Cognee is an open-source AI memory platform that gives AI agents persistent long-term memory across sessions. With nearly 25,000 GitHub stars, it addresses one of the most persistent weaknesses of agentic systems: by default, agents forget. Cognee lets you ingest data in any format and continuously builds a self-hosted knowledge graph so that every agent can recall, connect, and act with full context rather than starting cold on each new conversation. ## Self-Hosted Knowledge Graph Memory Rather than relying on a single vector store, Cognee combines vector embeddings with graph reasoning. Documents become both searchable by meaning and connected by explicit relationships, and because the graph is self-hosted, teams keep their memory layer and data under their own control. The result is a memory substrate that captures how pieces of knowledge relate, not just how similar they are. ## Cognitive-Science-Grounded Ontology A distinguishing feature is ontology generation grounded in cognitive science. As new information arrives, Cognee evolves the relationships in the graph so the memory reflects an updating model of a domain instead of a static snapshot. This design is backed by published research on optimizing the interface between knowledge graphs and LLMs for complex reasoning, signaling that the project is more than an ad-hoc retrieval wrapper. ## Ingest, Cognify, Retrieve The workflow is straightforward: feed in documents, conversations, or structured records; let Cognee "cognify" them into an interconnected graph enriched with embeddings; then query that memory by meaning and relationship from your agents. This pipeline turns scattered source material into a queryable, durable memory that improves as more data flows through it. ## Integrations Cognee meets developers where they already work. It ships as a plugin for Claude Code, offers Rust and TypeScript clients alongside its Python core, and maintains a community repository of plugins and add-ons. That breadth makes it practical to bolt persistent memory onto an existing agent stack without committing to a single language or framework. ## Considerations Running a self-hosted graph plus vector setup adds operational overhead compared with a hosted memory API, and tuning ontology generation for a specific domain takes experimentation. As a fast-moving project, its APIs and best practices continue to evolve. For teams building agents that need durable, relationship-aware memory they fully control, though, Cognee is among the most compelling open-source platforms in the space.