Cognee
Open-source memory and data infrastructure for AI applications that need reliable context.
Cognee overview
Cognee is an open-source memory and data layer for AI applications, focused on turning data into structured, retrievable context for agents and LLM systems.
Data-to-memory pipeline
Cognee focuses on transforming input data into usable memory and context.
AI apps fail when the context layer is improvised.Open-source context infrastructure
The project gives builders a repository and docs for evaluation.
Context infrastructure needs inspectability and deployment control.Useful for agent apps
Structured context can support agents that need to retrieve and reason over data.
Agents need grounded context to avoid acting on stale or missing information.When to use Cognee
Knowledge ingestion
Prepare documents, records, or project data for AI workflows.
Agent memory layer
Use it as a context layer that agents can retrieve from during tasks.
Internal AI apps
Build assistants that answer with company or project-specific context.
How it compares
A document loader moves data; Cognee is closer to an infrastructure layer for preparing and retrieving AI context.
Questions
What should I check before using Cognee?
Test Cognee with repeated sessions. Add facts, update them, ask for recall, inspect retrieval behavior, and verify deletion or scoping controls before storing sensitive user or project memory.
Is Cognee open source?
Cognee is listed with Apache-2.0 based on the official source links in this profile. Re-check the repository, model card, or docs before production use.
Who should evaluate Cognee?
Cognee is most worth evaluating for builders creating AI apps over messy data sources.