Cognee - AI Memory Management
4.0Cognee helps AI agents manage memory efficiently, enabling better context retention and retrieval for improved performance.
About
Cognee is a data memory engine built specifically for AI agents, solving the core problem of agents that "can't remember, can't organize, and can't effectively use" information during continuous tasks. By building a shared, continuously optimized memory system, Cognee enables AI agents to recall past events, connect context, and make more accurate decisions and execute workflows based on accumulated knowledge—just like humans do. Whether handling complex conversations, automating business processes, or coordinating multi-agent collaboration, Cognee provides agents with a stable, scalable "brain memory layer."
Key Features
Pricing & Fees
- Pricing: Cognee offers a Free plan ($0/month, 1 workspace, 1M tokens included), a Standard plan at $1.00 per 1M tokens processed plus $5 per additional workspace, and a custom-priced Enterprise plan delivered as a BYOC engagement.
- Free tier: The Free plan is free forever with no card required, including 1 workspace, 1M tokens, unlimited users, unlimited API calls, and agentic integrations (Claude Code, Codex, MCP).
- Self-hosted option: Cognee is open source, so the full memory engine can be run locally, self-hosted, in Docker, on-prem, or on Cognee Cloud at no cost.
- Enterprise tiers: BYOC engagements come in 12-month (Startup, heavily discounted), 6-month, 12-month (Recommended), and 24-month options, deployed in your own VPC with SSO, governance, and SLA support varying by tier.
Who It's For
AI application developers who need to add long-term memory and contextual understanding to chatbots, virtual assistants, or automation tools. Enterprise automation teams building cross-department, multi-step intelligent workflows that require agents to remember historical actions and business rules. Research labs exploring cutting-edge areas like multi-agent collaboration and memory-augmented learning, who need a reliable foundational memory framework. Product managers and architects evaluating and selecting next-generation AI infrastructure to enhance product intelligence and user engagement.