Cognee

Cognee is an open-source memory platform designed to give AI agents persistent, structured memory across sessions. The core workflow captures context from conversations, documents, and interactions, turns that context into graph memory that encodes entities and their relationships, and lets every agent recall relevant information later. This addresses a fundamental limitation of stateless agents: without memory, each session starts from zero. Cognee provides an SDK that developers integrate into their applications, plus a cloud platform for teams that want managed infrastructure. The project has strong open-source traction with over 30,000 GitHub stars, and the cloud offering is the commercial layer on top of the free open-source core. The platform integrates with popular agent ecosystems including Claude Code, Codex, MCP, OpenClaw, and the OpenAI Agents SDK, so developers can add memory to their existing stacks rather than rebuilding. Pricing follows a freemium model: the free tier starts at zero dollars per month, usage beyond the free allowance is billed at 2.50 dollars per million tokens, and additional workspaces cost five dollars each per month with unlimited workspaces available. Teams can start local with the open-source version and scale to Cognee Cloud when they need managed infrastructure, collaboration, and higher reliability. The company positions Cognee as the memory layer for the agent era, competing with approaches that store raw chat logs or embeddings only, by structuring memory as a graph that supports rich recall and reasoning. For developers building agentic applications, customer support copilots, research assistants, or personal AI systems, Cognee provides the persistence layer that makes agents feel continuous and context-aware across long-running interactions. The platform is designed around three layers: capture, storage, and recall. Capture ingests conversations and documents from the connected tools, storage converts the ingested context into a knowledge graph, and recall exposes that graph to agents through query APIs. Developers can choose how much of the pipeline runs locally versus in the cloud, which makes Cognee flexible for privacy-sensitive deployments where data should not leave the organization. The graph structure also supports incremental updates, so memory grows and corrects itself as new context arrives rather than requiring full re-indexing.