Cognee

Cognee is an open-source AI memory platform built by Topoteretes UG, headquartered in Berlin, that transforms raw data into structured knowledge graphs for AI agents. Most memory systems store text chunks in a vector database. Cognee runs an ECL pipeline (Extract, Cognify, Load) that extracts entities, maps relationships, and builds a queryable knowledge graph with embeddings. This gives agents temporal awareness, entity relationships, and feedback loops that pure vector retrieval cannot provide. The core operations are four: remember (store to graph), recall (query with auto-routing), forget (delete), and improve (refine through feedback). When an agent rates a response, that feedback updates edge weights in the graph, so the memory gets sharper with use rather than staying static. Cognee unifies three storage layers (relational, vector, and graph) into a single engine using SQLite, LanceDB, and Kuzu locally, with managed cloud options for production scale. Cognee ships three SDKs. The Python SDK is the most fully documented. A TypeScript SDK, @cognee/cognee-ts, provides Node.js bindings, and a Rust SDK, cognee-rs, is documented across architecture, configuration, guides, an HTTP server and operations. Native integrations include the Claude Agent SDK, the OpenAI Agents SDK, LangGraph, Google ADK, n8n, Amazon Neptune and Neo4j. Cognee is also available as a Claude Code plugin. Cognee publishes its own MCP server. The vendor documents it for Claude, Cursor, Cline, Continue and Roo Code, and the documentation describes both a standalone architecture mode for individual developers and an API mode for teams sharing one knowledge graph across multiple AI clients. Agentic integrations including MCP are available on the free tier rather than gated behind a paid plan. Pricing is usage-based and was restructured to a token model. Free is $0 per month and includes 1M tokens, one workspace, unlimited users, unlimited API calls and agentic integrations, with no card required. Standard is $2.50 per 1M tokens on a pay-for-what-you-process basis, and adds unlimited workspaces at $5 each per month, data source integrations for Slack, Notion and Google Drive, and in-app support. Enterprise is sold on a sales call and adds a dedicated Slack channel, a dedicated support engineer, bring-your-own-cloud and a support SLA. Self-hosted deployment remains free under the open-source license. What the entry price does not buy: the $5 per workspace charge is an add-on for additional workspaces rather than a plan fee, and it stacks on top of token consumption. The free tier is capped at one workspace and 1M tokens. Best fit: AI engineers who need agents with persistent, structured memory that improves from real usage rather than replaying conversation history, and teams that want graph-based memory without gating it behind an enterprise plan. Who Cognee is not for: teams that want a fully managed, turn-key hosted memory service with minimal configuration, and teams that need published temporal-reasoning benchmark scores for procurement, since Cognee has not published a LongMemEval result. Alternatives worth evaluating are Mem0 for a larger community, Zep for structured user memory with session history, and a general-purpose vector database where graph relationship mapping is not needed. Current state Q3 2026: Cognee raised a $7.5M seed round and reports surpassing 5 million SDK runs per month, with Bayer published as a named customer case study. The cloud runs on GPT-OSS-120B, OpenAI's open-weight model. Certifications are limited to GDPR and CCPA, stated on the vendor's trust page and privacy policy respectively, with no SOC 2 or ISO 27001 published. Cognee publishes General Terms and Conditions in separate US and EU versions, effective 27 March 2026, and neither those documents nor the privacy policy contains any statement about training on customer data.