An AI agent without memory starts every task from zero. The complete guide to the four kinds of memory — context windows, vector recall, knowledge graphs, feedback — what they solve, how they combine, and where each one breaks.
Memory stores what was said. Knowledge captures what it means. The difference is structure — typed entities, relationships, versioned facts — and it's the gap most agents still fall into. Three lines of code show what fixes it.
Two benchmark exercises across HotPotQA, TwoWikiMultiHop, and MuSiQue, plus a head-to-head against Mem0, Graphiti, and LightRAG. Full numbers, methodology, honest caveats, and reproduction code — read the evidence behind the marketing.
Dumping docs into a vector store isn't enough. An AI agent knowledge base needs three layers — reference, operational, feedback — plus an ingestion pipeline that keeps them current. What actually goes in, with code.
Add persistent memory to Claude Agent SDK using Model Context Protocol (MCP) + cognee tools—store once, retrieve anytime without prompt bloat. Try it now!
Add persistent AI memory to n8n automation with the cognee node—cognify data into a graph and search context instantly. Install now and build smarter flows!
Learn how Cognee enables long-term memory in AI agents using knowledge graphs, vector search, and feedback-driven optimization compared to stateless RAG.
Give Gemini agents persistent memory in Google ADK using cognee’s graph-backed memory layer. Build context-aware workflows that survive restarts—start building now!
Build your own AI news agent and smart news aggregator with cognee. Scrape Reddit and RSS, summarize events into a knowledge graph and stay ah ead—try it now!
An AI agent without memory starts every task from zero. The complete guide to the four kinds of memory — context windows, vector recall, knowledge graphs, feedback — what they solve, how they combine, and where each one breaks.
Memory stores what was said. Knowledge captures what it means. The difference is structure — typed entities, relationships, versioned facts — and it's the gap most agents still fall into. Three lines of code show what fixes it.
Two benchmark exercises across HotPotQA, TwoWikiMultiHop, and MuSiQue, plus a head-to-head against Mem0, Graphiti, and LightRAG. Full numbers, methodology, honest caveats, and reproduction code — read the evidence behind the marketing.
Dumping docs into a vector store isn't enough. An AI agent knowledge base needs three layers — reference, operational, feedback — plus an ingestion pipeline that keeps them current. What actually goes in, with code.
Add persistent memory to Claude Agent SDK using Model Context Protocol (MCP) + cognee tools—store once, retrieve anytime without prompt bloat. Try it now!
Add persistent AI memory to n8n automation with the cognee node—cognify data into a graph and search context instantly. Install now and build smarter flows!
Learn how Cognee enables long-term memory in AI agents using knowledge graphs, vector search, and feedback-driven optimization compared to stateless RAG.
Give Gemini agents persistent memory in Google ADK using cognee’s graph-backed memory layer. Build context-aware workflows that survive restarts—start building now!
Build your own AI news agent and smart news aggregator with cognee. Scrape Reddit and RSS, summarize events into a knowledge graph and stay ah ead—try it now!
Scrape live web data and build a knowledge graph for AI agents with ScrapeGraphAI + Cognee. Build a memory system that understands your data. Follow the step-by-step guide now.
Discover 3 OpenClaw use case ideas and how Cognee brings deeper memory, connected context, and smarter recall. Explore the next step for AI agents—read now.
Scrape live web data and build a knowledge graph for AI agents with ScrapeGraphAI + Cognee. Build a memory system that understands your data. Follow the step-by-step guide now.
Discover 3 OpenClaw use case ideas and how Cognee brings deeper memory, connected context, and smarter recall. Explore the next step for AI agents—read now.
Cognee is the fastest way to start building reliable Al agent memory.
Looking for a custom deployment? Chat with our engineers!