmentation, rigorous quality control, and a network of over 20k PhD and industry experts into one platform so you can manage the production of high quality datasets.

The data development platform for LLM users and builders.

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/sepal-ai

https://yc-oss.github.io/api/batches/s24/sepal-ai.json

Title: Sepal AI: Building LLMs for Large Enterprises. | Y Combinator URL Source: Markdown Content: ### Building LLMs for Large Enterprises. Sepal AI builds Large Language Models for Enterprises through data development, finetuning, and inference. Our team comes from Turing, Vercel, McKinsey, and Bain. At Turing, we built the LLM training business and products to support over $120M revenue growth in 6 months for companies like Open AI, Google, and Anthropic. We learned that large, non-tech enterprises that we worked with, like PepsiCo, Bridgestone, and Volvo, don't have the data they need to train models to produce real value. Which means they’re not going to unlock the value from AI without a partner. We are targeting the 2400 largest non-software companies to build, continuously fine tune, and deploy their custom models. Sepal AI Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Robi Lin, Founder Co-Founder @ Sepal AI Built the enterprise workflow products and fulfillment strategy at Turing.com. Scaled Turing’s LLM trainer business line from 50 to 800+ onboarded developers in 5 months for foundational LLM and enterprise customers. Previously was at Bain & Co. ### Kat Hu, Founder Cofounder @ Sepal AI Built Turing’s Foundational LLM trainer business GTM. Ran orgs of 500+ AI trainers & built corresponding operations for scale. Previously was at McKinsey. ### Fedor Paretsky, Founder I'm the co-founder and CTO at Sepal AI. Previously, I built platforms and infrastructure to bill users at Vercel while it went through hyper growth ($20M -\> $100M ARR). Before that, I worked on FP&A software at Mosaic and on platforms and infra at Newfront Insurance. ### Company Launches [### 🌱 Sepal AI - Confidently deploy your AI models]( **Tl;dr:** Sepal provides frontier data and tooling for advancing responsible AI development. --------------------------------------------------------------------------------------------- **\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_** ------------------------------------------------------------------------------------------------------------------------ [Sepal AI]( is on a mission to advance human knowledge and capabilities with the responsible development of artificial intelligence. **🧐 Responsibly advance human knowledge with AI? What does that mean?** ------------------------------------------------------------------------ We believe in a world where AI advances scientific research and empowers economic growth. To achieve that future, AI product & model builders need: 1. **Golden Datasets and Frontier Benchmarking:** To iteratively measure model performance on specific use cases. 2. **Training Data:** To improve model capabilities using fine-tuning and RLHF. 3. **Safety / Red-teaming:** To measure and forecast the safety of LLMs before putting them out in the wild. **\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_** ------------------------------------------------------------------------------------------------------------------------ ⚠️ **Okay, well why does it matter?** ------------------------------------- Frontier data for AI development is vital for safe deployment & scaling. However, developing this data is difficult. Most frontier data requires domain knowledge that can be hard to source and curate (e.g., finance, medical, physics, biology, etc.). Publicly available benchmarks (e.g., MMLU, GPQA, MATH, etc.) are contaminated and too general to be useful to actual product & model builders. **\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_** ------------------------------------------------------------------------------------------------------------------------ **🌱 How do we do this?** ------------------------- We’ve built Sepal AI - the data development platform that enables you to curate useful datasets. **The Platform:** We bring data generation tooling, human experts, synthetic data augmentation, and rigorous quality control into one platform so you can manage the production of high-quality datasets. **Our Expert Network:** We’ve built a network of 20k+ experts across STEM and professional services (think academic PhDs, business analysts, medical professionals, marketing and finance consultants) to support campaign design & data development. Sample engagements we’ve run: * **🧬 Cell and Molecular Biology Benchmark:** An original benchmark to evaluate complex reasoning across models. Produced by a team of PhD biologists from top institutions in the US. * **💼 Finance Q&A + SQL Eval:** A Golden Dataset to test the ability of an AI agent to query a database and produce human-expert-level answers to complex finance questions. * **📏 Uplift Trials & Human Baselining:** End to end support for conducting secure in-person evaluations on model performance. * _…. \[insert your custom use case next?\]_ **\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_** ------------------------------------------------------------------------------------------------------------------------ **🙏 Asks:** ------------ 1. If you are building an AI application and need to measure or improve your model, or 2. If you are a researcher at an AI lab building or evaluating models for new capabilities / risk areas, or 3. If you’re passionate about the development of AI, AI safety, or evals in general… Let’s [chat]( **\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_** ------------------------------------------------------------------------------------------------------------------------ **👪 Our team:** ---------------- Meet [Kat]( (on the left), [Robi]( (in the middle), [Fedor]( (on the right)! Robi and Kat previously built the technical LLM training business for Turing. Kat on the go-to-market & operations side. Robi on the product & fulfillment side. Fedor is a long-time close friend - he was an early engineer at Vercel & Newfront where he built out foundational infrastructure. Say hi: [founders@sepalai.com](mailto:founders@sepalai.com).

RetroFix AI

retrofix-ai

https://www.retrofix.ai/

San Francisco, CA, USA

RetroFix is a web platform that allows contractors to automatically apply for tax incentives and sustainability credits. Currently, contractors rarely apply for credits because discovering incentives, checking eligibility, and applying are all done manually via emails and phone calls with local utilities and/or government offices. RetroFix consolidates information on government incentives and allows building managers/contractors to apply in minutes, saving hundreds of thousands of dollars per building.

Turbo Tax for Building Rebates

Industrials

Industrials -> Climate

S24

Active

Early

https://www.ycombinator.com/companies/retrofix-ai

https://yc-oss.github.io/api/batches/s24/retrofix-ai.json

Title: RetroFix AI: Turbo Tax for Building Rebates | Y Combinator URL Source: Markdown Content: ### Turbo Tax for Building Rebates RetroFix is a web platform that allows contractors to automatically apply for tax incentives and sustainability credits. Currently, contractors rarely apply for credits because discovering incentives, checking eligibility, and applying are all done manually via emails and phone calls with local utilities and/or government offices. RetroFix consolidates information on government incentives and allows building managers/contractors to apply in minutes, saving hundreds of thousands of dollars per building. RetroFix AI Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Isaac Toscano, Founder Co-Founder/CEO at RetroFix AI. Before Retrofix I studied Materials Engineering at MIT, made financial models for billion dollar companies, did solar cell research at MIT's Nano lab and spend the weekends drilling Muay Thai. ### Daniel Portela, Co-Founder, CTO Co-Founder, CTO @ RetroFix AI | MIT CS | 🇵🇷 ### Company Launches [### 🏢 RetroFix AI - Turbo Tax for building rebates]( **tl;dr:** Building operations are responsible for around **1/4 of global energy CO2e** emissions. We want to make it extremely easy for every building in the world to decarbonize and decrease this number. Currently, we're working on making it extremely easy for buildings to secure government subsidies to become more energy efficient, starting with New York. [ Hi everyone, we’re [Isaac]( and [Daniel]( 👋 We met two years ago while studying at MIT, and now we are solving the problem of building decarbonization at [RetroFix AI]( **The Problem** 🌍 ------------------ Building operations are the 4th largest global contributor to carbon emissions: * **Globally**, they are responsible for around **26%** of all energy and process-related CO2e emissions * **In the US**, that number is approximately **29%** * **In dense cities** like New York, DC, Boston, and Philadelphia, they account for over **2/3** of all GHG emissions **Our Mission** 🚀 ------------------ We want to make it dead simple for every building in the world to decarbonize. We are committed to accelerating the adoption of clean energy technologies in buildings all around the world. We start by solving the largest barrier to decarbonization: money. Currently, we're working on making it extremely easy for buildings to secure government subsidies to become more energy efficient, starting with New York. 🏢 **Why Start with New York?** 🏙️ -------------------------------- With the passing of NYC’s Local Law 97, which penalizes building owners for exceeding emissions thresholds, around 12% of all buildings in NYC are starting to get fined this year for non-compliance. In 2024 alone, $20M in fines are estimated for these building owners. If no action is taken, the fines are expected to increase to over $85M per year by 2030, with over 70% of buildings being non-compliant. 💸 These fines will continue to rise as emissions thresholds become more stringent over time. Consequently, investments to improve critical building infrastructure have grown substantially, along with the need for subsidies. Consolidated Edison (the largest utility in New York) alone has deployed over $2B in subsidies over the last 4 years! 💡🏢 Contractors in NYC often spend hours researching the latest requirements and regulations to submit incentive applications, which are often not done correctly. As a result, a contractor may promise a certain amount of incentives to a customer but potentially deliver a completely different amount. This volatility in subsidy money is problematic for contractors who focus on delivering the best pricing and service to their clients. Because subsidy programs are often tied to government entities, contractors and building owners are interested in understanding how to “stack” incentives, but are deterred by the required reading to understand how to do so. 📚❗️ **The Solution ✅** ------------------ We start tackling the money problem by streamlining subsidy applications for energy-efficient equipment for buildings. Contractors no longer need to spend hours emailing or calling incentive programs, wondering when they'll hear back or if they did anything wrong! By using AI to understand regulatory constraints, we accurately identify the best incentives and provide a comprehensive list of required documentation. 📝 More time and money back in our contractors' pockets! We constantly update our software to ensure the most up-to-date information, so users remain worry-free. 😌 Contractors can rest assured they are submitting the right paperwork to maximize their clients’ incentives! Our goal is to accelerate the energy transition while saving owners and contractors hundreds of thousands of dollars through low-cost sustainability improvements. 🌿 **The Ask 🤲** -------------- We’re actively looking to onboard more building owners, building management companies, and HVAC professionals/engineers based in NYC! If you’re interested or know anyone we should connect with, please send us a message at [founders@retrofix.ai](mailto:founders@retrofix.ai)! 📩 **The Team 🗣️** ----------------

Evolvere BioSciences

evolvere-biosciences

https://www.evolverebiosciences.com/

Oxford, England, United Kingdom

🦠🤖 We use our computational models to make next-generation antibiotics that outcompete bacterial evolution and precisely target pathogenic bacteria, without harming good microbes or human cells. ☠️ Current antibiotics stop working because bacteria evolve resistance to them. This makes drug-resistant bacteria a looming global health crisis - already killing more people than malaria and AIDS and it is getting exponentially worse 📈. 🧬 Our approach leverages co-evolutionary protein-protein interaction datasets combined with AI to forecast bacterial mutations and create ‘future-proof’ antibiotics, addressing antibiotic resistance before it develops. This changes the game for how frequently society will need to make new antibiotics and how long our new antibiotics will be able to treat patients 👩‍⚕️. We are a team of biochemists and evolutionary biologists who met at the University of Oxford.

Making Next-Generation Antibiotics that Outsmart Bacterial Evolution

Healthcare

Healthcare -> Therapeutics

S24

Active

Early

https://www.ycombinator.com/companies/evolvere-biosciences

https://yc-oss.github.io/api/batches/s24/evolvere-biosciences.json

Title: Evolvere BioSciences: Making Next-Generation Antibiotics that Outpace Bacterial Evolution | Y Combinator URL Source: Markdown Content: ### Making Next-Generation Antibiotics that Outpace Bacterial Evolution 🦠🤖 We use our computational models to make next-generation antibiotics that outcompete bacterial evolution and precisely target pathogenic bacteria, without harming good microbes or human cells. ☠️ Current antibiotics stop working because bacteria evolve resistance to them. This makes drug-resistant bacteria a looming global health crisis - already killing more people than malaria and AIDS and it is getting exponentially worse 📈. 🧬 Our approach leverages co-evolutionary protein-protein interaction datasets combined with AI to forecast bacterial mutations and create ‘future-proof’ antibiotics, addressing antibiotic resistance before it develops. This changes the game for how frequently society will need to make new antibiotics and how long our new antibiotics will be able to treat patients 👩‍⚕️. We are a team of biochemists and evolutionary biologists who met at the University of Oxford. Evolvere BioSciences Founded:2021 Team Size:3 Location:Oxford, United Kingdom ### Active Founders ### Adam Winnifrith, Founder Evolvere (S24), CEO & Co-Founder, MBioChem Oxford, I work at the intersection of bioengineering, protein AI, and automation. E.S.B ### Piotr Jedryszek, Founder S24, Evolvere Biosciences, CTO and Co-founder, background in Bio and CompBio ### Weronika Slesak, Founder ex-Oxford biologist using evolution as an engineering tool. ### Company Launches [### 🦠💊 Evolvere Biosciences – Making next-generation antibiotics that outsmart bacterial evolution]( Hi everyone! – We’re [Piotr]( [Weronika]( and [Adam]( a team of biochemists and evolutionary biologists from the University of Oxford on a mission to make the next-generation of antibiotics. Current antibiotics stop working because bacteria evolve resistance to them. Our approach leverages co-evolutionary **protein-protein interaction datasets** combined with **AI** to forecast bacterial mutations and create **‘future-proof’ antibiotics**, addressing antibiotic resistance before it develops. This changes the game for how frequently we’ll need to make new antibiotics and how long our new antibiotics will be able to treat patients. Let's get into more detail: ❌ What’s the problem? --------------------- Antibiotic resistance is a looming global health crisis: * ☠ Already killing more people than Malaria and HIV * 📈 Getting exponentially worse because of bacterial resistance * 💸 $100 trillion economic burden undermining modern medicine ✅ We solve this by making future-proof antibiotics that: -------------------------------------------------------- 1. 🏃‍♂ Stay ahead of bacterial mutations to prevent resistance 2. 🎯 Precisely target harmful bacteria without disrupting beneficial microbes 3. 💵 Overcome the economic challenges of antibiotic development **Our Science** --------------- Traditional trial-and-error discovery cannot compete with bacteria's ability to mutate and acquire resistance genes. Our **evolutionary datasets** and **AI** will allow us to stay one step ahead of bacteria. We don’t react, we anticipate: You might wonder whether bacteria would eventually be able to mutate in other ways around our antibiotics. Well, yes, they could, but our approach forces all the escape mutations to be extremely costly. In fact, so costly that the bacteria wouldn’t survive. How? Our experiments are like running a battle simulation hundreds of times to find enemies’ weak points. This means that we can create detailed maps of the co-evolutionary landscapes of bacteria and our antibiotics so that we can ultimately engineer medicines with a low propensity for resistance emergence. [Watch how that works:]( We then engineer our antibiotics for **stability and safety** inside the human body using a suite of **protein AI models** (both diffusion and language model-based). This engineering means our antibiotics 1) only target pathogenic bacteria and not human cells or microbiomes and 2) have the potential to be given as a single dose – reducing the amount of monitoring that doctors have to do on patients. This is in contrast to current antibiotics, which can have human cell toxicity, disrupt microbiomes, and have to be dosed every few hours. * * * 👩‍⚕️ Why doctors are excited ----------------------------- Our blueprints have the potential for: * Low drug-drug interactions * Low risk of _C. difficile_ infection * Low dosing regimes * Low risk of resistance emergence * Low side effect profile 📊 Evolvere Bio Factfile ------------------------ * 🧪 We have already synthesized molecules that specifically kill bacteria in **physiological conditions**. These molecules are specific to only their target bacteria. * 🧬 Our R&D generates valuable **data** on protein co-evolution. * 🤖 We build **AI models** to predict and prevent resistance that arises from **protein co-evolution**, with potential applications in other therapeutic areas. Team ---- * 🧑‍🔬 **Adam Winnifrith** - Oxford biochemist who developed new biochemical assays based on advanced statistical concepts and published work on the advancements in generative AI in protein design. * 🧑‍🔬 **Piotr Jedryszek** – Oxford computational biologist studying the evolution of bacteria using deep learning techniques. His past work included molecular dynamics simulations, nanopore engineering, and biofuels. * 👩‍🔬 **Weronika Ślesak** – evolutionary biologist who worked at renowned microbiology laboratories (at the University of Oxford and Institut Pasteur) on high-throughput experimental evolution, antibiotic resistance genes and evolutionary trade-offs. * 👨‍💼 **Oliver Waterhouse** - serial biotech entrepreneur who sold his previous Oxford-based company Base Genomics for $410 million. Our Asks -------- Are you as excited as we are about making future-proof antibiotics? * Upvote/share this post! * Reach out to us at [founders@evolverebiosciences.com](mailto:founders@evolverebiosciences.com)

Conductor Quantum

conductor-quantum

https://www.conductorquantum.com

San Francisco, CA, USA

Quantum computers will allow humanity to simulate nature at the quantum level, enabling the acceleration of drug discovery and the development of new materials. Currently, quantum engineers spend days, sometimes weeks, manually getting their silicon chips to operational conditions to realize two qubits. A qubit is the information-carrying unit of a quantum computer, analogous to a bit in a classical computer. We need billions of qubits to make a useful quantum computer. Therefore, automation software will be vital to realizing this goal. Conductor Quantum will develop AI software to remove the human from the loop, enable the scaling of silicon quantum technology and build a silicon-based quantum computer.

Quantum computers on silicon chips using AI.

Industrials

Industrials

S24

Active

Early

https://www.ycombinator.com/companies/conductor-quantum

https://yc-oss.github.io/api/batches/s24/conductor-quantum.json

Title: Conductor Quantum: Quantum computers on silicon chips using AI. | Y Combinator URL Source: Markdown Content: ### Quantum computers on silicon chips using AI. Quantum computers will allow humanity to understand the world at its most fundamental level, enabling the acceleration of drug discovery and the development of new materials. Currently, quantum engineers spend days, sometimes weeks, manually getting their silicon chips to operational conditions to realize two qubits. A qubit is the information-carrying unit of a quantum computer, analogous to a bit in a classical computer. We need billions of qubits to make a useful quantum computer. Therefore, automation software will be vital to realizing this goal. Conductor Quantum will develop AI software to remove the human from the loop, enable the scaling of silicon quantum technology and build a silicon-based quantum computer. Conductor Quantum Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Brandon Severin, Founder Co-founder of Conductor Quantum, where we build quantum computers on silicon chips using AI. During my PhD at Oxford, I worked with 4 institutions across the globe (IST Austria, Basel, UNSW, Diraq), developing algorithms for semiconductor quantum device control and published 4 papers on the topic including one in Nature. ### Joel Pendleton, Founder Co-founder of Conductor Quantum, building quantum computers on silicon chips with AI. I’ve worked at many deep tech startups and research labs, exploring various quantum computing technologies — from carbon nanotubes to superconducting transmon qubits. I left my PhD at Oxford to start Conductor Quantum. ### Company Launches [### Conductor Quantum - Quantum computers on silicon chips using AI]( **Tl;dr:** * [Conductor Quantum]( is using **AI software** to **create qubits** in **semiconductor chips** to **build quantum computers** at scale. * The two founders met during their **PhDs at Oxford**. They have experience at 5 quantum companies and institutions, plus 4 publications between them. * Conductor Quantum is launching **the first publicly available API** to **classify quantum transport features in semiconductors**. **🧑‍🔬🧑‍💻The Team** ---------------------- Hi - We are Brandon and Joel! We are building Conductor Quantum. CEO, [Brandon]( – Brandon developed **_AI for Quantum Computing in Silicon_** during his **PhD** at **Oxford**. Over the past four years, Brandon has worked with four top quantum research institutions on **software for quantum device control** and has **four publications**, including one in **Nature**. CTO, [Joel]( – Joel has shipped software at **four deep tech companies** and has worked with a series of quantum devices ranging from **carbon nanotubes to superconducting circuits**. Joel studied **Physics at UCL** and **dropped out of his PhD** at **Oxford** to start Conductor Quantum. During Joel’s PhD at **Oxford**, he launched [Feynman.ai]( an AI science research assistant— with Brandon, which they bootstrapped to **300 signups within a month** of launch. **😯 The Problem** ------------------ * **Quantum computers** will **revolutionize drug discovery** and **material development** as we will, for the first time, be able to accurately **simulate nature at its most fundamental level**. * Leveraging the **trillion-dollar semiconductor** industry, silicon chips offer a **scalable architecture** for building quantum computers. → Currently, quantum engineers **spend days, sometimes weeks,** manually configuring silicon chips to **create a single quantum bit (qubit)**, analogous to a bit in a classical computer. **→ We need millions, if not billions, of qubits** to make a **useful quantum computer.** Automation software to create qubits at scale is vital to realize this goal. **✅ Our Solution - AI software to create qubits** ------------------------------------------------- * We are building **leading AI software** that creates qubits by **learning and understanding the principles of quantum transport** in semiconductor chips. * Our AI software will **replace the human** in the loop, **unlocking rapid qubit generation** and **fabrication feedback iteration cycles**. * Automatic qubit creation and control are the foundation of **the first quantum operating system** on **semiconductor chips**. [Our AI Playground]( **🤝 How You Can Help** ----------------------- * Sign up for our [**waitlist**]( (Announcements soon!) * Quantum engineers who want to get back to building and save themselves 100s of hours per qubit created - Email us at [founders@conductorquantum.com](mailto:founders@conductorquantum.com) * We’d love intros to: * Chip designers/verifiers/manufacturers * Anyone who wants to **bring chip manufacturing back to the USA** ### Hear from the founders #### What is your long-term vision? If you truly succeed, what will be different about the world? Everyone will have access to a quantum computer from their desk. ### Selected answers from Conductor Quantum's original YC application for the S24 Batch #### How long have each of you been working on this? How much of that has been full-time? Please explain. We’ve been working on the problem of quantum device control individually for the past 4 years as part of our degrees and work experience. Brandon (4 years full-time), Joel (2 years full-time, 2 years part-time).

