Welcome to Brief.AI

Brief.AI is an innovative platform tailored to hedge funds and investment banks, revolutionizing insights into earnings calls by harnessing large language models. ![WhatsApp Image 2023-11-29 at 12 05 35_2fe266a9](https://github.com/brief-ai-uchicago/About-Us/assets/105491876/ddc5078f-288f-410c-baf8-baca3509c69e)

๐Ÿค” Who is Brief.AI?

Our platform aims to be the voice for any executive or analyst on the buy side or sell-side trying to analyze earning call transcripts through two products: ๐Ÿ’ฌ **[Javi - Question Answering over Earnings Call Transcript](https://github.com/brief-ai-uchicago/Javi-The-Earnings-Call-Expert)** * The intelligent chatbot can engage in real-time queries regarding specific details from earnings call transcripts. This elevates user experience, ensuring immediate access to critical information without manual data trawling. ๐Ÿ“ƒ **[Long-Short - KPI Extractor](https://github.com/brief-ai-uchicago/LongShort)** * This model efficiently extracts crucial performance indicators and financial metrics from a comprehensive collection of earnings call transcripts. ![image](https://github.com/brief-ai-uchicago/About-Us/assets/105491876/416c81f6-dc1a-42ab-9908-cadfde8a77c9)

๐Ÿš€ What can this help with?

๐Ÿ’ฌ **[Chatbot for Earnings Calls:](https://github.com/brief-ai-uchicago/Javi-The-Earnings-Call-Expert)** Our chatbot amplifies the functionality of large language models, empowering users to engage in interactive conversations with earnings calls. This versatile tool serves multiple purposes, such as: - ๐Ÿค– *Comparison across multiple documents* - The chatbot uses an agent to compare queries that retrieves multiple documents and is able to create a chain of thought reasoning chain to answer queries. - ๐Ÿง  *Memory:* - Memory refers to persisting state between calls of a large language model. You can continue to ask follow-up questions from initial queries without restating the context. - โšก *Punctual Information:* - The chatbot provides quick and precise responses to specific questions, making it ideal for extracting timely information from earnings calls. - ๐Ÿšจ *Sentiment Analysis:* - Users can gauge the sentiment and emotional tone of earnings calls, helping them make more informed investment decisions. ๐Ÿ“ƒ **[Detailed Earnings Calls Analysis:](https://github.com/brief-ai-uchicago/LongShort)** - ๐Ÿ“š Concise answers - Utilizing cutting-edge language models, our system delivers succinct, structured answers extracted from verbose earnings call transcripts, streamlining the distillation of key performance indicators (KPIs) for analysts and executives. - ๐Ÿง Effective KPI extraction from long transcripts - Extracting data from unstructured sources like PDFs has become crucial for businesses, researchers, and individuals. Traditional manual methods are slow and error-prone, necessitating more efficient alternatives. For more detailed information on these capabilities and concepts, please refer to our comprehensive productย documentation.

๐Ÿ“– Documentation

For a complete guide to the documentation, please follow the steps outlined below to navigate through the GitHub organization: * [Javi-The-Earnings-Call-Expert](https://github.com/brief-ai-uchicago/Javi-The-Earnings-Call-Expert): Chatbot powered by langchain. * [LongShort-Dataset](https://github.com/brief-ai-uchicago/LongShort-Dataset): This is the dataset utilized for fine-tuning. * [LongShort](https://github.com/brief-ai-uchicago/LongShort): Fine-tuned models designed for KPI (Key Performance Indicators) extraction from earnings call transcripts. * [Website](https://github.com/brief-ai-uchicago/Brief-AI): Platform's UI/UX. * [Branding](https://github.com/brief-ai-uchicago/Branding): Repository containing branding documentation and assets. ##

๐Ÿš€ Your Next Stop

* [Github](https://github.com/brief-ai-uchicago/About-Us): Github organization page.