Cognee
Cognee is an open-source AI memory platform designed for agents, providing them with persistent long-term memory across sessions. It allows users to turn documents, code, and conversations into a self-hosted knowledge graph that agents can search and reuse. Cognee runs locally for free, using small models that utilize the user's CPU, and does not require an API key. The platform offers various features, including text ingestion, retrieval, and session storage, as well as generated answers and media processing with additional LLM configuration. Cognee also supports multiple interfaces, such as Claude Code, OpenClaw, and Python applications, and provides a REST API reference and TypeScript SDK. The platform is highly customizable, with options for deployment on Postgres, Docker, and other infrastructure. Cognee's architecture is designed to optimize the interface between knowledge graphs and LLMs for complex reasoning, and the project has published research on this topic. Overall, Cognee is a powerful tool for building and managing AI memory, with a wide range of applications in areas such as natural language processing, machine learning, and data science. Cognee's key features include its ability to build connected memory from different sources, its support for multiple interfaces and deployment options, and its customizable architecture. The platform is well-documented, with a comprehensive README and extensive documentation, and has a strong focus on community involvement and contribution. Cognee is a rapidly evolving project, with regular updates and new features being added, and is widely used in the AI and machine learning communities.
- Category
- AI Agents
- Pricing
- Open Source
Problem solved
Cognee solves the problem of providing AI agents with persistent long-term memory, allowing them to retain context and knowledge across sessions. This is a significant challenge in the field of AI, as many agents are limited by their inability to remember and learn from past experiences. Cognee's solution to this problem is to provide a self-hosted knowledge graph that agents can search and reuse, allowing them to build on their past experiences and improve their performance over time. By providing a free and open-source solution to this problem, Cognee is making it possible for developers and researchers to build more sophisticated and effective AI agents, and is helping to advance the field of AI as a whole.
Use cases
- Building a Company Brain to connect documentation, conversations, and agent work
- Giving agents memory across runs to retain project context and past decisions
- Grounding agents in a specific domain using custom data models and ontologies
- Building a knowledge graph from text, code, and session lessons
- Deploying Cognee on Postgres or other infrastructure
Audience
- Developers
- ML Engineers
- Data Scientists
- Researchers
Pros
- Free and open-source
- Self-hosted knowledge graph
- Supports multiple interfaces and deployment options
- Highly customizable
- Comprehensive documentation
Cons
- Steep learning curve
- Requires significant computational resources
- Limited support for certain features and interfaces
Official website: https://github.com/topoteretes/cognee
Canonical LambdaBase page: https://www.lambdabase.com/tools/cognee