Project
Bento
Agentic memory in Postgres — the elephant remembers so the goldfish can forget.
- Open Source
- Python
- postgres
- memory
- ai
- rag
- Status
- alpha
Bento is project #001 in Goldfish Labs — agent-grade memory primitives that run on Postgres, not a vector store bolted to an LLM. The thesis: durable, queryable, governable memory belongs in the system of record, not in a separate index that drifts.
Why Postgres
A vector store is an index, not a database. It can find similar things, but it can’t transact, join, version, or enforce row-level security on what it returned. Agent memory is none of those problems — it’s all of them at once. You need the recall of a vector index, the truth of a relational store, the ergonomics of SQL, and the operational maturity of something a bank already trusts. That’s Postgres + pgvector + a small kit of opinionated tables.
What ships
/v1/ask— a single HTTP endpoint that takes a question and returns a grounded answer with citations.- Memory primitives: episodic (events), semantic (facts), procedural (preferences) — three tables, three retrieval modes.
- Row-level security from day one. Multi-tenant by default. No “but in production we’ll add auth.”
- No-spin benchmarks: where Bento is faster, we show it; where it trades footprint for accuracy, we say so.
What’s on this page
Every piece of Goldfish content tagged project: bento shows up below — the blog posts that explain the thesis, the tutorials that get you to a working memory store, the videos and podcasts where we talk it through, and the sample code you can paste into a project today.