Polygres

Polygres brings AI retrieval to Postgres and makes it possible to search by meaning, follow relationships, and retrieve context across a database. It presents a dashboard and APIs and a Python SDK to explore and build with retrieval signals such as graph, vector, and text retrieval. The platform emphasizes embedding, graph traversal, and full‑text search as integrated retrieval signals for developers.

Polygres describes a virtual context layer that surrounds a question and uses the underlying data as a durable base. The platform aims to let AI retrieve context that can change from one request to the next, while keeping the data itself stable. It presents integration with Postgres and open‑source engines behind Polygres to enable retrieval workflows from the database. The emphasis is on providing an interface and context for AI applications built on existing data infrastructure.

It highlights three ways to start: hosted Postgres on Polygres, synchronized sources from other Postgres providers, or an application interface via API. It also mentions open‑source engines and a path toward AI‑native data through a virtual context layer.

Use cases

• Release intelligence traces a change through its downstream impact
• Decision memory traces a decision back through evidence and constraints
• Evidence trails keep an answer connected to passages that support it