Moonglow

moonglow

https://moonglow.ai

San Francisco, CA, USA

Moonglow connects local Jupyter notebooks to remote cloud compute. Machine learning researchers and data scientists use us to scale up their experiments without having to do DevOps. Previously, Leila was a software engineer at Jane Street. She led the build-out of its equities clearinghouse connectivity infrastructure and was the technical lead of its front-office SRE team. Trevor was part of Hazy Research Lab at Stanford, and published machine learning research at ACL and ICLR. With the explosive growth of deep learning, there are over 1 million ML researchers who do computationally intensive experiments every day. They use Jupyter notebooks to do so, but every time they want to try out a new idea, they need to get the notebooks running on cloud machines. This process, repeated hundreds of times a month, is time-consuming and error-prone. Moonglow reliably brings the time-to-experiment down from 5 minutes to 20 seconds. Just as Vercel and Replit abstracted away the lower levels of the computing stack for web developers and programmers, we do the same for ML researchers. https://moonglow.ai

Connecting local Jupyter notebooks to remote cloud compute.

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/moonglow

https://yc-oss.github.io/api/batches/s24/moonglow.json

Title: Moonglow: Connecting local Jupyter notebooks to remote cloud compute. | Y Combinator URL Source: Markdown Content: ### Connecting local Jupyter notebooks to remote cloud compute. Moonglow connects local Jupyter notebooks to remote cloud compute. Machine learning researchers and data scientists use us to scale up their experiments without having to do DevOps. Previously, Leila was a software engineer at Jane Street. She led the build-out of its equities clearinghouse connectivity infrastructure and was the technical lead of its front-office SRE team. Trevor was part of Hazy Research Lab at Stanford, and published machine learning research at ACL and ICLR. With the explosive growth of deep learning, there are over 1 million ML researchers who do computationally intensive experiments every day. They use Jupyter notebooks to do so, but every time they want to try out a new idea, they need to get the notebooks running on cloud machines. This process, repeated hundreds of times a month, is time-consuming and error-prone. Moonglow reliably brings the time-to-experiment down from 5 minutes to 20 seconds. Just as Vercel and Replit abstracted away the lower levels of the computing stack for web developers and programmers, we do the same for ML researchers. Moonglow Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Leila Clark, Co-Founder I'm currently building Moonglow, which connects Jupyter notebooks to cloud compute. Before this, I was a software engineer at Jane Street, where I led the build-out of its equities clearinghouse connectivity infrastructure and was the technical lead of its front-office SRE team. I graduated from Princeton with highest honors in Computer Science. ### Trevor Chow, Co-Founder Trevor is the co-founder of Moonglow. Previously, he graduated with a BS in Mathematics from Stanford, where he was part of Hazy Research Lab and published machine learning research at ACL and ICLR. He also traded index options and optimized low latency execution strategy at Optiver. ### Company Launches [### Moonglow - Colab on your cloud]( Hey everyone, we’re Trevor and Leila from [Moonglow]( ❌ Problem: moving experiments to cloud GPUs sucks ------------------------------------------------- When you’re doing machine learning research, it’s important to try out new ideas quickly. Jupyter notebooks make that easy. But what happens when your local computer isn’t enough? Your workflow probably looks like this: 1. Go to your cluster or cloud provider 2. Pick the right configs and spin up a node 3. SSH into the node 4. Install all the required packages 5. Pull your code from GitHub All of this is before you’ve even run a single cell in your notebook! And if you want to share your work or come back to it later, either you need to keep your GPU running (expensive) or go through this entire process again (slow). 🎉 Solution: Bring your own compute to Jupyter ---------------------------------------------- Moonglow connects your local Jupyter notebooks to your cloud compute provider. With a click of a button, you can switch runtimes and scale up your experiments to the GPUs you need. We handle all of the messy DevOps under the hood, and since your notebook lives in your local IDE, you can easily come back to it and get it running in seconds! We currently support connecting notebooks in VS Code / Cursor to Runpod instances, and we’re expanding this to other providers soon e.g. AWS, GCP, Azure, Lambda Labs etc. 👀 Team ------- [Trevor]( used to do ML research at Stanford, while [Leila]( was a software engineer working on high-performance infrastructure at Jane Street. We started Moonglow because we’ve seen how janky and unintuitive the current tooling is for ML research, and how that is bottlenecking the pace at which researchers can validate their results at scale. 🙏 Asks ------- * [**Try out**]( Moonglow or [book a time]( to get set up. * Let us know which **cloud providers** we should support next! * Connect us to **ML researchers** you know. We’re excited to hear from you, either at [trevor@moonglow.ai](mailto:trevor@moonglow.ai) or on Linkedin ([Trevor]( [Leila](

Hamming AI

hamming-ai

https://hamming.ai/

San Francisco, CA, USA

Humans make billions of calls/day. We think a majority of these will be handled by AI built by thousands of companies tackling every single vertical. Making these AI voice agents reliable is hard. A small change in prompts, function call definitions, or model providers can cause large changes in LLM outputs. Hamming automates testing for AI voice agents. Our voice agents call your voice agent. An AI drive-through startup uses Hamming to simulate thousands of simultaneous phone calls to achieve 99.99% agent order accuracy. We have a proven track record of helping enterprises win with AI. Sumanyu (CEO) previously helped Citizen (safety app) grow its users by 4X and grew an AI-powered sales program to 100s of millions in revenue/year at Tesla. Marius (CTO) previously ran data infrastructure @ Anduril and was a founding engineer @ Spell (MLOps startup acquired by Reddit).

Automated testing for AI voice agents

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/hamming-ai

https://yc-oss.github.io/api/batches/s24/hamming-ai.json

Title: Hamming AI: Automated testing for AI voice agents | Y Combinator URL Source: Markdown Content: Hamming AI: Automated testing for AI voice agents | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( AI Hamming AI ========== Automated testing for AI voice agents [S24]( Active [developer-tools]( Francisco]( * * * [Company]( [Jobs](  [ * * * ### Automated testing for AI voice agents Humans make billions of calls/day. We think a majority of these will be handled by AI built by thousands of companies tackling every single vertical. Making these AI voice agents reliable is hard. A small change in prompts, function call definitions, or model providers can cause large changes in LLM outputs. Hamming automates testing for AI voice agents. Our voice agents call your voice agent. An AI drive-through startup uses Hamming to simulate thousands of simultaneous phone calls to achieve 99.99% agent order accuracy. We have a proven track record of helping enterprises win with AI. Sumanyu (CEO) previously helped Citizen (safety app) grow its users by 4X and grew an AI-powered sales program to 100s of millions in revenue/year at Tesla. Marius (CTO) previously ran data infrastructure @ Anduril and was a founding engineer @ Spell (MLOps startup acquired by Reddit). Hamming AI Founded:2024 Team Size:2 Location:San Francisco Group Partner:[Gustaf Alstromer](  []( "LinkedIn profile") []( "Twitter account") []( "Crunchbase profile") []( "Github profile") ### Active Founders ### Sumanyu Sharma, Founder Sumanyu is the Co-Founder & CEO @ Hamming. Previously helped Citizen grow its MAU by 4X and helped bootstrap revenue from 0 to millions in ARR in under 6 months. Before that, grew an AI-powered sales program @ Tesla to 100s of millions in revenue/year as a Senior Staff Data Scientist. Published a first-author paper in AI during undergrad. BASc from UWaterloo w/ dean's list. Sumanyu Sharma [Hamming AI](  []( "Twitter account") []( "LinkedIn profile") ### Marius Buleandra, Co-Founder & CTO Marius is the Co-Founder & CTO @Hamming. Previously Eng Manager for Data Infrastructure @Anduril. Founding engineer @Spell (ML Observability & Infra startup acquired by Reddit). Worked on payments @Square and Windows Kernel Virtualization @Microsoft. Marius Buleandra [Hamming AI](  []( "Twitter account") []( "LinkedIn profile") ### Company Launches [### 🕵️ Hamming - Automated testing for voice agents]( 👋 [@Sumanyu Sharma]( and [@Marius Buleandra]( from [@Hamming AI]( **TLDR:** Are you testing your voice agents by hand? We're launching [Voice Simulations]( to automatically test your voice agents and flag quality issues in development and production. 🌟 [Click here to try our free Voice Simulations Demo]( 🌟 Problem: Making voice agents reliable feels like whack-a-mole ------------------------------------------------------------- Here's the workflow most teams follow: 1. **Call** your voice agent by hand and find bugs. Slow and ad-hoc. 2. **Tweak** your voice agents by adding new tools and changing the prompts or models to fix the bugs. 3. **Call again** to see if the changes worked. 4. **Detect** regressions when users complain of things breaking in production. 5. **Repeat** steps 1 to 4 until you get tired. **Calling your voice agent & finding bugs** is the slowest & most painful part of the feedback loop. This is what we automate. Our take: Character AI for voice testing ---------------------------------------- We create hundreds of characters that simulate how **real users interact with your voice agents** in real life. For every call, we measure whether our character successfully accomplishes the task (e.g., ordering a vegan burger, canceling next week’s appointment, etc.). Our approach is 100x faster, cheaper, and more thorough than manual testing. ### Flag errors & Tag calls in production You can log all call transcripts and traces within Hamming. We actively **tag your production calls** in real-time, and flag cases the team needs to double-click on. This helps engineering teams quickly prioritize cases they need to fix. **Example tags**: human detects that the bot is an AI, a follow-up call is needed, the user requested an urgent appointment, etc. ### Test new changes quickly **Simulation-driven development** Let’s imagine you’re building an agent called ‘YC Founder’; we can spin up 100s of VC agents who will try to distract you. You can edit the prompts or models and re-run the simulation to make sure you made progress. Want to see how you would handle a persistent investor? Try our ‘VC trying to distract founders’ free [demo here]( **Easily create new characters from call transcripts** When customers complain about a bad call, you can locate the call transcript and create a new character in one click. Make a change to your prompt, and then run the simulations to ensure you addressed the bad call. Meet the team ------------- [Sumanyu]( previously helped Citizen (safety app; backed by Founders Fund, Sequoia, 8VC) grow its users by 4X and grew an AI-powered sales program to $100s of millions in revenue/year at Tesla. [Marius]( previously ran data infrastructure @ Anduril, drove user growth at Citizen with Sumanyu and was a founding engineer @ Spell (MLOps startup acquired by Reddit). Summary ======= We previously launched [Prompt Optimizer]( and [AI Experimentation Tools]( to automate prompt engineering and make RAG pipelines more robust. In this launch, we show how you can test your voice agents quickly. Our offer ========= **Personalized characters + 100 free calls.** Struggling to make your voice agents reliable? We’ll create personalized characters and call + stress test your system ~100 times for free. Book time with us [here.]( Questions? Email us [here](mailto:sumanyu@hamming.ai) or chat with us [here]( ### Other Company Launches ### 🚀 Hamming - Make your RAG & AI agents reliable The only end-to-end AI development platform you need: prompt management, evals, observability [Read Launch ›]( ### 🚀 Hamming - Let AI optimize your prompts (free for 7 days) Automate 90% of manual prompt engineering using our self-improving prompt optimizer. [Read Launch ›]( Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

Blast

blast

https://blastsec.com

San Francisco, CA, USA

Blast helps large enterprises build safe and reliable LLM apps. We provide a platform to help enterprises rigorously evaluate and turn their generative AI prototypes into reliable apps that can be confidently deployed at scale.

Building safe and compliant LLM apps/agents for enterprises

B2B

B2B -> Security

S24

Active

Early

https://www.ycombinator.com/companies/blast

https://yc-oss.github.io/api/batches/s24/blast.json

Title: Blast: Building safe and compliant LLM apps/agents for enterprises | Y Combinator URL Source: Markdown Content: ### Building safe and compliant LLM apps/agents for enterprises Blast helps large enterprises build safe and reliable LLM apps. We provide a platform to help enterprises rigorously evaluate and turn their generative AI prototypes into reliable apps that can be confidently deployed at scale. Blast Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Arnav Joshi, Founder CEO at Blast. I was recently a BS/MS student in CS at Stanford. Previously, I worked on autonomous driving research at NVIDIA. I also interned at Amazon, where I built a computer vision tool. ### Daniel Zamoshchin, Founder CTO at Blast. I studied computer science with a focus in security at Stanford. I worked on security research with Prof. Dan Boneh and data privacy research with Prof. Matei Zaharia (Databricks). In high school, I built an app with 2M+ downloads. ### Company Launches [### 💥 Blast - Deploy AI safely and reliably at scale]( **TL;DR:** [Blast]( provides a platform to help enterprises turn their generative AI prototypes into reliable apps that can be confidently deployed at scale. — Hi everyone, we're Daniel and Arnav, and we're building Blast. **Problem: The mass adoption of LLMs across Fortune 500s is blocked by safety and reliability concerns.** Every large enterprise is trying to deploy their LLM-based apps/agent POCs at scale. Unfortunately, prohibited content, hallucinations, and other failures leave enterprises open to brand damage and legal liability. For example, Air Canada was forced to honor an out-of-policy bereavement discount that its chatbot had offered to a grieving passenger. Legacy enterprises in particular lack the talent and the tooling to solve these issues. **Solution:** We’re helping large enterprises build more reliable LLM apps. 1. **Evaluation platform:** Our red teaming tools enable developers to probe their end-to-end system with multi-turn conversations aimed at uncovering content/policy violations. 2. **Governance models:** We help enterprises detect, fix, and log failures in production. We started two months ago, and we are piloting with a Fortune 50 company. **The Team:** 👋 Hey, it’s [Daniel]( and [Arnav]( We met ten years ago in middle school and have been close friends ever since. We went to high schools in different states but reconnected at Stanford, where we were freshman year roommates. Daniel previously worked on AI security research at Stanford. Arnav previously worked on autonomous driving research at NVIDIA and in macro at Bridgewater. **Our Asks:** * We’d love intros to anyone working in security or AI governance at large enterprises. Email us at [founders@blastsec.com](mailto:founders@blastsec.com) * If you’re interested in adversarially testing your AI apps/agents or evaluating your guardrails, we’d love to talk! Please email us above!

Saturn

saturn

https://www.SaturnOS.com

London, England, United Kingdom

At Saturn, our mission is to make financial peace of mind more accessible by building the best operating system for wealth managers. Wealth and Asset Management is one of the world’s highest revenue-generating industries, yet it remains painfully inefficient. The sector relies heavily on disjointed legacy systems, manual human tasks, and a complex web of intermediaries, all of which increase costs. Saturn is an AI-powered operating system for wealth management built to automate investment research, streamline operations, and ensure compliance. Saturn creates the best version of truth, empowering investment advisors to work more efficiently, navigate complex regulatory landscapes, and deliver personalised, high-value services to their clients. Today, Saturn supports over 200 firms globally that manage more than £35bn in assets under management (AUM) and over 200,000 clients. As the industry grows, it faces massive operational challenges like bad tech, advisor retirements, regulatory pressure, an increased cost base, and transformational opportunities like great intergenerational wealth transfer and changing consumer needs. Saturn aims to be at the forefront of this transformation, driving the future of wealth management.

Backoffice and compliance automation for wealth managers

Fintech

Fintech

S24

Active

Early

https://www.ycombinator.com/companies/saturn

https://yc-oss.github.io/api/batches/s24/saturn.json

Title: Saturn: Compliance and back office workflows for Wealth Managers. | Y Combinator URL Source: Markdown Content: ### Compliance and back office workflows for Wealth Managers. At Saturn, our mission is to make financial peace of mind more accessible by building the best operating system for wealth managers. Wealth and Asset Management is one of the world’s highest revenue-generating industries, yet it remains painfully inefficient. The sector relies heavily on disjointed legacy systems, manual human tasks, and a complex web of intermediaries, all of which increase costs. Saturn is an AI-powered operating system for wealth management built to automate investment research, streamline operations, and ensure compliance. Saturn creates the best version of truth, empowering investment advisors to work more efficiently, navigate complex regulatory landscapes, and deliver personalised, high-value services to their clients. Today, Saturn supports over 200 firms globally that manage more than £35bn in assets under management (AUM) and over 200,000 clients. As the industry grows, it faces massive operational challenges like bad tech, advisor retirements, regulatory pressure, an increased cost base, and transformational opportunities like great intergenerational wealth transfer and changing consumer needs. Saturn aims to be at the forefront of this transformation, driving the future of wealth management. Saturn Founded:2023 Team Size:8 Location:London, United Kingdom ### Active Founders ### Amal Jolly, Founder/CEO Financial peace of mind enables every human to achieve more; we are on a mission to make it happen! Experienced in Product/GTM in Banking, Insurance, Wealth/Asset Management and Capital Markets technologies. ### Michael Ettlinger, Founder CTO & Co-Founder at Saturn AI Launched AI products used by 20M+ users across various industries. Background in AI research, focused on AI Agents since 2017. ### Rohit Vaish, Founder President & Co-founder at Saturn. Rohit has expertise in building investment portfolios for Wealth Management firms having spent over 5 years at BNY Mellon. Alongside that, he also led firm wide compliance initiatives across the UK fund management company to assess value for money and client suitability. After leaving financial services, Rohit led Product and Operations teams in a variety of startups before founding Saturn. ### Company Launches [### 🪐 Saturn: Backoffice and Compliance automation for Wealth Managers]( **tldr:** [Saturn]( automates investment research, compliance, and back-office workflows for wealth managers, significantly reducing operational costs and freeing up time to focus on client engagement and growth. — * * * * * * * * * Hey everyone, we're [Michael]( [Rohit]( and [Amal]( and we are on a mission to make wealth building more accessible for everyone by making wealth managers more efficient and scalable. 🧨 The Problem: Servicing a client with compliance and back-office tasks is a time drain ------------------------------------------------------------------------ Wealth managers spend an inordinate amount of time and resources on manual compliance and administrative tasks. This inefficiency leads to higher operational costs and limits their ability to serve more clients effectively. Take our client, Jason, as an example. Jason runs a mid-sized advisory firm in Norwich, UK, with over 15,000 clients and spends over 15 hours per client per year on compliance paperwork and back-office management all for doing one check-in a year. These manual processes drain his time and increase operational costs. This time and money could be better spent on growing his client base and enhancing client services. 🎉 The Solution: Automated AI-powered wealth management operating system built for scale and personalisation ------------------------------------------------------------------------------------------- Saturn helps wealth managers like Jason automate their compliance and back-office tasks, allowing them to focus more on client engagement and growth. Our platform uses AI to streamline processes and ensure real-time compliance, including: * Personalised investment research * Faster client onboarding * Seamless Compliance reporting * Client growth & analytics **Using Saturn, wealth managers:** ✔️ Save over 50% of the time typically spent on compliance and admin tasks ✔️ Increase operational efficiency, allowing them to offer more services and serve more clients ✔️ Improve personalisation, retention and net revenue from their client 💎 Opportunity: Driving the Future of Wealth Management --------------------------------------- Wealth management firms, like Jason's, waste countless hours and resources on manual compliance and operations—a massive inefficiency across the industry. Saturn is uniquely positioned to eliminate this burden through complete AI powered backoffice automation. Imagine a world where wealth managers can seamlessly guide clients through their entire financial lifecycle, making this service accessible to many more people. This is the future Saturn aims to create. > Big opportunities like the wealth transfer, growing consumer needs amongst wider demographics requires a more digital and robust system to serve them. > > The current systems simply cannot scale to serve the need, they are plagued by operational challenges added by bad tech, increasing regulatory pressure, and cost base. > > This industry is in a dire need of a transformation > > **Saturn aims to be at the forefront of this transformation, driving the future of wealth management.** **✅ Progress so far** 1. Grown to serve 200 firms globally 2. Cashflow positive since month 2 in the market, live since Feb. 3. Awesome team of 8 people. 👋 **Ask: How you can help** 1. Connect us to wealth managers or financial advisors in your network. [Intro us.]( 2. Know any killer engineer or product visionaries with experience in Wealth Tech and Financial Services. [Intro us.](mailto:founders@heysaturn.com) ### Hear from the founders #### What is your long-term vision? If you truly succeed, what will be different about the world? Managing wealth and access to financial services will be a standard for all.

Ontra Mobility

ontra-mobility

https://www.ontramobility.com

New York, NY, USA; Remote

Ontra Mobility is founded by two former Googler engineers with PhDs in operations research. Ontra helps cities and other transit agencies increase ridership through data-driven planning and real-time optimization. The founders developed the software that powered MARTA Reach in Atlanta, GA and CAT SMART in Savannah, GA.

