Cognee AI NEW

Cognee is an open-source agent memory platform that captures context, builds graph and vector memory, and enables agents to recall information across sessions.It provides an SDK and memory API with integrations for Claude, Claude Code, Codex, Cursor, MCP, OpenClaw, LangGraph and other agent frameworks for read/write memory access.

Connectors for S3, data warehouses, Slack, Notion, Google Drive and document stores ingest files, chats and APIs into a single recallable memory layer.Support for custom ontologies, data models and permission controls helps teams govern memory and maintain authoritative, searchable knowledge.

Deploy locally for on-premise control or scale on Cognee Cloud to preserve project context, decisions and past work across sessions.Common use cases include long-term agent memory for coding assistants, research and knowledge bases, sales and deal intelligence, technical manuals, and educational teaching assistants.

Key Features

• Captures context and builds graph and vector memory to enable cross-session agent recall
• Provides SDK and Memory API with integrations for Claude, Claude Code, Codex, Cursor, MCP, OpenClaw, LangGraph and other agent frameworks for read/write memory access
• Connectors for S3, data warehouses, Slack, Notion, Google Drive and document stores to ingest files, chats and APIs into a unified recallable memory layer
• Support for custom ontologies, data models and permission controls for governed, searchable memory
• Deployable locally (on-premise) or scalable via Cognee Cloud

Use Cases

• Build a customer-support assistant using Cognee that persistently remembers past conversations across Slack, email and Drive, stitches context into graph and vector memory for fast retrieval of case history and recommended resolutions, and runs on-premise with governance controls to keep sensitive data compliant
• Develop an internal knowledge hub for engineering and product teams using Cognee's connectors (Notion, S3, Drive) to ingest docs, map relationships with graph memory and a custom ontology, and provide searchable, recallable memory across sessions via the Memory API or SDK for instant access to design decisions and code snippets
• Create a research and experimentation assistant using Cognee to capture papers, experiment notes and datasets into vector memory for semantic search, surface related prior work and follow-ups across sessions, integrate via SDK/connectors and deploy on-premise with access and retention policies enforced by governance controls

Who is it for?

• Agent developers
• Machine learning engineers
• Data engineers
• Product managers
• Devops engineers