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I built an AI shopping assistant with 200M Shopify products

Hacker News

I built an AI shopping assistant with 200M Shopify products

Hi HN! I previously launched Agora, a search engine for e-commerce products, here on HN: https://news.ycombinator.com/item?id=38635695 Sticking to the Ancient Greek theme we just released Athena, an AI assistant that helps users find products in a personalized way. Athena gathers context of what you're looking for, asks specific questions about the product category and budget, and then presents a few recommendations. To power Athena we're using text embeddings of the name, description, and tag fields with SBERT. Additionally, we're using LangChain, GPT-3.5, GPUs on Digital Ocean's Paperspace, a Mongo database, and servers on AWS running self-hosted Typesense. Agora currently has a dataset of about 200 million products from stores on Shopify, WooCommerce, Squarespace, and Wix. The vision for Athena is to use AI to help people find any product in the world. I'm continuing to build it for someone like myself: I want to shop from smaller stores around the world but unsure where to start. Still working out a lot of bugs and enhancements before letting Hermes (i.e our aptly named store crawler) index billions of e-commerce products. We'll also feed in more data like reviews, discussion threads, and automated user feedback to improve the recommendation experience. I'd love any feedback!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
92%92% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, context · Missing: mac, agents, macos
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: just released, io · Missing: https docs, excited, exist
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: personal, users, way · Missing: mobile apps, ios, entrepreneurs
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: reviews, host, users · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: shopify · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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