Platform for planning and operating multimodal transit systems

Government

Government

S24

Active

Early

https://www.ycombinator.com/companies/ontra-mobility

https://yc-oss.github.io/api/batches/s24/ontra-mobility.json

Title: Ontra Mobility: Platform for planning and operating multimodal transit systems | Y Combinator URL Source: Markdown Content: ### Platform for planning and operating multimodal transit systems Ontra Mobility is founded by two former Googler engineers with PhDs in operations research. Ontra helps cities and other transit agencies increase ridership through data-driven planning and real-time optimization. The founders developed the software that powered MARTA Reach in Atlanta, GA and CAT SMART in Savannah, GA. Ontra Mobility Founded:2023 Team Size:2 Location:New York ### Active Founders ### Anthony Trasatti, Founder Founder at Ontra Mobility ### Connor Riley, Founder Founder Ontra Mobility. Xoogler, PhD from @GeorgiaTechISyE. Formerly @UMIOE and @UConn ### Company Launches [### Ontra Mobility - Increasing ridership for transit agencies]( **tldr:** [Ontra]( helps cities and transit agencies increase ridership through data-driven planning and real-time optimization. **🚀 Introduction** ------------------- Hey everyone! We’re Anthony and Connor, aka the [Ontra Mobility]( team, and we’re revolutionizing how people move. **❗ The Problem** ----------------- Transit agencies in the U.S. are facing massive budget shortfalls (up to $3B). Agencies need to adapt their transit systems more quickly to meet the demands of our evolving cities. Work from home led to a large drop in ridership, which is problematic for train and bus routes, which have high fixed costs. Cutting lines or reducing frequency further impacts ridership - transit agencies need a different solution. **💡 The Solution** ------------------- Ontra helps cities and other transit agencies increase ridership through data-driven planning and real-time optimization. Our platform optimizes cost and rider experience by designing high-frequency bus routes and ridesharing zones, where our algorithms adapt routes to demand in real time. **⚙️ How It Works** ------------------- Ontra analyzes information about where people live, how they've traveled in the past, and the existing transit system to figure out the best way to redesign the transit network. Once the improvements are made, Ontra Mobility plans rider journeys in real-time with the best combination of transit options available, whether it’s a train, bus, bike, or agency-operated on-demand. Our system can handle thousands of ridesharing requests per minute – efficiently assigning riders to optimal routes. [ **🚌 What’s New** ----------------- * Our transit network design application generates bus routes and micro-transit zones * Seamless multimodal journeys – our algorithm synchronizes transfers between on-demand and fixed-route **🎓 The Team** --------------- Anthony and Connor are both former Google engineers with PhDs in [operations]( [research]( Prior to joining YC, they worked on [MARTA Reach]( in Atlanta, GA, and [CAT Smart]( in Savannah, GA. **🙏 Ask: How you can help** ---------------------------- * Share this post and spread the word! * Connect us to private- or public- **transit agency employees** or **board members**, **politicians,** and **transit advocates**. [founders@ontramobility.com](mailto:founders@ontramobility.com) Quick blurb to copy and paste: [Ontra Mobility]( is founded by two former Google engineers with PhDs in [operations]( [research]( Ontra helps cities and other transit agencies increase ridership through data-driven planning and real-time optimization. The founders developed the software that powered [MARTA Reach]( in Atlanta, GA and [CAT Smart]( in Savannah, GA. ### Hear from the founders #### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?) Connor and Anthony met at Georgia Tech where they graduated with PhDs in operations research with a focus on optimization for public transit systems. Their publications have been cited over 150 times, appearing in IJACI and Transportation Science. Together, they have over a decade of experience in optimization of transit systems. While at Georgia Tech, they developed and managed full-stack deployments of MARTA Reach ([ a public on-demand ride-sharing service in Atlanta, GA, and the SMART Transit pilot ([ in Savannah, GA. ### YC S24 Application Video

Hey Revia

hey-revia

https://heyrevia.ai

San Francisco, CA, USA

Hey Revia is a voice AI that handles complex phone calls for healthcare providers. Our software automates complex menus, reduces hold times, and handles tedious phone calls—verifying provider details, updating insurance info, and securing approvals. We offer Revia as web app, mobile app and API.

Voice AI to automate complex phone calls for healthcare providers

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/hey-revia

https://yc-oss.github.io/api/batches/s24/hey-revia.json

Title: Hey Revia: Voice AI to automate complex phone calls for healthcare providers | Y Combinator URL Source: Markdown Content: ### Voice AI to automate complex phone calls for healthcare providers Hey Revia is a voice AI that handles complex phone calls for healthcare providers. Our software automates complex menus, reduces hold times, and handles tedious phone calls—verifying provider details, updating insurance info, and securing approvals. We offer Revia as web app, mobile app and API. Hey Revia Founded:2024 Team Size:4 Location:San Francisco ### Active Founders ### Shaun Wei, CEO & Co-founder Building voice AI assistant for phone call. Ex-googler worked on Google Assistant. Previously worked on self-driving car in Pony.ai ### David (Wenbo) Zhu, Founder Building a voice AI assistant for phone call. Previously at Google, Brex. ### Company Launches [### Hey Revia - AI call assistant for healthcare providers]( ❌ **The Problem** ----------------- Healthcare providers waste countless hours navigating insurance, pharmacies, and PBMs. Whether it’s credentialing, waiting for prior authorizations, or handling billing disputes, the process steals valuable time that could be spent on patient care. ✨ **Our Solution** ------------------ Imagine an assistant that never gets tired of being on hold. Revia does just that—an AI-powered call assistant tackling the most complex healthcare communications. With its natural language processing, Revia handles the toughest tasks: navigating IVRs, managing call scenarios, and getting things done. From coordinating with insurance for prior authorizations to following up with pharmacies, Revia simplifies the workflow, giving your team time to focus on what truly matters—patients. Revia doesn’t just save time—it transforms how you interact with the backend of healthcare. 🎤 **Here are some ways you can use Revia**: -------------------------------------------- [ **⭐ See Revia in action 👆** * Credentialing verification * Prior authorization follow-ups * Billing and payment disputes * Coordinating referrals * And many more 🔒 **Data Privacy and Security** -------------------------------- At Revia, we take data privacy seriously. Our AI agents adhere strictly to HIPAA compliance, providing full transparency and rigorous protection for your sensitive information. We’ve implemented robust security protocols to ensure the utmost privacy and integrity in every interaction. **🚀 Asks** ----------- * **Try Revia**: Schedule a demo at [heyrevia.ai]( you’re in health tech, a provider, or a payor, we’d love your feedback! * If you are interested in what we are building and want to collaborate, let’s hop on a call via [ 👉 **Follow Us** ---------------- * Follow us on [Web]( [Twitter/X]( [Linkedin]( or contact us at [founders@heyrevia.ai](mailto:founders@heyrevia.ai) Hey! [Shaun]( and [David]( here. We are both ex-googlers / AI engineers and dads. After hearing our daughters’ pediatric clinic spent hours on calls with insurance companies and pharmacies, we knew we needed a better solution. That’s why we are building Revia—to free healthcare providers from the stress of administrative calls and allow them to focus on what really matters: caring for patients like my daughter. P.S. Back in 2018, when Sundar Pichai demoed AI making a hairdresser appointment, we were behind the scenes at Google Assistant. Today, I’m bringing that same technology to healthcare—one call at a time. #### YC Sign Photo

BeeBettor

beebettor

https://beebettor.com

BeeBettor makes sports betting simple. Currently, sports bettors download more than 40 sports betting apps to get the full experience. At each one, they must go through a long KYC process. Then once their 40 accounts are active and funded, finding the best price is a painstaking process involving third-party tools to search available offers. BeeBettor aggregates all these accounts into one app and automatically gives sports bettors the best price.

Robinhood for sports betting

Consumer

Consumer -> Content

S24

Active

Early

https://www.ycombinator.com/companies/beebettor

https://yc-oss.github.io/api/batches/s24/beebettor.json

Title: BeeBettor: Robinhood for sports betting | Y Combinator URL Source: Markdown Content: ### Robinhood for sports betting BeeBettor makes sports betting simple. Currently, sports bettors download more than 40 sports betting apps to get the full experience. At each one, they must go through a long KYC process. Then once their 40 accounts are active and funded, finding the best price is a painstaking process involving third-party tools to search available offers. BeeBettor aggregates all these accounts into one app and automatically gives sports bettors the best price. BeeBettor Founded:2024 Team Size:2 Location: ### Active Founders ### Jordan Murphy, Founder Jordan is the founder and CEO of BeeBettor. He’s been studying and playing sports his whole life. Putting his math degree from University of Waterloo to good use, he developed sports betting strategies that got him banned from betting. He was then able to automate these strategies and turn them into the first version of BeeBettor. ### Matthew Wolfe, Founder Matthew is the founder and CTO of BeeBettor. He has experience working as a software engineer at Uber and Meta. Matthew has been betting on sports for years, using his skills as a software engineer to automate his strategies, which eventually evolved into BeeBettor. ### Company Launches [### BeeBettor: Robinhood for sports betting]( **TL;DR:** BeeBettor makes sports betting simple. Research and make your bets in one place without having to cycle through 40+ apps. ### **The Team 👨‍👨‍👦** [Jordan]( is a Math graduate from the University of Waterloo who put his degree to use by becoming a professional sports bettor before being banned from most recreational sportsbooks for winning too much. [Matthew]( is a Computer Science graduate from the University of Waterloo who saw how well Jordan was doing with his betting and worked with him to automate a lot of the process. BeeBettor v1 was born. We’ve been friends since the first grade and have lived together throughout university. ### **The Problem 🚩** Currently, sports bettors download more than 40 sports betting apps to get the full experience. At each one, they must go through a long KYC process. This can take months to complete. Then once their 40 accounts are active and funded, finding the best price is a painstaking process involving third-party tools to search available offers. ### **The Solution 💸** [BeeBettor]( aggregates all these accounts into one app and automatically gives sports bettors the best price. We’re currently in a closed beta with one sports betting company that allows users to place bets through our app. Our GTM is a subscription power tool that allows users to research sports betting picks and shop around for the best price. We’ve reached **$10.4k MRR** and grown a user base that enables us to learn and iterate fast. This product is building the foundation of our vision regarding both the technology and the users. ### **Why now? 🚨** Recent changes in the sports betting industry have made it easier to take a sportsbook live in most states. Coupled with the fact that the top two operators handle over 80% of the legally wagered dollars in the United States, it means there is a _very_ long tail of sports betting companies struggling to get a share of the market. They are desperate for users and want to work with us to solve that. ### **Our Ask 🙏** * If you know someone who works at a sports betting company, we’d love to talk to them. Contact us via email ([**founders@beebettor.com**](mailto:founders@beebettor.com)) if you know someone!

Merse

merse-2

https://merse.co

San Francisco, CA, USA

Visual stories like comics, but with voices and sound effects. Building a new medium to rival Youtube, TikTok, and Netflix.

The New Medium: Scroll Visual Stories with Audio Effects and Sounds.

Consumer

Consumer

S24

Active

Early

https://www.ycombinator.com/companies/merse-2

https://yc-oss.github.io/api/batches/s24/merse-2.json

Title: Merse: Visual stories like comics, but with immersive audio effects. | Y Combinator URL Source: Markdown Content: Merse: Visual stories like comics, but with immersive audio effects. | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( Merse ===== Visual stories like comics, but with immersive audio effects. [S24]( Active [generative-ai]( Francisco]( * * * [Company]( [Jobs]( [News](  [ * * * ### Visual stories like comics, but with immersive audio effects. Visual stories like comics, but with voices and sound effects. Building a new medium to rival Youtube, TikTok, and Netflix. ### Latest News [The Journal by Fondo | Merse launches: Netflix for Audio-Visual Comics]( Jul 16, 2024 Merse Founded:2024 Team Size:2 Location:San Francisco Group Partner:[Aaron Epstein](  []( "LinkedIn profile") []( "Twitter account") []( "Github profile") ### Active Founders ### Mark Rachapoom, Founder Co-Founder & CEO of Merse. Previously developed a top-ranking iOS app, reaching #3 on the App Store. Selected as one of 40 participants in the Vercel AI Accelerator program. Design engineer with a strong sense of design. \[markrachapoom.com\] Mark Rachapoom [Merse](  []( "Twitter account") []( "LinkedIn profile") ### Kumar Abhirup, Founder Helped lead Web Team at Airchat. Sold my first company Beam (Substack for Texting) at the age of 16. Helped my mom scale a newsletter from 0 to 300K subscribers. At Merse, we are working on changing the future of content consumption. Kumar Abhirup [Merse](  []( "Twitter account") []( "LinkedIn profile") ### Company Launches [### Merse: The Netflix for audio-visual comics]( **⏰ TLDR;** =========== **WE are the Netflix for Audio-Visual Comics,** with a wide range of premium entertaining content for comic readers. **YOU** can **HEAR THE CHARACTERS SPEAK** in 6 languages, with immersive soundtracks and crispy audio effects. **ARTISTS** can **EARN A LIVING** by creating, uploading, publishing, and monetizing comics. With a wide range of characters, voices and soundtracks to choose from. Artists can also generate audio effects and soundtracks at will using Merse AI. Our AI tooling handles text and voice translation of speech bubbles. **GET THE APP** @ [merse.co]( * * * * * * * * * **⚠️ The Problem** ================== **Creating comics is a labor-intensive process** that requires significant time and effort. Despite the popularity of comics, producing them often **takes hours of meticulous work** using tools like Adobe Illustrator, or requires plain drawings. This limits the number of creators who can participate and the volume of content available to readers. The comic reading experience has been the same for decades. On the other hand, **readers are looking for new and more immersive experiences.** While static images are the norm, there is a growing demand for interactive content that brings characters and stories to life with character voices and sounds. * * * * * * * * * **🫶 Our Solution — Audio-Visual Comics** ========================================= [** The Merse platform enables creators to generate high-quality, audio comics quickly and easily, and offers readers an immersive experience. You focus on crafting engaging stories; Merse handles all your tech, distribution, and monetization. * * * **📸 Features** =============== **• Generate comics using AI:** Our GenAI features create detailed comic panels from your scripts, creates compelling voices in multiple languages for each speech bubble, with AI generated sound effects, significantly reducing the time from concept to publication. **• Audio Effects + Soundtracks:** Be it the sound of gulping water, or cracking knuckles, it has it all. **• Read and Hear in 6 different languages:** 🇮🇳Hindi 🇫🇷French 🇨🇳Chinese 🇯🇵Japanese 🇰🇷Korean 🇺🇸English **• Monetization options:** Choose how to monetize your content – keep it free, or charge users per episode. * * * **🏪 The Market** ================= The biggest incumbent in this industry is Naver Webtoons. It’s the YouTube for static, hand-drawn comics. Over 120,000 artists draw and upload their episodes and get paid over $27M for their work, clocking in a revenue of over $1.4B a year and 170M monthly active readers. * * * **🇺🇸 The Founders** ===================== [**Mark Rachapoom**]( **CEO of Merse,** 21-year-old founder, an engineer at heart with a great sense of design, college dropout, and fellow at Vercel AI Accelerator. He created Diary Dingo, an iOS journaling app that hit the top 3 in the App Store's Lifestyle category within 24 hours of launch. [**Kumar Abhirup**]( **CTO of Merse,** 20-year-old founder, dropped out of high school in Nashik, India, and worked alongside Naval Ravikant as an **Engineer at Airchat**, **1x Exited founder** @ [itsbeam.com]( * * * * * * **🙏 Our Ask** ============== • **Connect us to creators and readers:** We’re looking to connect with comic artists, writers, and enthusiasts interested in innovative storytelling methods. Please reach us at [hey@merse.co](mailto:hey@merse.co), and we’ll follow up. • **Create on Merse:** Are you a passionate comic creator looking to transform your storytelling process? Start creating on our platform and own your storytelling journey! Share the comics you love on the Merse feed and on your socials, and help us gauge what content works best. • **We are looking to seed content:** CONTENT IS KING! It’s important we have a good catalog of content before future launches. If you want to help us with filling Merse up with exciting content, and have ideas, or want to work with us, contact [hey@merse.co](mailto:hey@merse.co) • **If you have experience going viral on TikTok / Reddit or are a good growth hacker and would love to help us**, contact us. Join us in helping artists story-tell with Merse. #### YC Sign Photo ### Selected answers from Merse's original YC application for the S24 Batch #### Describe what your company does in 50 characters or less. Immersive Comic Reader & AI Creator with Audio FX #### What is your company going to make? Please describe your product and what it does or will do. A fully immersive Comics reading and creation platform which uses Audio Effects. Creators can use our AI-native platform to generate characters, backdrops, and compelling audio speeches for each speech bubble. ### YC S24 Application Video Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

omnidock

omnidock

https://www.omnidock.com

Berlin, Berlin, Germany

Expanding to other geographies and marketplaces is a massive growth lever for brands and manufacturers, but it’s complex and resource-intensive. Omnidock makes it effortless for merchants to sell on multiple marketplaces by acting as their merchant of record. Brands simply plug into our operating system, which reads their catalog, assesses marketplace eligibility, and auto-launches their products through our pre-vetted marketplace accounts. We handle all transactions on their behalf, removing the challenges and complexities of multi-marketplace selling

Sell on all eCommerce marketplaces globally

B2B

B2B -> Operations

S24

Active

Early

https://www.ycombinator.com/companies/omnidock

https://yc-oss.github.io/api/batches/s24/omnidock.json

Title: omnidock: OS for global e-commerce expansion of brands & manufacturers | Y Combinator URL Source: Markdown Content: ### OS for global e-commerce expansion of brands & manufacturers Expanding to other geographies and marketplaces is a massive growth lever for brands and manufacturers, but it’s complex and resource-intensive. Omnidock makes it effortless for merchants to sell on multiple marketplaces by acting as their merchant of record. Brands simply plug into our operating system, which reads their catalog, assesses marketplace eligibility, and auto-launches their products through our pre-vetted marketplace accounts. We handle all transactions on their behalf, removing the challenges and complexities of multi-marketplace selling omnidock Founded:2024 Team Size:3 Location:Berlin, Germany ### Active Founders ### Shayan Zakerzadeh, Founder Co-Founder @ omnidock :) ### Christian Kohrs, Founder Co-founder @ omnidock :) ### Sebastian Rödling, Founder Co-Founder @ omnidock :) ### Company Launches [### omnidock: The OS for global e-commerce expansion]( **TL;DR:** Our AI-powered operating system enables brands and manufacturers to sell on all global e-commerce marketplaces. Using [omnidock]( they sell through our local entities and pre-vetted marketplace accounts, as we act as their merchant of record. This increases their revenue by at least 20% immediately after using omnidock. We’re live in the EU and already help more than 25 customers grow. 3 of them are enterprises. **Problem 🚨 & Opportunity 🌟** ------------------------------- Expanding to new geographies and marketplaces is a massive growth opportunity for brands and manufacturers, but it's complex and resource-intensive Global e-commerce marketplaces have varying requirements, are often gated, and demand multiple legal entities to operate. As a result, many merchants leave the potential untapped. The marketplace landscape is more fragmented than ever. Since 2020 (COVID), alternative marketplaces in the US and EU are outgrowing generalists like Amazon and now account for over 40% of marketplace GMV in the US and 51% in the EU. Additionally, manufacturers that work with us typically operate on production-focused ERPs like SAP. Integrating such ERPs into any marketplace is extremely expensive and takes months if not years. **Solution🚀** -------------- **Brands simply plug into our operating system, and we:** * Read & asses their catalog for marketplace eligibility [**✅**]( * Modify their content via AI to meet marketplace-specific requirements (e.g., matching taxonomies for them) [**✅**]( * Launch their catalog through our pre-vetted marketplace accounts & entities [**✅**]( * Provide them with pre-negotiated logistic rates, usually~30% cheaper than their own rates [**✅**]( * Give them access to unified reporting, KPIs, and forecasts to manage growth [**✅**]( We handle all transactions on their behalf, removing the challenges and complexities of multi-marketplace selling. **👬 Team:** ------------ We decided to start [**omnidock**]( as we were day 1 employees at a Berlin-based unicorn [Razor Group]( [Shayan]( and [Sebastian]( met in high school and have been friends for 12+ years. Most recently, [Christian]( was VP Warehousing & Logistics, Shayan was VP Expansion and Sebastian finalized his engineering master’s from TUD with focus on AI. We scaled alternative marketplace revenues at Razor from 0 to $30m in less than a year and know from firsthand experience how unsolved this is. **❤️ How you can help** If you know a brand or manufacturer of consumer goods that would like to expand globally, send us a message at [founders@omnidock.com](mailto:founders@soff.ai) 🙂 We are also hiring!

Promi

promi

https://www.usepromi.com/

San Francisco, CA, USA

Promi is a pricing and discount optimization platform. We help merchants by personalizing and dynamically setting discounts across products to maximize sales and profit. Ecommerce merchants and marketers typically use discounts to drive customer acquisition, boost sales during holidays, or liquidate inventory. But deciding on a discount to offer is typically guesswork. Who to send the discount to, how much to offer, and which products it applies to are, in the most advanced cases, determined manually by looking at past sales and seeing what worked well. In the majority of cases, it's what feels and sounds good. Promi leverages your store data to optimize discounts at a more granular level than possible manually. We dynamically determine the best value across each product, for different users, at different times in order to maximize sales and profit.

