Cognee

Cognee fills a real gap: durable, searchable memory for AI agents that isn't locked into a proprietary stack. With the 1.0 release, they've delivered a memory-native API that feels natural—remember, recall, improve, forget—and a single Postgres backend that cuts the usual database soup. When to pick Cognee: you're building coding agents with Claude Code or Cursor and want them to remember project context across sessions. Or you're shipping a customer-facing agent that needs cited facts and domain rules. The open-source core is free forever, and the cloud tier at $2.50/1M tokens is cheap for production. When to pass: you need a simple chatbot with zero setup. Cognee is developer-first—CLI/API, no visual builder. Also, if you need real-time streaming with sub-100ms latency, the edge version (cognee-RS) is still emerging. For non-technical teams, this isn't ready. Compared to mem0: Cognee uses a knowledge graph, not just vector embeddings, so it captures relationships. It also offers self-improving feedback loops. mem0 is lighter-weight but has less structure. Zep is fully managed and more polished but not open-source. Real-world caveats: token costs can add up if you process huge datasets repeatedly. The free tier gives 1M tokens—enough to test but not to run a busy agent. The documentation is decent but assumes you know your way around Postgres and embeddings. Support is community-driven for free users. Bottom line: if you're technical and want your agents to remember without lock-in, Cognee is one of the best options today. The 7x cost improvement over alternatives (per their BEAM benchmarks) makes it worth a try.