Launch HN: Lumona (YC W24) – Product search based on Reddit and YouTube reviews
Hey HN! We are Lumona (https://lumona.ai), a product search engine that recommends products based on what people on social media—Reddit and YouTube, for now—are saying about them.

Rather than going through SEO-filled Google results or adding site:reddit.com to your search, we explain what makes a good product, show you the best products, and back it up with Reddit and YouTube reviews about the product. We’re starting with skincare products (more on that below) and plan to expand from there.

Here’s a demo: https://www.youtube.com/watch?v=C4kKjW2YkZ4&lc=Ugzl94GP9SDBO...

We started off with skincare because, growing up, we struggled with acne but had no clue what skincare products could actually help us. Going down the rabbit hole of endlessly scrolling r/SkincareAddiction and watching countless hours of videos about cystic acne was not fun.

Lumona’s skincare search index was built by first scraping the internet for listings of skincare products, along with their ingredient lists, through a combination of SERP, Amazon’s API, and web page crawling. We then use a fine-tuned Mistral LLM to parse through a large number of Reddit threads and YouTube transcripts to extract opinions made by users, along with the context in which the opinions were made. These opinions are then matched with any relevant products through another fine-tuned LLM that looks at an opinion and any products that have a high cosine similarity as that of the opinion’s subject and decides whether that opinion is relevant to any of those products. Using a Mistral-7B FT trained on GPT-4 outputs allowed us to parse through hundreds of thousands of Reddit threads in a simple way with just hundreds of dollars of compute.

If your query relates to a specific situation (e.g. “cleansers for my son who has inflamed acne on his forehead”), we search semantically through the opinions of Redditors and YouTubers to retrieve the products recommended by those who have dealt with a similar situation. If your query relates to a specific product (e.g. “iunik centella gel”), we instead go through the product listings themselves to return you the relevant products.

We also use an LLM to analyze your search query to tell you what ingredients or effects are preferable for your skin concern.For example, if you searched for “inflamed forehead acne”, properties like “Oil-Control” and “Azelaic Acid” which are good for dealing with inflamed acne would be explained to you, and results containing those properties would be boosted and tagged in our results. You can also try out searches like “korean cleansers under $20 with Cica” to filter for certain ingredients and price points.

While we think we’ve built a product search that would be pretty helpful for our teenage (and current!) selves, there are many improvements we’d like to make, such as getting opinions from Tiktok and other social media platforms and making our opinion extraction process more robust for edge cases (e.g. by using OCR, video transcription tools). We’re also planning on allowing our users to upload their own reviews and content and to expand our search across more products.

The long-term potential is to be a go-to product for anyone looking for what other people think about anything subjective (products, restaurants, b2b products, vacation planning, etc.). We believe that the entire discovery experience can be revolutionized by making it as easy as searching on Google to find out what the people you care about think about something. On the individual level, we want to make sharing your opinions with your friends and the world as easy as posting a picture on Instagram.

For now, if you have any skincare needs, whether it be to solve a skin concern, get rid of an annoying pimple, or just to find a good sunscreen, please give us a try: https://lumona.ai (We are an Amazon and Stylevana affiliate.)

We’d love to hear your feedback on our search engine, whether that be how the skincare search performs, what you think is missing, what products you want to see there, or any technical suggestions!