Optimizing ecommerce merchant pricing with dynamic, personalized…

B2B

B2B -> Retail

S24

Active

Early

https://www.ycombinator.com/companies/promi

https://yc-oss.github.io/api/batches/s24/promi.json

Title: Promi: Optimizing ecommerce pricing with dynamic, personalized discounts | Y Combinator URL Source: Markdown Content: ### Optimizing ecommerce pricing with dynamic, personalized discounts Promi is a pricing and discount optimization platform. We help merchants by personalizing and dynamically setting discounts across products to maximize sales and profit. Ecommerce merchants and marketers typically use discounts to drive customer acquisition, boost sales during holidays, or liquidate inventory. But deciding on a discount to offer is typically guesswork. Who to send the discount to, how much to offer, and which products it applies to are, in the most advanced cases, determined manually by looking at past sales and seeing what worked well. In the majority of cases, it's what feels and sounds good. Promi leverages your store data to optimize discounts at a more granular level than possible manually. We dynamically determine the best value across each product, for different users, at different times in order to maximize sales and profit. Promi Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Peter Moot, Founder Co-founder @ Promi, a pricing and discount optimization platform. Prior to Promi I led product for discounts at Uber. I have a degree in economics and computer science from Harvard. ### Jiaxin Lin, Founder Co-founder of Promi. Most of my career has been working on recommendation / personalization systems in the e-commerce space. Avid coder and lifelong learner. ### Company Launches [### Promi - AI powered discounts for ecommerce merchants]( **tl;dr:** [Promi]( helps ecommerce merchants send smarter discounts by leveraging AI to dynamically update discounts and optimize for clearing inventory, varying discount values across products for first order, holiday, etc. campaigns, and better communicating discounts across your website via price strikethroughs and other UI components. We are available on the [Shopify app store]( [ 👬 **Meet Our Team** [_Peter_]( The Discount Guru_ Peter is coming from Uber, where he was the product lead overseeing discounts across Eats and Rides. While there, he launched many of the features we are now building into Promi today. He has a degree in economics from Harvard and would love to talk with you about your pricing and discount strategy. [_Jiaxin_]( The AI mastermind_ Jiaxin was the tech lead and founding engineer at Uber’s knowledge graph platform, focusing on recommendations and personalization. Before Uber, Jiaxin worked in AI at Google’s Shopping Recommendations team. **❌ The Problem** Most retailers spend 5-10% of their gross merchandise value on discounts to acquire new customers, celebrate holidays, hit sales targets, clear inventory, etc. However, choosing the right discount often involves guesswork. More sophisticated merchants look at what worked well in the past, but they don’t have the time or means to granularly optimize their discounts across products and users, or dynamically update the offers based on order trends. Additionally, many retailers don’t communicate savings available via discount codes on their website until checkout, causing a drop in customer conversion. **💡 Our Solution** ------------------- Promi enhances discount performance by addressing key issues: * **Dynamic Updates**: AI-driven adjustments ensure efficient inventory clearance without over-discounting. Specify the volume, timeframe, and pricing guardrails, and Promi will continuously monitor and update discounts. * **Improved Communication**: Discounts are displayed site-wide using deep links for price changes and other UI components. * **Variable Discounts**: We vary discount values across products to take advantage of differences in profit margins and prices, all under a single code. Your email sign-up and member-only campaigns just got a lot more profitable These solutions improved Uber's discount efficiency by more than 40%. Stay tuned for upcoming features like personalized discounts, performance measurement dashboards, and experiment setups! **🙏 Ask: Check out Promi!** If you run a Shopify store or know someone who does, we'd love to chat. Email us at [peter@usepromi.com](mailto:peter@usepromi.com). See our website and app listing below: * [ * [ #### YC Sign Photo ### Hear from the founders #### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?) We both worked at Uber prior to Promi, where Peter led product for discounts across Uber Eats and Rides. Jiaxin worked on Uber’s core AI team. Peter had the idea for Promi after having seen how wasteful discounts were for the business, and how impactful certain features could be for making discounts more efficient and ROI positive.

Coval

coval

https://coval.dev

San Francisco, CA, USA

Coval automates AI agent testing, helping engineers launch dependable assistants across chat, voice, and other modalities. Our simulation and evaluation complement ad-hoc manual testing, preventing poor user experiences. Using our team's background in the autonomous vehicle industry, we focus on statistically validated reliability, applying proven techniques from self-driving tech to ensure quality.

Simulation & Evaluation for AI Agents

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/coval

https://yc-oss.github.io/api/batches/s24/coval.json

Title: Coval: Simulation & Evaluation for AI Agents | Y Combinator URL Source: Markdown Content: Coval: Simulation & Evaluation for AI Agents | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( Coval ===== Simulation & Evaluation for AI Agents [S24]( Active [artificial-intelligence]( Francisco]( * * * [Company]( [Jobs](  [ * * * ### Simulation & Evaluation for AI Agents Coval is a simulation & evaluation platform for AI agents, helping engineers launch dependable assistants across chat, voice, and other modalities. We simulate thousands of scenarios engineers don't have to manually test their agents. Our CI/CD evaluations automatically simulate and detect regressions. Coval Founded:2024 Team Size:10 Location:San Francisco Group Partner:[Harj Taggar](  []( "LinkedIn profile") []( "Twitter account") ### Active Founders ### Brooke Hopkins, Founder Building evaluation for AI agents, previously led eval infra at Waymo 🚙 Brooke Hopkins [Coval](  []( "Twitter account") []( "LinkedIn profile") ### Company Launches [### Coval - Simulation & Evaluation for AI Agents]( Teams are racing to market with AI agents, but slow manual testing processes are holding them back. Engineers currently spend hours manually evaluating and playing whack-a-mole just to discover that fixing one issue introduces another. At Coval, we build automated simulation and evaluation for AI agents inspired by the autonomous vehicle industry to boost test coverage, speed up development, and validate consistent performance. We have a waitlist, but YC companies go first! Grab some time here: [ **Our Story** ============= Hey! I’m [Brooke]( the founder of [Coval]( 👋 Before starting Coval, I led the evaluation job infrastructure team at [Waymo]( I coded the first versions of our dataset storage and other foundational simulation systems, and my team built all of the dev tools for launching and running evals. Through my conversations with hundreds of engineering teams at startups and enterprises, I've seen that AI agents—models that operate independently and handle complex tasks—are facing similar challenges to those in self-driving. In the early days, autonomous vehicle companies relied heavily on manual evaluation, testing the self-driving cars on racetracks and city streets (remember when autonomous cars still had safety drivers?). However, as startups scaled, a significant shift happened: we moved towards simulating every code change in a “virtual” environment, using the vast amounts of data we collected. The new approach dramatically improved vehicle behavior, leading to hundreds of autonomous cars zipping around the San Francisco streets today! This story mirrors what's happening today with AI agents across various industries. Teams are coming up with promising prototypes but often hit a wall when it comes to their reliability. As we build for the future, where AI agents execute much of our work, ranging from sending emails to prescribing medication, the risks posed by untested systems could severely throttle the progress. At Waymo, I developed tools that tested each code modification made by engineers, ensuring that every change improved the Waymo Driver's performance. I believe this methodical approach was key in helping our team address edge cases and maintain peak performance, and it ultimately cemented Waymo's status as a leader in the autonomous vehicle space. Now, at Coval, we’re taking these proven strategies and adapting them in a completely new way to speed up the development of AI agents. Our goal is to help engineers build agent experiences that genuinely work for users in the real world. Automated simulation and evaluation are critical to trusting agents with impactful tasks across industries. **Working With Us** =================== Building agents or know someone? Let’s talk! [Grab time with me here]( for a quick intro, or message me at [brooke@coval.dev](mailto:brooke@coval.dev). #### YC Sign Photo Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

Guardian AI

guardian-ai

https://www.withguardian.ai/

New York, NY, USA

Guardian is an AI platform to help healthcare providers (hospitals, MSOs, physician groups) fight denials and address unpaid claims. Providers deploy Guardian to: 1. Detect emerging patterns in payer reimbursements 2. Automate the diagnosis and resolution of unpaid claims and denials Our founding team ran AI revenue cycle programs at Mount Sinai, NYC Health+Hospitals, and several other large health systems at Palantir, generating millions of dollars per hospital while eliminating hundreds of hours of work.

Helping healthcare providers fight insurance denials.

Healthcare

Healthcare

S24

Active

Early

https://www.ycombinator.com/companies/guardian-ai

https://yc-oss.github.io/api/batches/s24/guardian-ai.json

Title: Guardian AI: Helping healthcare providers fight insurance denials. | Y Combinator URL Source: Markdown Content: ### Helping healthcare providers fight insurance denials. Guardian is an AI platform to help healthcare providers (hospitals, MSOs, physician groups) fight denials and address unpaid claims. Providers deploy Guardian to: 1. Detect emerging patterns in payer reimbursements 2. Automate the diagnosis and resolution of unpaid claims and denials Our founding team ran AI revenue cycle programs at Mount Sinai, NYC Health+Hospitals, and several other large health systems at Palantir, generating millions of dollars per hospital while eliminating hundreds of hours of work. Guardian AI Founded:2024 Team Size:2 Location:New York ### Active Founders ### Mayank Jain, Founder Guardian AI Co-founder, ex-Palantir, Microsoft, Jump. Before Guardian, Mayank was a lead on the Hospital's team at Palantir - overseeing product, sales, and implementation of our staffing & scheduling product. Born in India, grew up in Kuwait, studied CS + Business @ CMU '21 ### Pranav Pillai, Founder Before Guardian, Pranav was an Enterprise Lead on Palantir's Hospitals Team. He started and ran their Revenue Cycle Management vertical, doing $6M in sales in his first quarter on the job. Pranav graduated from the University of Pennsylvania's Jerome Fisher Program in Management & Technology (M&T) with an M.S. in Computer Science and dual Bachelors degrees in Computer Science and Finance. ### Company Launches [### Guardian AI: Helping healthcare providers fight insurance claim denials]( 🛎 **TL;DR** ------------ After helping hospitals implement AI workflows at Palantir, our team has built a product to help healthcare providers automate how they manage insurance claim denials. This is desperately needed by the 40% of hospitals in the US that have negative operating margins each year. **Within a month of launching, Guardian has helped recoup \>$150,000 in claim value for providers.** 🏥🚨 **Hospitals are Dying** ---------------------------- While he was in college, the hospital where Pranav’s mom worked in Philadelphia went bankrupt - [**Bernie Sanders actually picketed outside in protest.**]( The last two years at Palantir, Mayank and Pranav have been working with some of the biggest health systems in the country who, despite their size, had hundreds of millions in unpaid claims and were shutting down hospitals. Insurance companies are using AI to deny more claims. We’re on a mission to arm the providers and fix a system where 40% of hospitals are losing money. 🤖 **Fighting Denials with AI** ------------------------------- Denial management is a manual and painstaking process. Healthcare providers have a long string of tasks to complete — (1) call payers, (2) write appeal letters, (3) scrape patient charts for missing diagnoses and authorizations, (4) check for clerical errors, (5) check clearinghouses for patient eligibility and provider enrollment – the list goes on. There are so many tasks and systems required to work a denial that **most healthcare providers end up writing off 5-20% of their accounts receivable.** Our platform serves as a one-stop shop for denials management, where AI agents manage claims from end-to-end. 1. **Data Model:** Guardian integrates with Clearinghouses, Payer Portals, and EHRs. Billing teams no longer have to switch between systems. 2. **Claim Status & Denial Cohorts:** Looking at payer policies / contracts and trends in payer behavior, Guardian triages claims that are worth pursuing and determines a specific path to resolution. 3. **Automating Denial Resolution:** Our growing denial resolution suite automates payer phone calls, claim corrections and re-submissions, and a dozen other rote tasks in a denied claim’s lifecycle. 👨‍💼👨‍💼 **The Team** ----------------------- Mayank and Pranav were two of the first members of Palantir’s Commercial Healthcare Team. They’ve worked together to improve hospital operations at some of the largest health systems in the country. After implementing AI programs at health systems the last several years, they look forward to democratizing AI across US healthcare and avoiding heartbreaking hospital and clinical practice closures. 🤝 **Our ask:** 💰 **Our Offer:** --------------------------------- We do risk-free, rapid denials + AR age assessments for hospitals and medical practices. Give us your unpaid claims and we’ll run them through our software to find slam-dunk cases which payers have mis-processed - we’ve consistently found over $100K in low-hanging fruit when we’ve done this. Reach out at [founders@withguardian.ai](mailto:founders@withguardian.ai) or grab time at [withguardian.ai.](

Gauge

gauge

https://gauge.sh

San Francisco, CA, USA

Gauge is solving the monolith/microservices dilemma. We’re helping enterprises break large codebases into small pieces. We first met as roommates in college, and in the decade since we've both worked exclusively at startups, including multiple founding engineering roles. We ran into this problem time and time again as our startups began to scale. We're now working with a wide range of companies, including a number of multi-billion $ enterprises. Our open source tooling also has ~1k stars on GitHub, over 400k downloads, and is in use by Nvidia. In the short term, Gauge is building tools to modularize the monolith. Long term, Gauge is building a way to deploy a single codebase as a set of independent services, giving you the scalability of microservices alongside the simplicity of monolithic development.

Solving the monolith/microservices dilemma.

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/gauge

https://yc-oss.github.io/api/batches/s24/gauge.json

Title: Gauge: Solving the monolith/microservices dilemma. | Y Combinator URL Source: Markdown Content: ### Solving the monolith/microservices dilemma. Gauge is solving the monolith/microservices dilemma. We’re helping enterprises break large codebases into small pieces. We first met as roommates in college, and in the decade since we've both worked exclusively at startups, including multiple founding engineering roles. We ran into this problem time and time again as our startups began to scale. We're now working with a wide range of companies, including a number of multi-billion $ enterprises. Our open source tooling also has ~1k stars on GitHub, over 400k downloads, and is in use by Nvidia. In the short term, Gauge is building tools to modularize the monolith. Long term, Gauge is building a way to deploy a single codebase as a set of independent services, giving you the scalability of microservices alongside the simplicity of monolithic development. ### Latest News Gauge Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Caelean Barnes, Founder CEO at Gauge - open source dev tools to solve the microservices/monolith dilemma. Previously founding eng. at Standard Metrics and Noble AI. Early at Carta, Roku, UCLA Internet Research Lab. ### Evan Doyle, Founder CTO at Gauge - building OSS to fix balls of mud! Early engineer and tech lead at Carta, Standard Metrics. Previously did technical consulting for early stage startups. ### Company Launches [### ⚙️ Gauge - Solving the microservices/monolith dilemma]( **TL;DR: Gauge is building open source tools to solve the microservices/monolith dilemma.** We’re doing this by enabling teams to build a **modular monolith**. Our first tool is called [Tach]( and it brings some of the power of microservices to your monolith, without all of the headaches. 🙏 Our Ask ---------- * **Are you undergoing a microservices <\> monolith migration?** We’d love to learn from your experience! * **Are you scaling a Python monorepo?** Give [Tach]( a try (and a ⭐)! It’s open source and free. If any of the above resonates with you, we’d love to buy you a drink! [Grab a time with the founders here]( ⚠️ The Problem Startups need to move fast. As they grow, code quality takes a back seat to velocity, inevitably leading to code sprawl and tightly coupled services. This creates an environment where even simple features and refactors become incredibly painful. Once startups reach this stage, they often reach for microservices. Unfortunately, this is like trying to fix a dirty kitchen by building a new house for the sink. With microservices, you introduce a whole new world of challenges - orchestration, lifecycle management, versioning dependencies, and more. ⚙️ The Solution --------------- By separating a monolith into decoupled modules with well defined interfaces, you get the benefits of microservices without the immense complexity that comes with it. Our first tool, [Tach]( lets you do just that. We recently rewrote the core in Rust ([~19x speedup]( [added visualization]( and [shipped test impact analysis support]( We’re currently live in production with a number of companies, have over [300k downloads]( and over 900 stars on [GitHub]( _An example of Tach on the FastAPI repo_ Next, we’re building more tools to help you scale a modular monolith - architecture enforcement, intelligent cached task execution, smart build and deployment pipelines, and more. Long term, we’re excited by a new approach that will allow you to deploy your modular monolith as a set of independent services. This will bring over the remaining set of benefits that microservices offer, including independent scalability and fault tolerance. Google recently put out a paper [describing this idea]( While the FAANGs have bespoke in-house solutions, the rest of the industry is far behind. We see an opportunity to bring this capability to everyone. 🧑‍🤝‍🧑 About Us ----------------- [Evan]( and I ([Caelean]( met as roommates in college, and in the decade since, we’ve both worked exclusively at startups, including multiple founding engineering roles. We’ve seen attempts to split up the monolith drain millions of dollars in engineering hours and ultimately fail. At every startup we’ve helped build, we’ve run into the problem of how to maintain development velocity as the team and codebase scales. We’re building the tools that we wish we had. If any of the above is interesting to you, [we’d love to chat]( Some more ways to follow along: * [Give us a ⭐ GitHub]( * [Join the conversation on Discord]( * [Check out our blog]( * [Chat with us on Twitter]( ❓Bonus ------ For those who aren’t familiar with microservices, here’s a great summary: [ ### YC S24 Application Video

Zeit AI

zeit-ai

https://zeit-ai.com/

San Francisco, CA, USA

Zeit AI transforms Excel files in a structured database that can be queried using natural language. For example, the financial consultancy RISE, which depends heavily on Excel, uses Zeit AI to access and analyze expenses across their organization.

Enterprise insights from tabular data in seconds, with just a few…

B2B

B2B -> Analytics

S24

Active

Early

https://www.ycombinator.com/companies/zeit-ai

https://yc-oss.github.io/api/batches/s24/zeit-ai.json

Title: Zeit AI: Enterprise insights from spreadsheet data with just a few words. | Y Combinator URL Source: Markdown Content: ### Enterprise insights from spreadsheet data with just a few words. Zeit AI transforms Excel files in a structured database that can be queried using natural language. For example, the financial consultancy RISE, which depends heavily on Excel, uses Zeit AI to access and analyze expenses across their organization. Zeit AI Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Leopold von Waldthausen, Founder Hi everyone! Welcome to my YC profile. I spent 3.5 years at Palantir, ultimately leading all established customers in Germany, Austria and Switzerland. Before that, I studied CS at Oxford, published research on process mining and cryptography, quit an MBA at Yale. During my undergraduate, I already started my first business (weview) at 18 years, which I built for 3 years and then sold to DemoUp Cliplister. Hit me up for any activity to do with mountains and I'll be your fan. ### Marvin Christopher Bornstein, Founder Grew up around Berlin, Germany and lived in London, U.K. for the last 5 years. Been writing software for over 18 years, professionally for almost 10. My focus is on full stack dev and data eng. I have researched deep learning topics and participated in numerous hackathons and InfoSec CTFs. I spent my last 5 years at Palantir in various roles across the business and have delivered value for customers in many industries (chemicals, railway infra, media, utilities, insurance, medical equipment). Marvin Christopher Bornstein [Zeit AI]( ### Company Launches [### 📈💡Zeit AI: Insights from your tabular data with just a few words]( ### **🏆 TLDR** [Zeit AI]( is ChatGPT for enterprise tables. You can upload tables as Excel, CSV, PDF, and more. Atop of these tables, simple questions in natural language can be used to locate data, combine it, generate analyses, or even charts. All results are repeatable and explainable. They can be exported at the click of a button. [Watch our demo!]( 🧑‍💻🌟 **The Team** -------------------- Together, [Marvin]( and [Leopold]( have over 15 years of combined experience in data engineering and analytics. During our four years side-by-side at Palantir, we led high-impact projects, building an AI rule-engine and generating over €50 million in novel project revenue. We saw first-hand how corporates heavily relied on Excel files, leading to manual work to analyse and combine data. A solution like Zeit AI would have been a game-changer in accessing this data at scale. ⚠️ **Problem** -------------- Non-technical users find it challenging to access and analyse enterprise data. Yet, making data-driven decisions is crucial in today’s fast-paced world. 1. Data is stored in files rather than structured databases. 2. Databases cannot be accessed by non-technical users. 3. Data often needs to be exported and manually combined in Excel. 💡 **Solution** --------------- Zeit AI allows non-technical users to derive ad-hoc insights from tables using natural language. This is possible in just three steps. 1. Drop data files (We support Excel, CSV exports from databases, and PDFs). 2. A structured cloud database is instantly generated and ready to be explored. 3. Use natural language to seamlessly derive insights from the data. 🛠️ **How Zeit AI is Used Today** --------------------------------- **Procurement** 🛒 Gaining the upper hand during negotiations by having ad-hoc access to all historical procurement data. **Consulting** 🗂️ Rapidly explore and analyse data rooms and client files using natural language to confidently deliver value to clients. **Controlling** 📊 Access extracts from accounting systems and seamlessly combine them with files across departments for comprehensive financial control. ✅ **Ask** --------- [Book a slot]( with us to explore using Zeit AI. Refer us to procurement managers and senior consultants. ([founders@zeit-ai.com](mailto:founders@zeit-ai.com)) Get on a [30-minute call]( with us for a live demo or free office hours for anyone struggling to easily access tabular data at scale. #### YC Sign Photo #### Company Photo ### Hear from the founders #### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?) We founded Zeit AI after working side-by-side at Palantir for four years. Together, we led forward-deployed teams—Leopold on the strategic side and Marvin on the technical side. We developed software for operational teams at our client's site under high time pressure, addressing urgent data issues while leading Palantir’s highest-potential public client in Europe. During our time at Palantir, we saw first-hand that any hole in corporate data strategies was stuffed by Excel files, but there was no effective way to access and utilize the knowledge contained in these files at scale. This insight inspired us to create Zeit AI, a solution that transforms Excel files into a structured database, that makes it easy to query them using just natural language.

