We help people make the right decision on what to buy. To do this we indexed the world's product knowledge and then taught a neural net to replicate the research process of a savvy shopper.
We're going after a massive problem. Commerce is fundamentally broken with the only way products get sales is if they run expensive ads on Facebook, Google, Amazon etc.
We envision a meritocratic & pro-consumer shopping experience. Where the best product for each person wins, not the one with the best marketing.
The director of ML at Apple called us one of the best ML teams he's met in Silicon Valley.
We just raised a series A from a tier 1 VC.
Scrape the world's product knowledge. Figure out how to get knowledge out of Editorial sites, Reddit, Youtube, Forums etc. Scale the QA of that data pipeline. Use cutting edge ML as well as simple scrapers to extract data.
Ingest scraper data to build out a product knowledge graph. Figure out how to automatically create relationships between data/products/ratings to help our ML systems recommend products. Incorporate human-in-the-loop curation to maximise the quality of our data.
Build & train a neural net to replicate the product research process of savvy shopper. Figure out what features you can build from the knowledge graph to solve behavioral issues of our recommendations.
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