Cognee is an open-source AI memory platform for agents with 32,600+ stars on GitHub, giving AI systems persistent, structured long-term memory.
Agents forget everything between sessions unless you build them a memory. Cognee is that memory layer: it ingests your data — documents, conversations, code, events — and organizes it into a knowledge graph combined with vector search, so an agent can recall facts, relationships and context across sessions instead of starting from zero. The platform is designed to work with small, free models running locally on CPU, which keeps the memory layer cheap and private, and it plugs into agent frameworks through a straightforward API. For teams that do not want to operate it themselves, Cognee Cloud offers the same platform as a managed service. The project is Apache-2.0 licensed and very actively developed, with updates in October 2026.
The insight behind Cognee is that raw vector search is a weak form of memory: it finds similar text but knows nothing about entities, relationships or how facts evolved. By structuring memory as a graph, Cognee lets agents answer relational questions — who works on what, which decision superseded which — that similarity search fumbles. Developers typically start by pointing it at a folder of documents or a conversation history and get a queryable memory in a few lines of code, then grow into custom pipelines as their agents mature.
Cognee is free and open source under the Apache License 2.0 for self-hosting. Cognee Cloud is a paid managed service — see cognee.ai for current plans.
Developers building agents, copilots and AI apps that need to remember users, facts and history over time — without hand-rolling a memory system.