Simple AI

simple-ai

https://www.usesimple.ai

San Francisco, CA, USA

Simple AI is what Siri should be. We make it 10x easier for you to use your favorite consumer apps: Amazon, Uber, Doordash, Venmo, Google Maps, etc. We also help you do research and book arbitrary things: restaurants, flights, or that local minigolf place that doesn’t have a website.

Better Siri

Consumer

Consumer

S24

Active

Early

https://www.ycombinator.com/companies/simple-ai

https://yc-oss.github.io/api/batches/s24/simple-ai.json

Title: Simple AI: Better Siri | Y Combinator URL Source: Markdown Content: ### Better Siri Simple AI is a better Siri. We make it 10 times easier to buy things on Amazon, call Ubers, and book appointments or reservations at any business. Simple AI Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Catheryn Li, Founder Cat is co-founder and CEO of Simple AI. Previously, she spent 4 years at Y Combinator, where she led the software team responsible for Startup School, the YC Library, and YC's Co-Founder Matching site. She has degrees in computer science and math from MIT. ### Zach Kamran, Founder Zach is the co-founder and CTO of Simple AI. He previously worked at YC for 3 years as a tech lead and the Head of Product for the Bookface team. He has a degree in CS and Statistics from UChicago and has worked in various roles leading analytics and software teams. ### Company Launches [### Simple AI - a better Siri]( [Simple AI]( is what Siri should be. We make it 10x easier for you to use your favorite consumer apps: Amazon, Uber, Doordash, Venmo, Maps, etc. We can also help you do research and book anything from restaurants and flights to that local minigolf place that doesn’t have a website. The consumer products we use every day are often confusing, adversarial, and sometimes downright deceptive. It makes sense when you realize that Amazon and Google’s primary customers are merchants and advertisers, not you and me. Our goal is to help you cut through the noise and go from “having an intent” to “getting it done.” ### **Our ask** If you have an iPhone, try out our mobile app! Please reach out to [founders@usesimple.ai](mailto:founders@usesimple.ai) or join the [waitlist]( and we’ll onboard you soon. ### **Team** [Zach]( and [Catheryn]( met at YC, where they spent 4 years building consumer products like Bookface, Startup School, and YC’s co-founder matching site. #### Company Photo

Comfy Deploy

comfy-deploy

https://comfydeploy.com

San Francisco, CA, USA

We a platform for product teams to collaboratively build and deploy AI video and image workflows using ComfyUI, instantly transforming custom workflows into scalable APIs. ComfyUI workspace - Replace cobbled-together solutions with a unified, team-focused environment without the pain of self-hosting - Eliminate "works on my machine" issues with version control - Shared storage for models and input/outputs across your organization - Leverage the power of ComfyUI without the complexities of self-hosting Powerful GPU Infrastructure - Access managed GPUs that grow with your teams needs - Tailor the platform to your requirements by easily installing custom nodes and models Custom configuration - Download the models you want, stored privately in your personal volume - Install the custom nodes your workflow needs API Deployments: From workflow to production in seconds - Transform any workflow into a fully functional API immediately without extra engineering - Comprehensive observability on every run - Built-in API authentication -TS/JS/Python/Ruby SDKs for seamless integration

Best place for product teams to use ComfyUI.

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/comfy-deploy

https://yc-oss.github.io/api/batches/s24/comfy-deploy.json

Title: Comfy Deploy: Vercel for Gen AI applications | Y Combinator URL Source: Markdown Content: ### Vercel for Gen AI applications Comfy Deploy lets developers build and deploy workflows that use Stable Diffusion and other models to produce images and video. Instead of cobbling together fragmented tools, teams now build workflows that generate assets they need on their own. \*\*Team ComfyUI workspace\*\* • Replacing cobbled-together solutions with a unified, team-focused environment without the pain of self-hosting. • Eliminate "works on my machine" issues with version control. • Share storage for models and outputs. • Leverage the power of ComfyUI without the complexities of self-hosting \*\*Powerful GPU Infrastructure\*\* • Access managed GPUs that grow with your teams needs • Tailor the platform to your requirements by easily installing custom nodes and models \*\*Custom configuration\*\* • Download the models you want, stored privately in your personal volume • Install the custom nodes your workflow needs • Train models on your own datasets. \*\*API Deployments: From workflow to production in seconds\*\* • Transform any workflow into a fully functional API immediately without extra engineering • Comprehensive observability on every run • Built-in API authentication • TS/JS/Python/Ruby SDKs for seamless integration Comfy Deploy Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Nicholas Kao, Founder Building an image generation platform. ### Benny Kok, Founder Building ComfyDeploy, a platform empowering teams to deploy custom AI workflows using ComfyUI. With a background in music, game development, and programming, he's passionate about making advanced AI tools accessible to non-technical users, revolutionizing how teams interact with AI in creative processes. ### Company Launches [### Comfy Deploy - ComfyUI for product teams]( **Tl;dr: ComfyDeploy is the best way for product teams to build and tailor AI video and image workflows using ComfyUI, which can instantly deploy custom workflows as APIs.** Hey everyone, we're Nick and Benny, the team building [Comfy Deploy]( **Problem** Product teams struggle to build AI video and images in their workflows using fragmented tools and inflexible controls from off-the-shelf solutions. ComfyUI is a powerful tool that solves this and gives control back to the user, but there are challenges for teams to use it. 1. Complex Self-Hosting: Setting up and maintaining ComfyUI for teams is technically demanding and time-consuming, distracting teams from their core product development. 2. Collaboration: ComfyUI wasn't built for teams, making it challenging to share, edit, and run workflows between team members 3. Hardware Limitations: Running complex AI workflows requires powerful GPUs. 4. Slow Deployments: Deploying ComfyUI workflows as scalable, production-ready APIs requires significant engineering effort. **Solution** We’ve created the best way for product teams to use ComfyUI to build and tailor their AI image and video workflows with ComfyUI. Key Benefits: * Managed platform: Managed ComfyUI workspace, which can install any custom node and model. * Team Collaboration:  Work together seamlessly with a team workspace designed for sharing, editing, and running workflows across your team. * Scalable Infrastructure: Powerful cloud GPUs on-demand, with auto-scaling to grow with your team's needs. * Instant Deployment: Transform your ComfyUI workflows into scalable, production-ready APIs with just one click; no additional engineering required, with multi-language SDKs. Some wins and testimonials from our users * _Production time is now up to 300% faster. Producing a complete character pack for Mighty Action Heroes used to take 6 man-weeks. It now takes 1.5 man-week_ - Ben, Chief AI officer, Mighty Bear Games. * _ComfyDeploy has laid a lot of the groundwork for us, allowing us to move quickly and save on our engineering budget which is crucial in our fast-paced environment. 10/10, I would highly recommend it_ - Javid, CEO, Secret Desires. * _Comfy Deploy comes in and addresses the main barrier to using ComfyUI while also taking it a step further and allowing us to deploy our unique ComfyUI workflows. This allows us to seamlessly integrate image generation into our product, freeing up time to focus on developing our product. Comfy Deploy also comes with tools for sharing, editing, and managing workflows in a collaborative environment, enabling more of our team to get involved in the process of building image generation processes_ - E, AI Applied Engineer, VC backed in stealth. **How it works** Access our managed ComfyUI environment, with pre-configured machines and models. Share and manage your workflows in your team, install custom nodes and models as needed. Deploy your workflows instantly as API and integrate them into your products. **Why we’re building this** Product teams have much to gain from owning and iterating on their own AI pipelines. Benny created the v1 of Comfy Deploy when, as CTO at his previous startup, he saw the issues with the handoff between applied AI artists and engineering. We think this is an exciting tool for product teams to take the first step and develop their skill sets and capabilities with these exciting new tools. **The Offer 🤝** If your team is interested in using the best way to use ComfyUI for product teams, sign up for a free trial here at [ and schedule an on-boarding call with us [ Contact us at [founders@comfydeploy.com](mailto:founders@comfydeploy.com)

Snowpilot

snowpilot

https://www.snowpilot.com

San Francisco, CA, USA

Snowpilot is a spreadsheet-like UI with the full power of a data warehouse. Powered by cutting-edge database tech, Snowpilot lets non-technical users join datasets and query live across billions of rows, with data automatically pulled in from tools like Salesforce, Zendesk, Gong, and Posthog. Ben and Dom met at a Sequoia & a16z-backed data startup, Census. Together, we built the first real-time, warehouse-native customer data platform. Prior to that, Dom led 20+ ML engineers at Adobe to build their internal ad optimization platform, which allocates $1B in annual spend. Ben built the microservices stack powering the new Microsoft Edge, scaling from 0 to hundreds of millions of DAUs. We started coding Snowpilot two weeks ago (mid-August '24), and we already have a live demo app that can run sub-second queries on millions of rows, entirely in the user's browser. The data warehouse market is $10B/yr, growing 23% YOY. We will disrupt incumbents and significantly expand this market by enabling non-engineers to use the data warehouse on a daily basis.

The data warehouse that's as simple as a spreadsheet

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/snowpilot

https://yc-oss.github.io/api/batches/s24/snowpilot.json

Title: Snowpilot: The data warehouse that's as simple as a spreadsheet | Y Combinator URL Source: Markdown Content: ### The data warehouse that's as simple as a spreadsheet Snowpilot is a spreadsheet-like UI with the full power of a data warehouse. Powered by cutting-edge database tech, Snowpilot lets non-technical users join datasets and query live across billions of rows, with data automatically pulled in from tools like Salesforce, Zendesk, Gong, and Posthog. Ben and Dom met at a Sequoia & a16z-backed data startup, Census. Together, we built the first real-time, warehouse-native customer data platform. Prior to that, Dom led 20+ ML engineers at Adobe to build their internal ad optimization platform, which allocates $1B in annual spend. Ben built the microservices stack powering the new Microsoft Edge, scaling from 0 to hundreds of millions of DAUs. We started coding Snowpilot two weeks ago (mid-August '24), and we already have a live demo app that can run sub-second queries on millions of rows, entirely in the user's browser. The data warehouse market is $10B/yr, growing 23% YOY. We will disrupt incumbents and significantly expand this market by enabling non-engineers to use the data warehouse on a daily basis. Snowpilot Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Dom Crosby, Co-founder & CEO Dom Crosby is co-founder & CEO of Snowpilot, the Data Warehouse that's as simple as a spreadsheet. Starting his career as an analyst for the UK Ministry of Defence, he has since worked in Big Data and ML for the last decade leading product for high profile ML and data solutions at Adobe & Census (Sequoia & a16z backed.) ### Ben Warren, Co-founder & CTO Co-founder & CTO of Snowpilot, the data warehouse that's as simple as a spreadsheet. Started as a software engineer at Microsoft, scaling the new Edge browser. After that, built next-gen data tooling at Census (backed by a16z & Sequoia). ### Company Launches [### Snowpilot: The data warehouse that’s as simple as a spreadsheet]( **TL;DR:** We’ve built a spreadsheet-like UI with the full power of a data warehouse. Powered by cutting-edge database technology, [Snowpilot]( lets non-technical users join datasets and query across billions of rows, with live data pulled in from tools like Salesforce, Zendesk, Gong, and Posthog. Hey everyone, we’re [Ben]( and [Dom]( We met at a Sequoia & a16z-backed data startup, Census. Together, we built the first real-time, warehouse-native customer data platform. Prior to that, Dom led 20+ ML engineers at Adobe to build their internal ad optimization platform, which allocates $1B in annual spend. Ben built the microservices stack powering the new Microsoft Edge, scaling from 0 to hundreds of millions of DAUs. Locked up data = blocked deals 🤬 --------------------------------- At every company we worked at, deals and features went awry because non-engineers were blocked on basic questions across customers, products, and deals. In theory, all of the data was in Snowflake, but in practice… * Sales couldn’t find the status of their deals’ feature requests * PMs weren’t able to estimate the value of a feature * Support couldn’t triage issues based on account size We accepted that queries had to go through some “data guy”. This meant that most questions were never answered, deals were lost, and the wrong features were built. We simplify data access, 10x’ing business velocity ✅ ---------------------------------------------------- With Snowpilot, we’ve taken the much-loved spreadsheet interface and given it the full power of the data warehouse. Snowpilot feels like using Excel or Notion databases, but without the limitations: * Connected to live data from sources like Salesforce, Zendesk, and Gong * Simple interface that abstracts away complex operations, such multi-table joins, grouping, pivots, and deduplication * Scales to infinity Demo ---- [ Solving data engineering, once and for all ------------------------------------------ For decades, business users have been bottlenecked on the data guy. That era is coming to a close. The UX landscape has been opened up by a few key tech advancements: * Fast, in-memory columnar query engines (DuckDB, DataFusion) * Standardized data formats (Apache Arrow, Parquet, Iceberg) * LLM-automated grunt work (picking join keys, data cleaning, field mapping) Snowpilot is solving data engineering, forever. And we couldn’t be more pumped to make it happen. Try the Snowpilot demo today ---------------------------- To get a taste, check out our live demo: [

Tandem

tandem-2

https://tandem.space/

San Francisco, CA, USA

The pandemic reduced office use nationwide by 50%, and tenants have been left to deal with highly inflexible, long term lease agreements that don’t fit today’s office use patterns. The traditional brokerage model works great for big spaces and long terms. But when you want to talk smaller units, short term lengths, shared and common areas, you’re out of luck. Tandem is an AI-enabled office leasing platform. We’re using technology to unlock flexible, month-to-month agreements in quality, ready-to-go spaces. Our AI co-pilot enables a white-glove-quality B2B office search experience, with a fraction of the human labor typically required. Today we’re serving two primary markets — NY & SF, with hundreds of active Hosts in each. We’ve helped match more than 100 companies and have seen double-digit month-over-month growth.

Marketplace to help companies lease and share office space

B2B

B2B -> Office Management

S24

Active

Early

https://www.ycombinator.com/companies/tandem-2

https://yc-oss.github.io/api/batches/s24/tandem-2.json

Title: Tandem: Marketplace to help companies lease and share office space | Y Combinator URL Source: Markdown Content: ### Marketplace to help companies lease and share office space The pandemic reduced office use nationwide by 50%, and tenants have been left to deal with highly inflexible, long term lease agreements that don’t fit today’s office use patterns. The traditional brokerage model works great for big spaces and long terms. But when you want to talk smaller units, short term lengths, shared and common areas, you’re out of luck. Tandem is an AI-enabled office leasing platform. We’re using technology to unlock flexible, month-to-month agreements in quality, ready-to-go spaces. Our AI co-pilot enables a white-glove-quality B2B office search experience, with a fraction of the human labor typically required. Today we’re serving two primary markets — NY & SF, with hundreds of active Hosts in each. We’ve helped match more than 100 companies and have seen double-digit month-over-month growth. Tandem Founded:2023 Team Size:9 Location:San Francisco ### Active Founders ### Rafi Sands, Founder Rafi is Co-Founder & CEO of Tandem. Rafi is an 18-time marathon runner, Guinness World Record Holder, Oaklandian, and former management consultant (one of these things is less exciting than the others…). He spent two years at Stanford researching the future of the office market after COVID under Professor Nick Bloom. Read his blog at rafisands.substack.com ### Kristen Gallogly, Founder With a passion for efficiency, helping, and creating value, Kristen merges 8 years of experience advising companies in the commercial real estate world with an art of the possible mindset to change how companies lease and access office space. ### Brendan Suh, Founder Brendan is Co-Founder & Head of Marketing at Tandem. After 3 years of management consulting at Bain, Brendan led marketing at a DTC startup and scaled them from $6 to $10M ARR. He also bootstrapped an e-commerce business prior to building Tandem. ### Company Launches [### Tandem - Marketplace for flexible office leasing]( **_tl;dr:_** _Tandem is a marketplace that uses AI to make the office leasing process less tedious. Whereas a typical office search takes 3-6 months, Tandem’s platform gets it done in 14 days or less. Since launching in NYC & SF earlier this year, **the team has helped \>100 companies find off-market space, paying out \>$1M in rent through its platform.**_ [ * * * * * * * * * Hey everyone, we’re building [Tandem]( a marketplace to help companies flexibly lease office space. ### ❌ The Problem Renting an office is expensive and hard. Here’s how the traditional process works: hire a broker, tour options for months, hire a lawyer to review a lease, sign for a 1-5 year minimum term, hire another broker to sublease the space when you outgrow it, repeat. COVID has left US offices half as full as they were in 2019 and resulted in landlords sitting on $500B+ in losses. This means tons of excess space that both landlords and companies are paying for, but because the traditional process is so tedious, they have no way of offering it flexibly - the way tenants these days want it. ### 🔍 The Solution **Tandem is a new type of office marketplace that uses AI-powered workflows to help companies list, discover, and pay for new office space.** Lower transaction costs mean shorter lease terms — Tandem customers can trade spaces, upsize or downsize, with as little as 30 days notice. [ To provide access to unique supply, Tandem helps top companies rent out office space in iconic buildings (e.g., the World Trade Center), almost like a long-term Airbnb for a business. Hosts can list their excess space on our marketplace, and our platform will coordinate tours with prospective teams, manage legal, and process rent payments. Companies looking for space can browse off-market options, meet interesting Hosts, pay rent through our platform, and maintain flexible month-to-month contracts. We have 200+ offices across New York, San Francisco, and Los Angeles, with more than 100 companies actively sharing. Here’s a sample of our community’s favorite spaces, MTV cribs-style: 🗺️ **World Trade Center (FiDi, NYC)** 🗺️ **Spring Street (SoHo, NYC)** 🗺️ **Bryant Street (Mission Bay, SF)** ### 🙏🏼 Asks * If your company / a company you know has **excess office space,** we’d love to help you earn money for that space! * If you’re **looking for an office**, let us know, and we’ll help you find a new home! Thanks for reading! The Tandem Team

Spur

spur

https://www.spurtest.com/

San Francisco, CA, USA

Never code up another test or hire an external QA team. We handle and automate all functional and E2E testing.

Spur is your AI QA Engineer. Test your websites with natural language.

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/spur

https://yc-oss.github.io/api/batches/s24/spur.json

Title: Spur: Spur is your AI QA Engineer. Test your websites with natural language. | Y Combinator URL Source: Markdown Content: ### Spur is your AI QA Engineer. Test your websites with natural language. Never code up another test or hire an external QA team. We handle and automate all functional and E2E testing. Spur Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Sneha Sivakumar, Founder Co-founder and CEO at Spur. Previously, Growth Engineer at Figma and Snap. ### Anushka Nijhawan, Founder Co-founder and CTO and Spur. Previously @ Yale CS, Deepmind, and Meta. ### Company Launches [### ✨ Spur - Your AI QA Engineer]( **TL;DR: Spur lets you test your website with natural language.** ----------------------------------------------------------------- You can launch web agents that mimic exactly what your users do on your platform, so you can ensure your product doesn’t fail your users. ----------------------------------------------------------------------------------------------------------------------------------------- * * * ### Launch Day Deal 🎉 As part of launch day, we are offering to help you set up tests for your **core flows** on [signup]( for free. Use the code `SPUR_LAUNCH` on signing up to redeem this deal. — Here’s how it works! (A flow we test for the YC Tech Team) ---------------------------------------------------------- An example test for YC’s Application Portal to Invite Co-Founders [ **⛔️ The Problem (Do we even need to get into this?)** ------------------------------------------------------ A. Testing is TIME-CONSUMING and PAINFUL. 🤕 * whether you write a test * or manually check (or maybe not check) your core flows every single time you merge to production B. Tests are not MAINTAINABLE; they break! 🛠️ * Your UI is constantly changing, and maintaining test scripts is a tedious task. **✨ The Solution** ------------------ On Spur, you can: * Write automated tests in minutes (_not hours_) with natural language 💨💨 * Not worry about maintaining tests when your UI changes 💅 _We use multimodal agents that interact with your web pages exactly like users would. Tests are not bound to CSS selectors_ **🧡 The Team behind Spur** --------------------------- [Anushka]( and I met our freshman year at Yale. We did research at the Yale NLP Lab on web agents. [Sneha]( (here!) previously worked on growth at Figma, and Anushka at DeepMind. We’ve hacked on our fair share of projects before — and have very much felt the pain of neglecting testing. **🤝 Our Ask** -------------- ### **If this problem is one that you face, try us out!** * Book a [demo]( * [Sign up!]( We are live and actively onboarding customers every single day Our customers have found a **lot** of value from using us so far, and we’d love to take testing off your plate. Here is what some of them have said :) > Spur is shockingly easy to use—no coding, just plain English. Simply describe what you want to test, and Spur handles the rest. Onboarding was a breeze, and Anushka and Sneha are fantastic to work with. > > _\- Eve Bouffard, Product Engineer @ YC Tech Team_ > I’m gonna see if I can expense Spur through my wellness stipend. Category: Therapy > \- Gabe Wilson, Founder & CTO @ Terrakotta > We had a HUGE UI revamp and are still able to test easily without needing maintenance, not a single test has broken due to flakiness. They mean it when they say their tests are reliable.  > \- Joseph Parker, Founder & CTO @ VecFlow > We’ve been using Spur and it’s been AMAZING — unlike all the competitors that we’ve tried, they actually work! Can highly recommend. > \- Konsti Wohlwend, Founder @ StackAuth #### YC Sign Photo ### Hear from the founders #### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?) Anushka and I met our freshman year at Yale. We did research at the Yale NLP Lab on web agents. Sneha previously worked on growth at Figma, and Anushka on codegen at DeepMind. We’ve hacked on our fair share of projects before — and have very much felt the pain of neglecting testing.

