Polygres (YC F26) @polygres
AI retrieval that feels like extended context. Graph + vector + full-text, one query over your whole Postgres / Neon / Planetscale/Supabase polygres.com San Francisco, CA Joined April 2025-
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How do you forget to announce smh
A little late but: Polygres is in Y Combinator. Apparently when you get into @ycombinator you’re supposed to announce it. I forgot. Mbmb If your retrieval system “mostly works” and you’ve started developing a personal hatred of PGVector, custom SQL tools, or the word
A little late but: Polygres is in Y Combinator. Apparently when you get into @ycombinator you’re supposed to announce it. I forgot. Mbmb If your retrieval system “mostly works” and you’ve started developing a personal hatred of PGVector, custom SQL tools, or the word “embedding”, please message me. You're... basically why we’re building @polygres . And fortunately! (cos i'm great to work with) :D try it free if uw: polygres.com <3 frm @daltonmeon @daleverett @damienhe
If you’re still unsure what to film for your @ycombinator video, here’s ours! We’re @polygres , and we turn your entire database into a context window. We uprooted our entire lives to come to SF, because we believe this is the best place to build a startup. - @daleverett
How to be ninja (YC Edition) 🥷
Stealth is rather hard when you don’t know where you are
Make search light again
Lightsearch: a System 1 model for search. Most semantic search makes you pay before you search. Lightsearch flips it: send a query, the model figures out how to search, pay only at query time. we’re in private beta and looking for design partners with hard search problems.
Lightsearch: a System 1 model for search. Most semantic search makes you pay before you search. Lightsearch flips it: send a query, the model figures out how to search, pay only at query time. we’re in private beta and looking for design partners with hard search problems. make search light. dm me
Wait what?
Pool Noodle (YC F26)
Why the fuck are you building a search engine?
I can break your AI agent with a can of Monster. Link in first comment.
This is crazy holy shit
I can break your AI agent with a can of Monster. Link in first comment.
I can break your AI agent with a can of Monster. Link in first comment.
@etok_me @DhravyaShah @PlanetScale Wassup
Demo day is coming
Day 2 of @ycombinator 48 hours in and we've already had to unlearn half of what we thought we knew about growth @polygres Reply 'coffee' if you'd wanna meet for coffee! (virtual too!) Filmed at dinner, right before a great talk with @sama @daltonmeon @damienhe
Day 2 of @ycombinator 48 hours in and we've already had to unlearn half of what we thought we knew about growth @polygres Reply 'coffee' if you'd wanna meet for coffee! (virtual too!) Filmed at dinner, right before a great talk with @sama @daltonmeon @damienhe
Arguably a vector store without an embedding model is a fridge without a kitchen Glad we got this sorted 🫡🫡🫡 Free credits btw
things that should never have been separate: > peanut butter and jelly > Simon and Garfunkel > your data and its embeddings anyway, embedding models now run inside @polygres + free quota on every account for a limited time 😉
me: babe are you ok my database: I'm fine me: you're generating your own embeddings now my database: I said I'm fine
things that should never have been separate: > peanut butter and jelly > Simon and Garfunkel > your data and its embeddings anyway, embedding models now run inside @polygres + free quota on every account for a limited time 😉
things that should never have been separate: > peanut butter and jelly > Simon and Garfunkel > your data and its embeddings anyway, embedding models now run inside @polygres + free quota on every account for a limited time 😉
New site is slick af
We joined @ycombinator’s Fall batch to kill the fragmented AI retrieval stack. Polygres gives you one API for graph, vector, and text retrieval over Postgres. No new database. No mess of retrieval infrastructure. New site is live. Much more coming. polygres.com
Our ambition reaches way beyond a better search box. We want intelligence to work with the information the world already has, wherever useful context is waiting to be found. We’re solving AI retrieval to make the entire world's data ai-native. There’s a lot to build.
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