Postgres plus retrieval primitives
Polygres combines PostgreSQL hosting with native graph traversal, HNSW vector search, and hybrid retrieval APIs so relational, semantic, and structural queries can run against the same data source.
Polygres is a Postgres platform for AI agents that combines hosting with graph traversal, HNSW vector search, and hybrid retrieval APIs. It helps teams turn relational data into queryable working memory for agent workflows.
Polygres is a Postgres platform for AI agents that combines database hosting with graph traversal, vector search, and hybrid retrieval APIs. Its core pitch is to make rows, relationships, and embeddings queryable together, so an agent can retrieve grounded context from the database instead of relying on prompt stuffing.
The product is organized around two retrieval layers described on the homepage as pgGraph and pgContext. pgGraph turns existing foreign keys into graph traversal for multi-hop relationship search, while pgContext runs multiple search methods in parallel and fuses the results into a single ranked answer. The output is presented as a token-ready context block that can be passed into an agent workflow.
The site also shows supporting surfaces around the core platform: a public retrieval playground for user memories and Wikipedia, and Polygres Pocket, a separate CLI-oriented package that folds codebases, files, and memories into a queryable context window for agents. The pricing page offers a free self-hosted option and managed cloud plans for users who want hosted infrastructure.
Polygres combines PostgreSQL hosting with native graph traversal, HNSW vector search, and hybrid retrieval APIs so relational, semantic, and structural queries can run against the same data source.
The homepage describes pgGraph as graph retrieval over existing foreign keys, with multi-hop traversal, shortest paths, and relationship search over the tables you already have.
The homepage describes pgContext as fused search that runs multiple search methods at once and merges the results into one ranked list.
The product returns a token-ready context block for agents, assembling rows, paths, and matches into a single result that can be passed to an LLM or agent workflow.
The site positions the product as usable with an existing schema or as a managed instance, and the Pocket page shows an MCP-style workflow for connecting agent tools.
The user demo pages expose retrieval controls for graph depth, semantic, lexical, and graph weighting, plus answer synthesis settings in the interface.
Use Polygres when an agent needs to follow foreign-key relationships, look up related records, and return a grounded answer in one request. The product is designed to turn relational data into traversable memory.
Use the public playground style workflows to inspect how semantic, keyword, and graph signals are fused for a specific query. The demo pages make the retrieval process visible for evaluation and experimentation.
Use Polygres when your application needs to combine vector similarity with graph expansion and typed filters without building separate systems. The homepage shows a single query path that merges these signals into one ranked list.
Use the Pocket workflow when you want a CLI-mediated context store for codebases, files, and memories that can be attached to an agent through MCP. The product page frames it as a way to give coding agents a larger working memory.
Use the managed cloud if you want hosted PostgreSQL infrastructure, or self-host if you already have a Postgres instance and want to run the open-source components yourself.
Polygres is a Postgres-based database platform that combines managed hosting with native graph traversal, HNSW vector search, and hybrid retrieval APIs. It is positioned for agents that need relational, graph, and semantic retrieval from the same database.
The source shows managed cloud options, a free self-hosted path, and an open-source workflow. The pricing page also says Polygres is currently looking for design partners.
The homepage shows retrieval flows that combine graph hops, semantic search, lexical search, filters, and token-ready context assembly. The user demo pages also show a public playground with adjustable retrieval controls.
The site mentions that you can start free, and that the managed cloud has a free Launch plan plus paid Scale and enterprise options marked coming soon. The pricing page also offers a $0 forever self-hosted option.
The public demo pages note that queries are rate-limited to prevent abuse, so responses may be slightly slower. They also say the point of the demo is to show how Polygres works, not to provide full performance benchmarks.
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