AnswerGrid

answergrid

https://answergrid.ai/

San Francisco, CA, USA

AnswerGrid is an AI-powered web research tool realised as a spreadsheet. For our first research problem, we’re helping founders discover the 30 most relevant leads worth the investment of manual outbound every day. Both co-founders (Noah and Bolu) have led the development of mission-critical software during their time at Palantir. Noah, as a Tech Lead working on platform security infrastructure used on the company’s largest contracts (incl. the UK's NHS and the US Gov), and Bolu, as a Tech Lead on the contract-winning team behind the company's largest engagement in South Korea.

Accelerate your web research.

B2B

B2B -> Productivity

S24

Active

Early

https://www.ycombinator.com/companies/answergrid

https://yc-oss.github.io/api/batches/s24/answergrid.json

Title: AnswerGrid: AI research agents for Strategy Consultants and Investment Analysts | Y Combinator URL Source: Markdown Content: AnswerGrid: AI research agents for Strategy Consultants and Investment Analysts | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( AnswerGrid ========== AI research agents for Strategy Consultants and Investment Analysts [S24]( Active [productivity]( Francisco]( * * * [Company]( [Jobs](  [ * * * ### AI research agents for Strategy Consultants and Investment Analysts AnswerGrid is an AI-powered web research tool realised as a spreadsheet. For our first research problem, we’re helping founders discover the 30 most relevant leads worth the investment of manual outbound every day. Both co-founders (Noah and Bolu) have led the development of mission-critical software during their time at Palantir. Noah, as a Tech Lead working on platform security infrastructure used on the company’s largest contracts (incl. the UK's NHS and the US Gov), and Bolu, as a Tech Lead on the contract-winning team behind the company's largest engagement in South Korea. AnswerGrid Founded:2024 Team Size:2 Location:San Francisco Group Partner:[David Lieb]( ### Active Founders ### Bolu Ben-Adeola, Founder Bolu is the Co-Founder and CEO of AnswerGrid. Before AnswerGrid, he tech-led teams at Palantir, winning new business and tackling problems in heavy-industries manufacturing and logistics network optimisation. Bolu Ben-Adeola [AnswerGrid](  []( "Twitter account") []( "LinkedIn profile") ### Noah Ohrner, Founder Noah is the Co-Founder and CTO of AnswerGrid. Before AnswerGrid, he was a Tech lead on the Security & Governance team at Palantir. He got his BA in Computer Science from the University of Cambridge. Noah Ohrner [AnswerGrid](  []( "Twitter account") []( "LinkedIn profile") ### Company Launches [### AnswerGrid - Scale your web research for relevant outbound]( Hello! We’re [Bolu]( and [Noah]( and we’re building AnswerGrid, an AI-powered web research tool realised as a spreadsheet. For our first research problem, we’re helping founders discover the 30 most relevant leads worth the investment of manual outbound every day. [Demo]( **Problem** =========== B2B founders find that the most effective lead qualification goes beyond industry category filters and instead involves evaluating a company against many loose heuristics. For example, one of our early customers qualifies leads with questions like, "Do they offer subscription or usage-based pricing?". Founders have been forced to choose between this sort of thoughtful qualification research and increasing the reach of their high-quality outbound. Until now :) **Solution** ============ AnswerGrid helps founders run their lead qualification research at scale. We, however, **_do not_** want to scale AI spam :) Instead, we are helping teams codify and deploy the research to discover leads that justify investing in human-written outreach. **Why we’re working on web research** ===================================== Most web research workflows—from a research analyst going deep into a new sector to a content creator in the market to buy new recording gear—start as questions in browser tabs, then move on to become answers in the cells of a spreadsheet, paragraphs in a document, or bullet points on a slide deck. We’re now close to having these research deliverables _write themselves_. We have the intelligence (thanks to LLMs) but lack the interfaces and infrastructure to do it well (great). We founded AnswerGrid to build these interfaces and infrastructure. **Why start with lead qualification?** ====================================== Because the research outcome is immediately actionable—"Who should I sell to today?"—and the feedback cycles are short—"Was that lead relevant?". **What’s next?** ================ We want to help more people avoid choosing between scale and quality in their web research workflows. Please [**book time with us**]( if you have a similar use case in private equity, management consulting, or elsewhere. **Asks** ======== 1\. If you’re selling to companies and would like to discover the 30 \[1\] most relevant people to speak with every day, kindly **Book time **[**Here**]( We’re offering a concierge experience to the **first 20 sign-ups**. Noah and I will be embedding with you as your personal growth ops team to help you discover, iterate on, and codify your qualification criteria. 2\. If you have a different research workflow with a similar shape you’d like help with, kindly **Book time **[**Here**]( In the meantime, you can play with the tool [**Here**]( Footnote ======== \[1\] Why 30 leads daily? We’re not dogmatic about it, but we’ve found this is about the number of daily personalised messages you can write before starting to sound like an LLM, which takes us back to where we started. There are other practical bottlenecks, such as LinkedIn connection limits. Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

Educato AI

educato-ai

https://www.educato.ai/

San Francisco, CA, USA

Educato builds exam prep platforms worldwide using AI. We are profitable, making $25.5k last month from 10 active exams and 10 more in the pipeline. Online exam prep has existed for decades, yet the big players all target the same top 10 exams in the US. The reality is that most exams around the world still have little to no quality online prep material, including many taken by hundreds of thousands of students each year. Educato uses AI to generate high-quality prep content for these exams. LLMs allow us to target the profitable fat middle in the distribution of exams, historically overlooked by education companies.

AI-Powered Worldwide exam-prep platform

Education

Education

S24

Active

Early

https://www.ycombinator.com/companies/educato-ai

https://yc-oss.github.io/api/batches/s24/educato-ai.json

Title: Educato AI: AI-Powered Worldwide exam-prep platform | Y Combinator URL Source: Markdown Content: ### AI-Powered Worldwide exam-prep platform Educato builds exam prep platforms worldwide using AI. We are profitable, making $25.5k last month from 10 active exams and 10 more in the pipeline. Online exam prep has existed for decades, yet the big players all target the same top 10 exams in the US. The reality is that most exams around the world still have little to no quality online prep material, including many taken by hundreds of thousands of students each year. Educato uses AI to generate high-quality prep content for these exams. LLMs allow us to target the profitable fat middle in the distribution of exams, historically overlooked by education companies. Educato AI Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Codrut Lemeni, Founder Known for a very difficult name to pronounce - ("Code" + "Roots). ### Felix Gabler, Founder Felix is the co-founder and CTO of Educato AI, an AI platform for educational content creation and personalization. He holds an M.Sc. in Machine Learning from the University of Tübingen and UC San Diego. Previously, Felix led as CTO at Sagacity, developing AI-driven simulations, and founded OurFlat to enhance household organization. ### Pierre-Louis Monnot, Founder Prior Life: - Echo @Palantir - Quant Markets @Bloomberg ### Company Launches [### 📚✨ Educato AI - Duolingo for every exam]( **TL;DR:** Educato uses AI to create high-quality exam prep for underserved students worldwide. With 10 exams live and 5,000+ students across Europe, Asia, and South America already on board, we’re expanding fast. Reach out to build with us: [founders@educato.ai.](mailto:founders@educato.ai) Hi everyone, we’re Codrut, Felix, and Pierre-Louis and we’re building Educato AI. ### **❌ The Problem** **Most exams don’t have any high-quality online prep material.** Exams and certifications aren’t going anywhere, especially in an AI world where anyone can fake any homework assignment. Online exam prep has existed for decades, yet the big players all target the same top 10 exams in the US. The reality is that many exams around the world—including some taken by hundreds of thousands of students each year—still lack high-quality online prep materials. As a result, students often turn to expensive private tutoring or mediocre resources, leading to poor learning outcomes. ### **🔧 Our Solution** The Educato platform allows us to quickly build high-quality adaptive learning experiences, **for any exam and geography**. We already offer prep for a diverse set of 10 exams across Europe, Asia, and South America, and are adding more every week. **Educato platform features**: * **High-quality content using AI**: Our models generate realistic exam questions from textbooks or past exams, with human-in-the-loop validation, linked to the original content * **Unique student experience**: Cutting edge features including personalized learning paths, AI essay grading with individualized feedback, and live simulation tests with peers * **Detailed analytics**: Leverage interactive tools and adaptive assessments to enhance student engagement, improve learning outcomes, and identify areas for improvements See the platform in action here: ### **💙** **Our Progress** Educato already supports 5000+ students, preparing them for exams such as: * 🇷🇴 Romanian Medical Residency * 🇮🇳 Indian Civil Service Exam * 🇵🇪 Peruvian San Marcos University Exam * 🇦🇷 Argentinian Medical Unico * \+ 6 more We’re currently adding 10 more exams and are looking for partners to expand our offering further. Calling all entrepreneurial educators to help us transform education and improve student outcomes - please reach us at [founders@educato.com](mailto:founders@educato.com).

Polymet

polymet

https://polymet.ai

San Francisco, CA, USA

Polymet makes it easy for product teams to create a design system and well-designed pages, components with AI. Whenever the team needs a new component or a page, they just give the prompt in, get the new design that follows their design system, and code out. It takes seconds and teams can iterate and ship faster.

AI Product Designer

B2B

B2B -> Engineering, Product and Design

S24

Active

Early

https://www.ycombinator.com/companies/polymet

https://yc-oss.github.io/api/batches/s24/polymet.json

Title: Polymet: AI Product Designer | Y Combinator URL Source: Markdown Content: ### AI Product Designer Polymet makes it easy for product teams to create a design system and well-designed pages, components with AI. Whenever the team needs a new component or a page, they just give the prompt in, get the new design that follows their design system, and code out. It takes seconds and teams can iterate and ship faster. Polymet Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Yusuf Hilmi, Founder Building Polymet to help product designers and engineers ship faster with AI. ### Furkan Köseoğlu, Founder Building an AI that can design and code. ### Company Launches [### Polymet - AI designer at your service]( **TL;DR** Polymet uses AI to help non-designers create production-ready designs and front-end code. They explain what they want to build or provide an image, and Polymet will design and implement it for them. [ Problem ------- * Most companies need help with design but don't have a designer * Designers can't design fast enough or are just slow… * Managers hate the long feedback loop with the designers, taking days for simple changes * They want to do it themselves but learning a complex editor like Figma is hard * They need to whip up a whole new demo with new features for a customer but don’t have time to design and build that Our Solution ------------ ### Design with AI Create designs by explaining what you need or providing images (can be hand-drawn sketches). * **No design expertise required:** Anyone can create beautiful and functional interfaces with us * **Quickly flesh out prototypes:** Use these for customer demos and share them with the team * **Quickly explore multiple design paths:** Generate multiple variations for inspiration ### Edit with Natural Language Refine your designs using simple English instructions; no need to learn complex editing tools like Figma. * Make changes quickly and easily, as if you're giving feedback to a designer * Select individual elements to ask for improvements, **just like commenting on Figma** ### Show Your Work to Customers and Teams * **Make demos for each customer:** Create a special preview link for each client and tune the demo for them. * **Work better with your team:** Send preview links to your team to get their thoughts on your designs right away. [ ### Explore a New UX Faster * **Create multiple variations:** with each prompt to find the best user experience * **Image to design:** Upload reference images, sketches, or Figma designs and get started "create similar step indicators in different forms, make them functional, and add subtle animations" **variations: 8** ### Production-Ready Frontend Code With Polymet, every design comes with high-quality frontend code that integrates with your existing codebase. * **Save time and money:** Polymet is better and faster than hiring a designer and a frontend engineer * **Reduce time from designs to code** for engineers ### Get Creative Polymet lets you make cool, complex designs easily. Here are some examples of that: * Make fun color pickers * Create dropdowns that move in interesting ways * Design eye-catching loading animations * Build tabs and buttons that respond smoothly * Craft date pickers that are easy and fun to use How can you help? ----------------- * Go ahead to [app.polymet.ai]( , try it out, and share what you've designed and your feedback! * If you don’t want to hire a designer and need urgent help with design, hit us up! * If you’re in SF, we might visit your office with some “Turkish Baklava” and onboard you personally :) * Introduce us to companies who are building out their component libraries and design systems, likely right before or after Series A * If you’re working at one of these companies and want to see the enterprise version, schedule a call from: [cal.com/yus-hilmi/onboarding](

Winford AI

winford-ai

https://winford.ai/

New York, NY, USA

Winford AI helps institutional credit investors monitor their loan portfolios and make better underwriting decisions. Our AI automatically extracts data from financial reporting packages and legal documents, helping portfolio managers invest in the right businesses and saving analysts hours every week.

AI-Powered Underwriting and Monitoring for Institutional Credit Funds

B2B

B2B -> Productivity

S24

Active

Early

https://www.ycombinator.com/companies/winford-ai

https://yc-oss.github.io/api/batches/s24/winford-ai.json

Title: Winford AI: AI-Powered Underwriting and Monitoring for Institutional Credit Funds | Y Combinator URL Source: Markdown Content: ### AI-Powered Underwriting and Monitoring for Institutional Credit Funds Winford AI helps institutional credit investors monitor their loan portfolios and make better underwriting decisions. Our AI automatically extracts data from financial reporting packages and legal documents, helping portfolio managers invest in the right businesses and saving analysts hours every week. Winford AI Founded:2024 Team Size:3 Location:New York ### Active Founders ### Jacob Tucker, Co-Founder, CEO Jacob brings several years of investment experience to Winford AI, where he is excited to build the next generation of software tools for investors. He was previously a credit investor at Blackstone, where he helped originate financing solutions for companies through the firm’s direct lending and opportunistic credit vehicles. Prior to Blackstone, Jacob received an M.S. in Computer Science and a B.A. in Business Economics from the University of Chicago. ### Rohan Prashant, Co-Founder, CTO Rohan is building Winford AI, software that uses AI to empower institutional credit investors to make better underwriting decisions and easily monitor loan portfolios. He was previously a Software Engineer at Microsoft and studied Computer Science at the University of Michigan (Go Blue!). ### Company Launches [### Winford AI - AI tools for institutional credit investors]( **tl;dr:** If you're a credit investor or finance professional who has ever been frustrated by tedious tasks or curious about how AI can help your investment fund, [Winford AI]( is designed for you. Get in touch at [founders@winford.ai](mailto:founders@winford.ai) ### **The Team:** [Jacob]( (Co-Founder & CEO) spent several years as a private credit investor at Blackstone, where he was involved in the underwriting of new deals and management of existing positions. [Rohan]( (Co-Founder & CTO) was previously a software engineer at Microsoft and NASA. ### **What are Institutional Credit Funds?** Institutional credit funds provide financing solutions to companies. Two verticals within credit investing include: * **Private Credit**: Bypasses traditional banks by providing tailored debt financing directly to companies with flexible terms. * **Opportunistic Credit**: Investing in high-yield opportunities in special situations, such as distressed assets or market dislocations. ### **The Problem:** Institutional credit investors often face the daunting task of navigating complex legal documents and dealing with imperfect financial reporting. The highly competitive nature of new deals and opportunities requires swift decision-making, while expanding portfolios make it challenging to efficiently and accurately track existing investments. ### **The Solution:** Our platform addresses pain points for investors across the firm: * **Investment committees**: Make better underwriting decisions and effortlessly monitor loan portfolios. * **Investment leaders**: Gain the upper hand in deal negotiations and opportunity analyses by using AI to easily compare proposed legal documents and diligence materials with historical data. * **Junior investors**: Save hours each week by extracting data from reporting packages and diligence materials, and automatically spreading financials into customized Excel templates. ### **Demo:** [ ### **Our Ask:** * **Introductions:** If you or someone you know is an institutional credit investor that would find our solution useful, or wants to understand how AI can help your investment fund, we’d love to connect. Please feel free to reach out or make an introduction at [founders@winford.ai](mailto:founders@winford.ai) or through [LinkedIn](

Pax

pax

https://getpaxai.com/

San Francisco, CA, USA

Pax uses AI to automate import tax refunds (aka duty drawback) for retailers and manufacturers. We launched 4 weeks ago and have ~$200K in contracts. Each year, 80% of eligible refunds—equivalent to $11B—go unclaimed. Pax is the first AI-powered broker helping brands under $50M reclaim 3-5% of their revenue. Our algorithms generate 15% more refunds than the industry leader and reduce processing time by 99% with AI. Pax was founded by Penny, an MIT PhD who encountered the duty drawback problem firsthand at Flexport, and Chris, a second-time founder and engineer with experience at Amazon, Brex, and TikTok.

TurboTax for Import Duty Rebate

B2B

B2B -> Supply Chain and Logistics

S24

Active

Early

https://www.ycombinator.com/companies/pax

https://yc-oss.github.io/api/batches/s24/pax.json

Title: Pax: AI Broker for Import Tax Refund | Y Combinator URL Source: Markdown Content: ### AI Broker for Import Tax Refund Pax uses AI to automate import tax refunds (aka duty drawback) for retailers and manufacturers. We launched 4 weeks ago and have ~$200K in contracts. Each year, 80% of eligible refunds—equivalent to $11B—go unclaimed. Pax is the first AI-powered broker helping brands under $50M reclaim 3-5% of their revenue. Our algorithms generate 15% more refunds than the industry leader and reduce processing time by 99% with AI. We are two technical founders: I got my PhD from MIT and, and was a former research scientist at Amazon & Flexport, where I encountered the problem firsthand. My co-founder Chris is a second-time founder and former software engineer at Amazon, Brex, and TikTok. Pax Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Penny Chen, Founder Penny is the Co-Founder and CEO of Pax AI. She has designed and built algorithms for pricing, forecasting, fulfillment, and capacity planning to optimize workflows, costs, and quality across logistics and supply chain. She has extensive experience driving projects at MIT, Flexport, and Amazon, addressing real-world problems through a mixture of AI/ML, statistics, and optimization. ### Chris Le, Founder Chris is the Co-Founder and CTO of Pax AI. Before Pax AI, Chris worked on scaling up Amazon's supply chain network where he was introduced to the logistics space. After Amazon, Chris built the TikTok E-Commerce merchant systems from 0-1 and took that learning to build Kyros, a live streaming e-commerce platform in Singapore. Most recently, Chris built the financial rewards and billing systems at Brex. ### Company Launches [### Pax AI - TurboTax for Import Duty Rebate]( TL;DR - Billions of dollars paid on import duties are eligible for return every year, but the claim process is costly and time-consuming. That’s where Pax comes in. We turn complex regulations into algorithms, so importers of all sizes can reclaim the money that's rightfully theirs effortlessly. **We can give sub $50m sales ecommerce brands 3-5% back on their sales**. Hi everyone, we’re Penny and Chris, aka the team behind [Pax]( 🧠 [Penny]( 8+ years in research, built algorithms for supply chain and logistics @ Flexport, Amazon & MIT. Chat with me about #optimization #sauna #Taiwan. 🎯 [Chris]( 6+ years in software engineering, built financial systems and supply chain solutions @ Amazon, Brex & TikTok. Chat with me about #boxing #meditation #Vancouver. Problem ------- U.S. companies spend over $100 billion annually on import taxes. The good news is that Duty Drawback—a tax refund program—lets companies reclaim that cash! Astonishingly, $10 billion (80% of eligible refunds) goes unclaimed each year. Why? The process is a real headache. Today, dealing with the government and customs brokerages takes months, as they take 10-20% of the refund and refuse to work on claims under $100k. As a result, only large enterprises file drawbacks, leaving smaller businesses out in the cold. With trade wars heating up, duty drawbacks are more important than ever—new rules like Tariff 301 include an additional 25%- 100% duty on $50 billion of Chinese goods. It’s time to make the process simple and accessible! Solution -------- Pax creates a [**TurboTax-like experience**]( requiring no duty drawback expertise. Our product uses AI to handle the heavy lifting of collecting, extracting, and validating data and maximizes claim amounts with optimization algorithms. Pax democratizes duty drawback, enabling importers of all sizes to recover money that is rightfully theirs. Using Pax, companies: * Save hundreds of hours dealing with manual data entry. * Reclaim millions of dollars spent on import duties. * Full in-suite dashboard and analytic reporting. 😀 **Ask**: If you or any companies you know import goods into the U.S. (e.g., retailers like Nike or manufacturers like Zero Motorcycles) or customs brokerages, we’d love to chat! Please reach us at [founders@getpaxai.com](mailto:founders@getpaxai.com)! #### YC Sign Photo

Cracked

cracked

https://www.cracked.so/

San Francisco, CA, USA

Playground for Movement

AI Motion Graphics Copilot

B2B

B2B

S24

Active

Early

https://www.ycombinator.com/companies/cracked

https://yc-oss.github.io/api/batches/s24/cracked.json

Title: Cracked: AI Motion Graphics Copilot | Y Combinator URL Source: Markdown Content: ### AI Motion Graphics Copilot Playground for Movement Cracked Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Kelly Lu, Founder I care about empathetic code and design. ### Anirudh Rahul, Founder Hey I'm Ani I just graduated from MIT. I've worked on high performance trading systems at JaneStreet and FiveRings, and have done ML work at Bytedance. ### Company Launches [### 💥 Cracked — Motion Graphics Copilot]( [ **Problem** ----------- It’s well known that Adobe AfterEffects and similar platforms are notoriously painful to use. Only a handful of individuals have mastered the motion graphics techniques required to make even simple animations. In fact, in media and entertainment, motion graphics are often the bottleneck to going live. **Solution** ------------ Cracked lets anyone create animations with intuitive text prompts. Our goal is to make motion graphics truly accessible through promptable animation generation. We’re focused on building a motion graphics copilot that not only helps generate ideas, but also brings them to life. **We’re starting off by helping folks create stunning launch videos. Email** [founders@cracked.so](mailto:founders@cracked.so) **to get started!** **Team** -------- We met while studying CS at MIT, where we ran HackMIT, the largest undergraduate hackathon in the US. [**Ani**]( High-performance trading systems at Jane Street and Five Rings. SWE at Tiktok. Computer Vision Research at MIT CSAIL. Bootstrapped a Video Streaming Platform [**Kelly**]( Infra at Discord. Quant trading at Virtu. Unsupervised line art generation at MIT CSAIL. Computational design at MIT Media Lab. Presidential Scholar of the Arts Semifinalist in Design. **Ask** ------- We just launched on [Product Hunt]( We would really appreciate your support! If you’re interested in creating animated graphics for your business, or a video for your upcoming launch, shoot over an email — [founders](mailto:founders@cracked.so)[@cracked.so](mailto:kellylu@cracked.so). Kelly ### Other Company Launches ### 🥚Overeasy – Go from idea to CV model 100x faster Overeasy lets you build task specific CV models from unstructured image data. [Read Launch ›](

Focus Buddy

focus-buddy

https://www.focusbuddy.ai/?ref=yc

San Francisco, CA, USA

Reach out to us at founders@focusbuddy.ai Focus buddy is an AI productivity coach that stays on calls with you and help you accomplish your important work goals on a daily basis, even when you are struggling to focus. We noticed that our users develop a productive relationship with Focus Buddy. Users stay on calls for multiple hours everyday where they depend on Focus Buddy to: • Avoid procrastination and get started: Address hidden anxieties, embrace imperfection, chunk tasks, kickstart with mini-goals, and use regular check-ins to maintain momentum. • Recover from distractions and stay focused: Focus Buddy detects when they are working on less important tasks or scrolling on social media, help them overcome the underlying concerns feeding the distraction, and help them get back to the important task • Manage stress and Prevent Burnout: Focus Buddy detects stress buildup, integrates mindfulness habits to the workflow, helps take short rejuvenating breaks, and stay composed. Our Initial ICP is people with ADHD who are highly motivated but also highly blocked by internal and environmental factors. In the future, we believe each worker should have their own personal coach that enforces proven productivity techniques in real time to help them extract more focused hours every day with the same effort.

