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Every time I had a new idea the first thing I wanted to know was whether something similar was already out there in the patent world. Turns out actually searching patents is a pain if you've never done it before. So I built something simple: describe your idea in plain English, it searches a large patent database and shows you the closest existing patents with a rough patentability grade. Takes about 90 seconds. It's a basic first look, not a substitute for a full legal search before you...
Comments (4)
because ai never hallucinates details about prior art
which embedding model? vector search over full patent text or just abstracts?
vector embeddings over uspto data still miss half the obscure cpc overlaps
what embedding model are you using for the patent vector search?
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