AI Productivity Coach: Get work done when you are struggling to focus

Consumer

Consumer -> Content

S24

Active

Early

https://www.ycombinator.com/companies/focus-buddy

https://yc-oss.github.io/api/batches/s24/focus-buddy.json

Title: Focus Buddy: AI Productivity Coach: Get work done when you are struggling to focus | Y Combinator URL Source: Markdown Content: Focus Buddy: AI Productivity Coach: Get work done when you are struggling to focus | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( Buddy Focus Buddy =========== AI Productivity Coach: Get work done when you are struggling to focus [S24]( Active [artificial-intelligence]( Francisco]( * * * [Company]( [Jobs](  [ * * * ### AI Productivity Coach: Get work done when you are struggling to focus Reach out to us at founders@focusbuddy.ai Focus buddy is an AI productivity coach that stays on calls with you and help you accomplish your important work goals on a daily basis, even when you are struggling to focus. We noticed that our users develop a productive relationship with Focus Buddy. Users stay on calls for multiple hours everyday where they depend on Focus Buddy to: • Avoid procrastination and get started: Address hidden anxieties, embrace imperfection, chunk tasks, kickstart with mini-goals, and use regular check-ins to maintain momentum. • Recover from distractions and stay focused: Focus Buddy detects when they are working on less important tasks or scrolling on social media, help them overcome the underlying concerns feeding the distraction, and help them get back to the important task • Manage stress and Prevent Burnout: Focus Buddy detects stress buildup, integrates mindfulness habits to the workflow, helps take short rejuvenating breaks, and stay composed. Our Initial ICP is people with ADHD who are highly motivated but also highly blocked by internal and environmental factors. In the future, we believe each worker should have their own personal coach that enforces proven productivity techniques in real time to help them extract more focused hours every day with the same effort. Focus Buddy Founded:2024 Team Size:2 Location:San Francisco Group Partner:[Michael Seibel]( ### Active Founders ### Yash Ramchandani, Founder Co-Founder of Focus Buddy. Previously PM @ Google working on AI features on the Pixel phone, and Ads for stores trying to drive in-store traffic Yash Ramchandani [Focus Buddy](  []( "Twitter account") []( "LinkedIn profile") ### Adnan Sherif, Founder CEO Focus Buddy. Ex ML @ Google working on Generative AI on the Pixel Phone. Ex ML Researcher @ UC Berkeley Sky Lab Adnan Sherif [Focus Buddy](  []( "LinkedIn profile") ### Company Launches [### Focus Buddy - AI productivity coach for people with ADHD]( ### **TLDR** _Focus Buddy is an AI productivity coach that helps people with ADHD get important work done. Our users converse with the AI over a phone call for 6+ hours a week while they’re working_. ### **The Cost of ADHD** **People with ADHD consider it the BIGGEST blocker in their life and the PRIMARY cause of their poor grades, missing promotions, and getting fired.** * 17 million adults and children in the US * 2-4 more hours wasted every day compared to peers * $1,500 in medication costs every year per person ### **How Focus Buddy helps our user Jeff** Jeff is a brilliant product engineer who has ADHD. He often struggles to complete work due to his tendency to hyper-focus on details and get distracted by sudden impulses. Here is what Jeff's new workflow looks like since he started using FocusBuddy: Jeff calls Focus Buddy first thing in the morning after breakfast. They go over his to-do list together and create a schedule for his day. Jeff then begins his first task - writing a draft PRD. He explains his approach to FocusBuddy and asks for frequent check-ins to keep him on track. An hour into drafting, Jeff notices a small discrepancy in a user activity chart. His ADHD brain latches onto this detail, and he spends the next 30 minutes hyper-focusing on it, losing sight of the bigger picture. Just then, FocusBuddy speaks up: "How's it going?" Jeff explains: "He is still figuring out the details on the chart" FocusBuddy detects that Jeff has been hyper-focusing on a detail and helps Jeff realize that he is falling behind on schedule with more important parts of the PRD. Focus Buddy then works with Jeff to wrap up work on the chart discrepancy and reorganize his schedule to come back to the chart later in the day. They then do a 5-minute meditation to shift his focus away from the discrepancy and ease his mind back onto the main task. At the end of the day, FocusBuddy helps Jeff perform a daily reflection and prepare for his day tomorrow. Jeff and our other users experience multiple types of interventions by Focus Buddy every single day and attribute their new-found productivity to it. ### **Why Focus Buddy works** Today, people with ADHD spend hours every day virtually co-working on apps like Focusmate, updating to-do lists, using meditation apps like Calm, and journaling with little success. It is extremely hard to keep these apps updated, they have very little context about you and are unable to proactively provide timely support when needed. Focus Buddy is deeply integrated, is seamless to interact with, builds a lot of context over time and is able to leverage this context at critical moments to provide the necessary support. On top of that, our voice AI infrastructure is revolutionising the way humans and AI interact. we're crafting an entirely new paradigm for fluid, natural conversations that feel as intuitive as talking to another person. Here are some examples: [**Multimodal Voice + Text Conversation**]( [**Proactive AI Initiated Check-ins**]( ### **Our Team** [Adnan]( and [Yash]( have been best friends for over a decade, roommates for the last two years, and worked on the Google Pixel team as a Product Manager and ML Engineer. Yash led product and safety for Generative AI apps on the latest Pixel phone, while Adnan worked on training and deploying low-latency, resource-constrained, fully on-device Gemini models used by these apps. Adnan is a national triple jump champion, and prior to Google, he conducted AI research at UC Berkeley’s SkyLab with Ion Stoica (co-founder of Databricks), focusing on scaling graph machine learning to problems with millions of nodes. Yash has worked at startups like Kalshi and Relay, helping them from pre-launch to launch. Adnan learned to manage the ADHD symptoms he faced throughout high school and college and went on to help others cope with the same condition. **Our Asks** ============ Reach out to us at [founders@focusbuddy.ai](mailto:founders@focusbuddy.ai) to learn more and sign up on our website to try us out and give us feedback. If you know anyone with ADHD, feel free to send them our way Contact:  [founders@focusbuddy.ai](mailto:founders@focusbuddy.ai)  | Website: [ Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

AutoPallet Robotics

autopallet-robotics

https://autopallet.bot

San Francisco, CA, USA

We’re building the next generation of warehouse robotics. In the US today, retailers spend approximately $10B per year paying human laborers to pick up and move cardboard boxes in warehouses. Existing solutions for automating this are expensive and difficult to install, which is why manual operation is still so prevalent. Our solution is different. We make swarms of small mobile robots that install into existing warehouses to provide a low-cost and robust automation solution for case picking and mixed-SKU palletization. Our novel technology allows these robots to be installed and operate at significantly lower cost than existing solutions while being both flexible and robust.

We make robots that move boxes in warehouses

Industrials

Industrials -> Manufacturing and Robotics

S24

Active

Early

https://www.ycombinator.com/companies/autopallet-robotics

https://yc-oss.github.io/api/batches/s24/autopallet-robotics.json

Title: AutoPallet Robotics: We make robots that move boxes in warehouses | Y Combinator URL Source: Markdown Content: ### We make robots that move boxes in warehouses We’re building the next generation of warehouse robotics. In the US today, retailers spend approximately $10B per year paying human laborers to pick up and move cardboard boxes in warehouses. Existing solutions for automating this are expensive and difficult to install, which is why manual operation is still so prevalent. Our solution is different. We make swarms of small mobile robots that install into existing warehouses to provide a low-cost and robust automation solution for case picking and mixed-SKU palletization. Our novel technology allows these robots to be installed and operate at significantly lower cost than existing solutions while being both flexible and robust. AutoPallet Robotics Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Nathan Yee, Founder Nathan is the co-founder and CEO of AutoPallet Robotics. At 18, he graduated as the valedictorian of College of Alameda and then studied Engineering with Computing at Olin College where he met Eric. He has since built ML models for MBARI, consulted for the DIU (xView2) and WashU (drug discovery), and built core software for lab automation robotics at Trilobio. ### Eric Miller, Founder Eric is the co-founder and CTO of AutoPallet Robotics. After graduating from Olin College in 2019, he led the Subject Tracking and Autonomy Infrastructure teams at Skydio, rapidly growing from individual contributor to lead a team of 6 engineers. Eric is a multidisciplinary robotics engineer with significant experience building modern robotics stacks, from hardware and electronics through perception and high-level software. ### Company Launches [### 🤖 AutoPallet Robotics: The future of case picking in warehouses]( TL;DR ----- * AutoPallet Robotics unlocks automated case picking for existing warehouses. Our novel system delivers rapid ROI by leveraging the current infrastructure to deploy swarms of hundreds of small, agile, mobile robots. * Want to get in touch? [**connect@autopallet.bot**](mailto:connect@autopallet.bot) or [send us an inquiry]( The Team -------- **Nathan and Eric** met at Olin College of Engineering 9 years ago, where they collaborated on over 15 projects. **CEO** - [Nathan]( brings four years of experience in machine learning. In his previous position, he worked on robot software and explored heuristic-based and RL-based methods for multi-robot scheduling. **CTO** - [Eric]( has extensive experience creating hardware, electronics, and software for modern robotics systems, including five years at Skydio, founding and growing the Autonomy Infrastructure team. The Problem ----------- **Case picking for order selecting**, a critical task in the supply chain for grocery stores, retail, and restaurants, remains largely manual in U.S. warehouses. We estimate that **over 30 billion cases** are manually moved between pallets annually, resulting in labor costs exceeding **$10 billion** each year. Current automation solutions are prohibitively expensive and fall into two main categories: 1. **Build a new warehouse** with extensive conveyor belt systems, industrial robot arms, and high-density case storage. Costs range from **$100M to $350M per warehouse**. 2. **Install large mobile robots** that directly replace humans in existing warehouses at a cost of **$300k to $500k per unit**. This high capital expenditure and long ROI period make them infeasible for many businesses. Our Solution Is Fundamentally Different --------------------------------------- We've developed a way to retrofit existing warehouse infrastructure with swarms of affordable, agile robots to automate the order-selecting process. This approach eliminates the need to rebuild warehouses from scratch or invest in expensive large mobile robots. We are designing our system to: * **Meet or exceed** your current throughput—our robots work in swarms, easily picking tens of thousands of cases per shift. * Ensure **resilience** through a decentralized swarm that continues operating even if several robots fail. * Optimize **multi-stop deliveries** and create **maximally dense pallets** using an **AI-powered** pallet-building algorithm. * Deliver a typical ROI in **less than** **12 months**. How You Can Help ---------------- We’re actively seeking **partnerships and collaborations** to propel our mission forward. If you or anyone in your network is interested in exploring opportunities or learning more, we’d love to connect! We’re especially interested in engaging with: * Retailers and 3PLs operating distribution centers * Grocery and Broadline Foodservice Distributors If this resonates with you or someone you know, please don’t hesitate to reach out! [**connect@autopallet.bot**](mailto:connect@autopallet.bot) or [send us an inquiry]( ### Hear from the founders #### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?) Eric and Nathan met at Olin College, where they worked on 15 group projects together.

AminoAnalytica

aminoanalytica

https://www.aminoanalytica.com

San Francisco, CA, USA

Creating new functional proteins, such as industrial enzymes or therapeutic peptides, has traditionally been an inefficient and costly ‘trial-and-error’ process. Biotech companies painstakingly make random mutations of existing proteins, test them, and repeat this cycle until success. AI ‘de-novo’ protein design promised a breakthrough by generating entirely new proteins from scratch. However, it severely falls short due to a lack of comprehensive data, resulting in poor accuracies that make it unfit for industrial use. At AminoAnalytica, we offer a new approach: accelerated adaptation. Our AI software rapidly predicts protein properties in silico, eliminating the need for thousands of lab tests. This enables us to enhance existing proteins for better industrial performance, transforming the traditional ‘trial-and-error’ method into an ultra-high throughput and intelligent process.

AI for enhanced functional proteins

Healthcare

Healthcare -> Industrial Bio

S24

Active

Early

https://www.ycombinator.com/companies/aminoanalytica

https://yc-oss.github.io/api/batches/s24/aminoanalytica.json

Title: AminoAnalytica: AI designed enzymes for health and nutrition | Y Combinator URL Source: Markdown Content: ### AI designed enzymes for health and nutrition Creating new functional proteins, like enzymes or therapeutic peptides, has traditionally been an inefficient, costly trial-and-error process. Biotech companies repeatedly mutate and test proteins, hoping for success. Generalist AI protein models, like AlphaFold3 and ESM3, are built work across all fields but lack the precision needed for industrial applications. At AminoAnalytica, we build tailored models for specific tasks. This approach eliminates the need for thousands of wet lab experiments, speeding up breakthroughs in areas like drug development and industrial enzymes—without sacrificing accuracy. AminoAnalytica Founded:2024 Team Size:3 Location:San Francisco ### Active Founders ### Abhi Rajendran, CEO & Co-founder I previously worked at the Mercedes Formula 1 Team and now work at the intersection of AI and Protein Design - there's a funny story in there somewhere. ### Matteo Peluso, Founder Compute credits are all you need ### Adam Wu, Founder Recent engineering graduate from Imperial College London. Worked in product design, manufacturing, and industrial labs. Shameless plug: check out 'adwuu' on spotify for a good time ### Company Launches [### 🧬 AminoAnalytica – Next generation proteins engineered with \*protein\* language models]( Hey everyone – it’s [Abhi Rajendran]( [Adam Wu]( and [Matteo Peluso]( **Tl;dr**: just look at the pictures ;) **💞 The A(mino) Team** ----------------------- 👨🏾 **Abhi Rajendran** – From Imperial College London to the Mercedes F1 Team, Abhi builds AI tools in data-intensive environments. AminoAnalytica was inspired by his computational bio master’s project and was the top AI x Robotics venture from Imperial in 2024. 👦🏻 **Adam Wu** – With experience in academic and industry wet labs, Adam is now building his own. He has a background in materials science, tissue engineering and biosensing as a Thermo Fisher Scholar from Imperial. 👱🏼‍♂️ **Matteo Peluso** – Bioinformatics PhD from the University of Zurich. His skills in biology, machine learning, and software development tie up everything seamlessly. 👨🏻‍🦱 **Dr. Stefano Angioletti-Uberti** – Senior lecturer at Imperial, specializing in modeling biological and soft matter systems. He ensures models are based on the latest scientific principles. **❌ Problem: better proteins are needed to accelerate global innovation** ------------------------------------------------------------------------- * Industrial and pharma companies prefer to use enzymes and peptides over harsh chemicals as they are more specific and sustainable. * However, natural proteins often lack stability, efficiency, or specificity for their desired applications leading to poor performance * Improving these proteins has been a costly and inefficient 'trial-and-error' process, where biotech companies randomly mutate existing proteins, test them, and repeat until success. **✅ Solution: AminoAnalytica’s protein adaptation platform, powered by PLMs** ----------------------------------------------------------------------------- * Like how ChatGPT understands human language, our **"protein language models" (PLMs)** understand biology and can optimize proteins for industrial and therapeutic use. * This allows us to perform in-silico protein property prediction, eliminating the need for thousands of lab tests. * We’re transforming the traditional ‘trial-and-error’ method into an ultra-high throughput and rational process. **🤝 Any industry working with proteins can benefit from our tech** ------------------------------------------------------------------- Currently, we’re working on: * **Aquaculture feed** → enzymes for maximizing fish feed nutritional efficiency * **Pharmaceuticals** → peptide drugs with improved stability and specificity * **Climate tech** → enzymes for eco-friendly carbon capture * **Consumer goods** → safer enzymes for everyday products **🐡 Get in touch with us!** ---------------------------- * Upvote/share this post with your network and help spread the word! * If you (or anyone in your network) are as excited as we are about next generation industrial proteins and would like to learn more about what we’re doing, email us here - [founders@aminoanalytica.app](mailto:founders@aminoanalytica.app) * We’re also looking to expand **our advisory board** in the areas of aquaculture, fish testing, and feed manufacturing!

Ångström AI

angstrom-ai

https://www.angstrom-ai.com

San Francisco, CA, USA

We build GenAI-based molecular simulations to substitute wet lab experiments in the drug development pipeline. Our Biotech/Pharma clients can verify the efficacy and safety of new drug candidates using our computer simulations, which match the accuracy of wet lab experiments but are faster. Our AI models do not require training data, the limiting factor in ML for bio. They learn directly from the equations of physics. Furthermore, our simulations obey the laws of physics, avoiding the hallucinations seen in other GenAI technologies (e.g., generating an image of a person with six fingers.) Since joining YC, Angstrom AI has developed the first physically accurate AI-based simulation of multiple molecules interacting. We have published the first molecule water solubility results with accuracy within the error range of wet lab experiments.

Fast Gen AI molecular simulations that reproduce wetlab results

Healthcare

Healthcare -> Drug Discovery and Delivery

S24

Active

Early

https://www.ycombinator.com/companies/angstrom-ai

https://yc-oss.github.io/api/batches/s24/angstrom-ai.json

Title: Ångström AI: Gen AI molecular simulations that reproduce wetlab results | Y Combinator URL Source: Markdown Content: ### Gen AI molecular simulations that reproduce wetlab results Angstrom AI builds GenAI-based molecular simulations to substitute wet lab experiments in the pre-clinical drug development pipeline. We are a team of 2 PhD's and 2 Professors from the University of Cambridge who decided to start a company together after we realised how to combine breakthoughs in our research in quantum-accurate models of physics and generative AI models. Our Biotech/Pharma clients can verify the efficacy and safety of new drug candidates using our computer simulations, which match the accuracy of wet lab experiments, but are over 100x faster. We achieve this accuracy by constraining our genAI-based simulations to obey the laws of physics, avoiding the hallucinations seen in other GenAI technologies. Since joining YC, Angstrom AI has developed the first physically accurate gen-AI based simulation of multiple molecules interacting. We have published the first molecule water solubility results with accuracy within the error range of wet lab experiments. We have also kicked-off a 150K pilot project with a pharma company to apply our tech to estimating solubility in their drug development pipeline. Ångström AI Founded:2024 Team Size:5 Location:San Francisco ### Active Founders ### Javier Antoran, Founder Co-founder of Ångström AI, accelerating drug discovery+ development by substituting wet lab experiments with GenAI molecular simulations. My background is in probabilistic modeling and machine learning research (PhD University of Cambridge) with experience as a researcher at Google, Microsoft, and in Quant Finance. I am interested in meeting fellow founders or other people from the industry - reach out if you want to grab a virtual coffee! ### Jose Miguel Hernandez Lobato, Founder Miguel is co-founder of Ångström AI and Professor of Machine Learning at the Department of Engineering, University of Cambridge, UK. He has nearly 20 years of research experience in Machine Learning and his work has been cited over 15,000 times. His research in Machine Learning for Molecules has led him to build strong relationships with partners in BioTech and Pharma. Before joining Cambridge as a faculty, he was a postdoctoral fellow at Harvard University. ### Laurence Midgley, Founder I'm the co-founder of Ångström AI which substitutes wet lab experiments with physically accurate GenAI molecular simulations for clients in Pharma and BioTech. Before founding Ångström AI, I was a research engineer at InstaDeep (acquired by BioNTech 2023), and pursued a PhD at the University of Cambridge in generative AI models for molecular systems. I love coding and surfing, reach out if you are in the Bay Area and want to catch some waves. ### Company Launches [### Ångström AI: Gen AI molecular simulations]( * * * **TLDR:** **We build fast and experimentally accurate generative AI-based simulations of molecular interactions for pharma and biotech companies.** These simulations can tell us whether a drug is going to bind to a protein or how quickly a drug will act once it is consumed by a patient. * * * Our Team -------- We are a team from the University of Cambridge with 30+ years of combined experience in AI and Molecular Modelling, including: * [Javier]( who scaled probabilistic AI methods 1000x during his PhD, turned down a research scientist position in Big Tech to start Angstrom AI. * [Laurence]( who developed FAB, a method for training AIs from physical equations without training data, during his PhD and was a researcher at InstaDeep before its acquisition by BioNTech in 2023. * [Miguel]( Javier and Laurence's PhD supervisor, author of foundational research on AI for drug discovery and generative modeling. * [Gabor]( who developed MACE, a state of the art quantum mechanically accurate force field. Miguel and Gabor's work has been cited over 40k times. The Problem ----------- During drug discovery and development, pharmaceutical companies need to understand how drug molecules interact with other molecules in the human body to determine the drugs’ efficacy and safety. Conventional methods to assess molecular interactions are unsatisfactory: * Wet lab experiments are accurate but slow and expensive. * Machine learning prediction methods, like AlphaFold, are fast but inaccurate. They are limited by the quality and quantity of training data, which must be generated by lab experiments. * Molecular Dynamics simulates interactions by rolling out the equations of physics, offering a balance between wet lab and machine learning predictions in accuracy and speed. These factors depend on the model of physics used. More accurate models are more expensive to run. This makes the method compute bottlenecked rather than data bottlenecked. Here is a video of a simulation of 64 water molecules. [ Solution: Fast and Accurate Molecular Simulations ------------------------------------------------- We run molecular simulations, keeping us in the compute constrained regime, but we combine **1) quantum mechanically accurate models of physics 2) generative AI that allows us to run these models quickly.** 1. We use the MACE (multi-atomic cluster expansion) physics model, which accurately reproduces quantum-mechanical interactions. It was developed by Gabor, our co-founder. In collaboration with our academic partners, we recently showed MACE simulations are the **first ever to provide accuracy comparable to lab experiments** when estimating the hydration-free energies (a quantity relevant to drug bioavailability). Below is a plot from the [resulting publication]( However, MACE is computationally expensive, each of the results from the below plot required 1 week of compute on 8 A100 GPUs. 2. We use diffusion models to accelerate MACE simulations, making them computationally affordable. Our models generate states **consistent with physics, but the transitions between states are non-physical and significantly faster.** Here is a video of our AI simulating the same water box as above. [ Demos! ------ Here are a couple of examples to show off the type of stuff you can do with our generative models. ### Speeding up Supercool Water Supercool water—liquid water below freezing, here at -40°C—is notoriously difficult to simulate with traditional methods because cold molecules move slower. The plot below shows the correlation between water molecule orientations across simulation steps. **Our AI introduces about 10,000 times more information per step compared to traditional simulations.** ### Hydrating Methane Modeling interactions between molecules and water allows us to calculate how quickly the molecules will dissolve and their bioavailability as drugs. Here are videos of a traditional simulation of a methane molecule interacting with water and our AI simulation. **Our AI prioritizes the movement of the methane molecule and its surrounding water, which are the parts that matter for solubility and bioavailability calculations.** [ [ These are the first ever **genAI accelerated, physically accurate molecular dynamics simulations** incorporating the interaction of many molecules. We are scaling up - so stay tuned! Our Ask ------- Reach out to [info@angstrom-ai.com](mailto:info@angstrom-ai.com) if * You are in pharma or biotech and interested in learning about the theory of diffusion models and quantum-mechanically accurate models of atomic interactions. We would be happy to give a talk on our research or have a more informal chat over Zoom. * You have friends who work in pharma or biotech and are interested in computational methods. We would love to meet them! #### YC Sign Photo

Unbound Security

unbound-security

https://www.unboundsecurity.ai/

San Francisco, CA, USA

Secure Gen AI apps for the modern enterprise

B2B

B2B -> Security

S24

Active

Early

https://www.ycombinator.com/companies/unbound-security

https://yc-oss.github.io/api/batches/s24/unbound-security.json

Title: Unbound Security: Allow employees to use AI tools without fear of data loss | Y Combinator URL Source: Markdown Content: ### Allow employees to use AI tools without fear of data loss Unbound Security Founded:2023 Team Size:4 Location:San Francisco ### Active Founders ### Rajaram Srinivasan, Founder Building data security for Gen AI. Prev: Palo Alto Networks, Adobe | MIT Alum ### Vignesh Subbiah, Founder Cofounder at UnboundSecurity. Building cyber security for gen AI apps. Previously engineering at Shogun, Tophatter, and Adobe Systems. ### Company Launches [### 🚀 Unbound Security - Secure Gen AI apps for enterprise]( ### TL;DR [Unbound Security]( prevents leakage of sensitive information when employees use Gen AI applications. For example, we intervene and stop when someone pastes a code snippet that contains a secret key into ChatGPT while troubleshooting. The problem ----------- 1. **AI faces enterprise adoption roadblocks**: Despite Gen AI boosting productivity, many enterprises remain wary. Even in 2024, over 1 in 4 organizations have banned all AI apps, keeping them off-limits to employees. 2. **AI app sprawl:** There are now well over 1,000 Gen AI apps, and many have questionable security practices. These cool “tools” continue to worry CSOs (Chief Security Officers) as employees are already using many of these to get work done. 3. **Data privacy remains a top concern**: Over 55% of all prompts contain some form of Personally Identifiable Information (PII). This is not only a privacy nightmare, but also pushes enterprises out of compliance with multiple regulations such as PCI, SOX and HIPAA. Our solution ------------ 1. **AI app discovery:** We discover and catalog all AI apps in use by employees and help security teams understand the risk levels of each of these apps. 2. **Granular application access policies:** Rather than block all apps by default, we allow enterprises to allow some trustworthy AI apps and steer users towards those. For example, if your org invested in Chat GPT enterprise, we help get the most out of that investment by encouraging people to use that instead of a random cool file summarizer on the internet. 3. **Protect data leakage:** On the allowed AI apps, Unbound monitors all prompts and also blocks users from sharing sensitive information based on the configured AI usage policy. Our ask and offer ----------------- 1. If you know a company that has blocked the usage of AI apps, we can help your friends use these apps with IT consent. Please drop us a note at [founders@unboundsecurity.ai](mailto:founders@unboundsecurity.ai). 2. If you’d like to understand what people are using AI for within your org, and stay compliant, we are happy to offer our AI visibility platform for free to any YC company. Let’s [chat more over a meeting.]( The team -------- [Vignesh]( and [Raj]( worked together at Adobe on the same Engineering team for 5+ years, solving some of the most complex problems in the digital advertising space - The team built sub-millisecond latency systems that processed billions of advertising artifacts. Vignesh went on to be founding engineer at Tophatter and an early engineer at [Shogun (YC S18)]( Raj has built data security products for Palo Alto Networks and Imperva prior to Unbound where he observed the struggles of data security programs in large enterprises.

Weave Robotics

weave-robotics

https://www.weaverobots.com

San Francisco, CA, USA

Making the world’s first personal robot that's built for the home. Our robot, Isaac, will autonomously tidy up endless messes, fold laundry, and care for your home while you’re away, and we’re shipping our first 30 in the fall of 2025.

Personal robots for the home--that ship in 2025

Industrials

Industrials -> Manufacturing and Robotics

S24

Active

Early

https://www.ycombinator.com/companies/weave-robotics

https://yc-oss.github.io/api/batches/s24/weave-robotics.json

Title: Weave Robotics: Personal robots for the home--that ship in 2025 | Y Combinator URL Source: Markdown Content: ### Personal robots for the home--that ship in 2025 Making the world’s first personal robot that's built for the home. Our robot, Isaac, will autonomously tidy up endless messes, fold laundry, and care for your home while you’re away, and we’re shipping our first 30 in fall of 2025. Weave Robotics Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Evan Wineland, Founder Co-founder of Weave Robotics (S24) | Former Lead AI PM at Apple ### Kaan Dogrusoz, Founder Co-founder of Weave Robotics (S24) | Former research lead in Apple ### Company Launches [### Weave - Making the first personal robot built for the home]( We’re [Evan]( and [Kaan]( the team behind [Weave]( and [Isaac]( **What’s the problem?** ----------------------- The average American spends 3.5 years of their life on housework (cleaning, maintenance, laundry) that they don’t want to do.¹ Our customers (and everyone else we’ve spoken to) want to reclaim that time for themselves and their loved ones. Robots that automate this mundane, repetitive work won’t just finally mean that we’re living like the Jetsons; they’ll mean people get months or years of their lives back. In order to do much of that work, they have to have a general-purpose design; they have to be capable (i.e., of manipulation across a long tail of tasks), and they have to be safe. **We’re building Isaac to help** -------------------------------- [Weave’s]( first robot, Isaac, is the first and only personal robot that meets these requirements for the home and is shipping soon. Isaac will tidy up endless messes, fold laundry, and care for your home while you’re away, and we’re shipping in the fall of 2025. Isaac acts autonomously when it’s given a voice or text command, or in response to an automation that’s programmed in our app.  When Isaac isn't needed, its camera folds and turns off, its torso lowers, and it stows in the enclosure that's included with every order. And with Remote Op, users can request that Weave remotely operate their Isaac for a task it can't yet do autonomously. _Collecting data with our first prototype_ **What we’ve already built** ---------------------------- In two months, we’ve already: * assembled our first data collection system and prototype * trained Isaac's planner and VLA, combined them with a VLM in our ML pipeline * had Isaac autonomously complete its first tasks * got our first reservations for Isaac **The team** ------------ [Evan]( and [Kaan]( are best friends and roommates dating back to 2015 and their time at Carnegie Mellon. They're both Apple veterans: Evan most recently was a Lead AI PM who worked on Next-Gen Siri (Apple Intelligence). Before that, he shipped private, large-scale knowledge graphs for on-device personalization and marquee features like Communication Safety (child safety) and Focus modes. Kaan most recently was a manager in ML Robotics research, and before that, he was a staff ML researcher who shipped Double Tap on the Apple Watch and a lead embedded engineer on the iPhone who spent way too many weeks in factories debugging prototype hardware. ### **Our asks** If you know anyone who would be interested in having their own Isaac, have them check out our [website]( where they can now reserve one directly!  Each Isaac costs $1000 to reserve and nothing more until we deliver in the fall of 2025. We’re also happy to talk to interested folks in more detail; reach us at [founders@weaverobots.com](mailto:founders@weaverobots.com). ¹ [

Genie

genie

http://www.genie.gg

Lake Oswego, OR, USA; Remote

Genie unlocks a new level of personalized play that's never been possible before.
 More than 10k kids have made friends with Genie in our iOS app, and our most engaged kids spend 2hrs a day creating adventurous stories, playing games and having fun talking to their AI friend... always in a safe & age appropriate way.

Conversational AI Sidekick for Kids.

Consumer

Consumer -> Social

S24

Active

Early

https://www.ycombinator.com/companies/genie

https://yc-oss.github.io/api/batches/s24/genie.json

Title: Genie: Conversational AI Sidekick for Kids. | Y Combinator URL Source: Markdown Content: Genie: Conversational AI Sidekick for Kids. | Y Combinator =============== []( "Y Combinator") [About]( [What Happens at YC?]( Interview Guide]( Blog]( [Companies]( [Startup Directory]( Companies]( Directory]( YC]( [Startup Jobs]( [All Jobs]( Engineering]( Operations]( Marketing]( Sales]( Internship Program 2024]( Job Guide]( Coaching]( Startup Jobs Blog]( [Find a Co-Founder]( [Library]( [SAFE]( [Resources]( [Startup School]( Investors]( News]( Open main menu Apply for **W2025** batch.[Apply]( "Apply for W2025 batch.") [Home]( Genie ===== Conversational AI Sidekick for Kids. [S24]( Active [artificial-intelligence]( * * * [Company]( [Jobs](  [ * * * ### Conversational AI Sidekick for Kids. Genie unlocks a new level of personalized play that's never been possible before.
 More than 10k kids have made friends with Genie in our iOS app, and our most engaged kids spend 2hrs a day creating adventurous stories, playing games and having fun talking to their AI friend... always in a safe & age appropriate way. Genie Founded:2023 Team Size:4 Location:Lake Oswego, OR Group Partner:[Garry Tan](  []( "LinkedIn profile") []( "Twitter account") []( "Facebook profile") ### Active Founders ### Darius "Bubs" Monsef, Founder Founder/CEO, Genie.gg Past: Founder/CEO BraveCare.com, CreativeMarket.com & COLOURlovers.com Darius "Bubs" Monsef [Genie](  []( "Twitter account") []( "LinkedIn profile") ### Asa Miller, Founder Maker, builder and designer in the PNW. Asa Miller [Genie](  []( "LinkedIn profile") ### Company Launches [### Genie — The best AI sidekick for kids]( Hi, we’re Darius and Asa. We're friends, dads, go-karting rivals, and the cofounders of [Genie]( — the best AI sidekick for kids. Genie is a conversational AI that encourages creative play and guides kids through the Genieverse, the future of games, media, and social for kids. **Download our app at:** [** Visit us at: [ **The Genie Team** [Asa]( and [Darius]( previously cofounded [BraveCare.com]( (YC S19), which raised $40M in funding and enabled more than 50k urgent care visits for kids who were sick or injured— during the pandemic and the recovery years— all while delivering a care experience that maintained a nearly 5-Star score across thousands of reviews. Darius’ first time through YC was in W10 with [CreativeMarket.com,]( which led to an acquisition by Autodesk in ’14. He also cofounded Sightbox, a DTC contact lens service that was acquired by Johnson & Johnson in ’17. **Our vision for a better internet for kids** As a father, I want to protect my kids at all times and everywhere they go in the world, and in reality, I can’t. But I can build an AI that keeps them safe everywhere they go online and create a “digital Disneyland” for them to play, explore, and connect in. Like Jarvis to Ironman, Sox to Buzz Lightyear, or Baymax to Hiro, a child is the hero of their own story, and we’re building them the ultimate sidekick. An AI buddy that has their back in the online world, encourages creative play and helps them learn about anything, at any time, in an age-appropriate way. Soon, hundreds of millions of kids across the globe will connect on the next platform that’s foundationally powered by AI. We’ve seen it coming for a while, and we’re already building that new space… the Genieverse! **Do something fun with Genie today** **Create** Genie is an always-kind, supportive & friendly AI agent that can co-create free-form generative art with kids, and they can create thru other art modes like the “Crazy Food Lab” or “Muppet Monsters.” **Play** Genie can also build incredibly imaginative story worlds where kids decide what happens next or play logic puzzles or word games designed to spark kids’ creative and critical thinking. Genie also knows that kids should have time off of their screens and be active out in the world. When there is available screen time, we built Genie to be engaging and creative. **Learn** The internet is an incredible wealth of knowledge and information, but browsers are binary about whether a kid has access to everything… or nothing. Genie is a safe resource for kids who are curious about the world around them. Sometimes a trusted adult isn’t available to ask, or kids feel weird about asking, so Genie makes sure that tricky questions are answered in kind and age-appropriate ways. **Find “**[**Genie.gg**]( on the App Store** or click here: [** #### Company Photo Footer ------ [Y Combinator]( "Y Combinator") ### Programs * [YC Program]( * [Startup School]( * [Work at a Startup]( * [Co-Founder Matching]( ### Company * [YC Blog]( * [Contact]( * [Press]( * [People]( * [Careers]( * [Privacy Policy]( * [Notice at Collection]( * [Security]( * [Terms of Use]( ### Resources * [Startup Directory]( * [Startup Library]( * [Investors]( * [SAFE]( * [Hacker News]( * [Launch YC]( * [YC Deals]( ### Make something people want. [Apply]( [Twitter]( © 2024 Y Combinator

stormy.ai

stormy-ai

https://stormy.ai

San Francisco, CA, USA

Stormy is an AI that knows everything that's happening on your computer screen as context. It learns from everything you do during your workday, helps you stay productive and automates boring parts of your job.

AI layer on top of MacOS that knows you on an unparalleled level

Consumer

Consumer

S24

Active

Early

https://www.ycombinator.com/companies/stormy-ai

https://yc-oss.github.io/api/batches/s24/stormy-ai.json

Title: stormy.ai: AI layer on top of MacOS that knows you on an unparalleled level | Y Combinator URL Source: Markdown Content: ### AI layer on top of MacOS that knows you on an unparalleled level Stormy is an AI that knows everything that's happening on your computer screen as context. It learns from everything you do during your workday, helps you stay productive and automates boring parts of your job. stormy.ai Founded:2024 Team Size:2 Location:San Francisco ### Active Founders ### Robert Lukoshka, Founder Building new paradigm of local context collection for AI. ### Alex Pokras, Founder Building an AI layer on top of your OS that knows you on an unparalleled level. Previous nonprofit AI startup: 150+ members, $200k+ ARR. Ex-MIT.

Overstand Labs

overstand-labs

https://overstandlabs.com

Imagine that your company had an extremely knowledgeable employee who’d been at your company since its inception. This employee would have perfect awareness of all of the product features and workflows, and they know all of your customers. They’ve attended every meeting with every customer and read every single support ticket. They’ve read every word of product documentation and listened to every meeting in which any use case for your products have been described. Senta and Mihir are building Overstand: the AI manifestation of this omniscient employee. With Overstand, no revenue is left on the table due to “not knowing” about an opportunity. Overstand is able to match any expressed customer interest to its entire product understanding, ensuring that opportunities for upsell or cross-sell are clearly identified and surfaced to those responsible for account expansion. If you are trying to upsell your existing customer accounts, email founders@overstandlabs.com to schedule a demo.

The cross-selling engine for enterprise software companies

B2B

B2B -> Sales

S24

Active

Early

https://www.ycombinator.com/companies/overstand-labs

https://yc-oss.github.io/api/batches/s24/overstand-labs.json

Title: Overstand Labs: The cross-selling engine for enterprise software companies | Y Combinator URL Source: Markdown Content: ### The cross-selling engine for enterprise software companies Imagine that your company had an extremely knowledgeable employee who’d been at your company since its inception. This employee would have perfect awareness of all of the product features and workflows, and they know all of your customers. They’ve attended every meeting with every customer and read every single support ticket. They’ve read every word of product documentation and listened to every meeting in which any use case for your products have been described. Senta and Mihir are building Overstand: the AI manifestation of this omniscient employee. With Overstand, no revenue is left on the table due to “not knowing” about an opportunity. Overstand is able to match any expressed customer interest to its entire product understanding, ensuring that opportunities for upsell or cross-sell are clearly identified and surfaced to those responsible for account expansion. If you are trying to upsell your existing customer accounts, email founders@overstandlabs.com to schedule a demo. Overstand Labs Founded:2024 Team Size:2 Location: ### Active Founders ### Senta Knuth, Founder Co-founder at Overstand Labs. Ex-Oliver Wyman, ex-Palantir. ### Mihir Patil, Founder Co-founder of Overstand Labs. California Native. Ex-Palantir. Faculty @ NYU. Go Bears! ### Company Launches [### Overstand - The platform for upselling your enterprise accounts]( **TLDR**: [Overstand]( helps enterprise software teams maximize revenue by reading all customer communication channels (chat, email, call recordings, support tickets) to uncover opportunities for contract expansion. **The problem:** Big tech companies know that one of the best ways to increase revenue is to bring more value to existing customers. But customer account management involves not just sales, but also support, customer success, implementation teams, and so on. Customers might voice problems that are not conveyed in a timely manner (or at all!) to those responsible for expanding the account. Enterprise software companies are leaving a lot of potential revenue on the table— some offer a whole menu of products, with each enterprise customer only taking advantage of one or a few of the offerings. **The solution:** Overstand is designed to read all customer communications and flag opportunities for expansion of customer accounts. It identifies hidden expansion opportunities that are buried in customer communications by analyzing every single message and comparing it to product docs and even existing use cases at other enterprise accounts. **The team:** We met at Palantir several years ago and both recognized the importance of empowering customer-facing teams to fully understand and sell highly technical and complex products. [Mihir]( was a PM and engineering lead at Palantir and often felt that many existing customers could have further benefited from using his products. [Senta]( managed customer accounts valued in the double-digit millions and often observed challenges associated with upselling into existing accounts. **Asks:** If you’re interested in cross-selling and upselling as a strategy for growing your enterprise account revenue, we’d love to chat! Email us at [founders@overstandlabs.com](mailto:founders@overstandlabs.com). Follow us [on LinkedIn](

Melty