Most support teams don't have a support problem — they have a context problem. Here's how we built a support agent on top of cognee using user, agent, and organization memory.
Adding memory to agentic workflows used to mean restructuring your stack. One decorator changes that. We ran 198 simulated sales conversations — and the results make a strong case for structured memory.
MCP has real auth built in. CLI doesn't — or so the claim goes. The Claude Code plugin that wraps cognee-cli runs a full register-login-token handshake before the first command fires.
Your agent forgets everything between sessions. The fix isn't a bigger context window — it's persistent memory via a CLI. Four commands give your agent cross-session, graph-structured memory.
Anthropic accidentally exposed 500,000 lines of internal source code. Buried inside: engineers studying Cognee's memory architecture and wondering if they should just adopt it.
Learn how Custom Graph Models in cognee create a stable, domain-aware memory layer for agents — and how the Cascade feature progressively discovers missing schema from real data.
Learn how to build self-improving skills for AI agents with Cognee. Transform static SKILL.md files into evolving components that learn from failure. Try it now.
Most support teams don't have a support problem — they have a context problem. Here's how we built a support agent on top of cognee using user, agent, and organization memory.
Adding memory to agentic workflows used to mean restructuring your stack. One decorator changes that. We ran 198 simulated sales conversations — and the results make a strong case for structured memory.
MCP has real auth built in. CLI doesn't — or so the claim goes. The Claude Code plugin that wraps cognee-cli runs a full register-login-token handshake before the first command fires.
Your agent forgets everything between sessions. The fix isn't a bigger context window — it's persistent memory via a CLI. Four commands give your agent cross-session, graph-structured memory.
Anthropic accidentally exposed 500,000 lines of internal source code. Buried inside: engineers studying Cognee's memory architecture and wondering if they should just adopt it.
Learn how Custom Graph Models in cognee create a stable, domain-aware memory layer for agents — and how the Cascade feature progressively discovers missing schema from real data.
Learn how to build self-improving skills for AI agents with Cognee. Transform static SKILL.md files into evolving components that learn from failure. Try it now.
Anthropic accidentally exposed 500,000 lines of internal source code. Buried inside: engineers studying Cognee's memory architecture and wondering if they should just adopt it.
Edge AI memory brings private, on-device AI memory to phones, wearables and IoT, for better latency, accuracy and privacy. Book a call to discuss your use case!
Anthropic accidentally exposed 500,000 lines of internal source code. Buried inside: engineers studying Cognee's memory architecture and wondering if they should just adopt it.
Edge AI memory brings private, on-device AI memory to phones, wearables and IoT, for better latency, accuracy and privacy. Book a call to discuss your use case!
Cognee is a memory engine for AI agents that builds a knowledge graph from data and makes it searchable. It's a simple, yet powerful way to build AI agents that can remember and use information over time.
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.
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.
Cognee is a memory engine for AI agents that builds a knowledge graph from data and makes it searchable. It's a simple, yet powerful way to build AI agents that can remember and use information over time.
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.
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.
Banking Agents meet semantic AI memory to unify credit card rules with ontology supported provenance - boosting accuracy and compliance. Read more, book a call!
Turn scattered research into trusted context for Special Education Agent with cognee, delivering evidence with citations. Book a demo and power your domain Agent!
AI memory case study: Knowunity used AI in education and cognee's knowledge graph tech to connect 40,000 learners by proximity and needs—see results. Read now.
Banking Agents meet semantic AI memory to unify credit card rules with ontology supported provenance - boosting accuracy and compliance. Read more, book a call!
Turn scattered research into trusted context for Special Education Agent with cognee, delivering evidence with citations. Book a demo and power your domain Agent!
AI memory case study: Knowunity used AI in education and cognee's knowledge graph tech to connect 40,000 learners by proximity and needs—see results. Read now.
Most support teams don't have a support problem — they have a context problem. Here's how we built a support agent on top of cognee using user, agent, and organization memory.
Adding memory to agentic workflows used to mean restructuring your stack. One decorator changes that. We ran 198 simulated sales conversations — and the results make a strong case for structured memory.
MCP has real auth built in. CLI doesn't — or so the claim goes. The Claude Code plugin that wraps cognee-cli runs a full register-login-token handshake before the first command fires.
Most support teams don't have a support problem — they have a context problem. Here's how we built a support agent on top of cognee using user, agent, and organization memory.
Adding memory to agentic workflows used to mean restructuring your stack. One decorator changes that. We ran 198 simulated sales conversations — and the results make a strong case for structured memory.
MCP has real auth built in. CLI doesn't — or so the claim goes. The Claude Code plugin that wraps cognee-cli runs a full register-login-token handshake before the first command fires.
Turn AI agent skills into a knowledge graph with Cognee. Route tasks by meaning, learn from feedback, and improve over time. Start building smarter agents now.
Learn how Cognee enables long-term memory in AI agents using knowledge graphs, vector search, and feedback-driven optimization compared to stateless RAG.
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!
Turn AI agent skills into a knowledge graph with Cognee. Route tasks by meaning, learn from feedback, and improve over time. Start building smarter agents now.
Learn how Cognee enables long-term memory in AI agents using knowledge graphs, vector search, and feedback-driven optimization compared to stateless RAG.
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.
Learn how OpenClaw's Markdown memory works, where it falls short, and how a Cognee plugin adds knowledge-graph recall, indexing, and smarter retrieval.
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.
Learn how OpenClaw's Markdown memory works, where it falls short, and how a Cognee plugin adds knowledge-graph recall, indexing, and smarter retrieval.
Cognee is the fastest way to start building reliable Al agent memory.
Looking for a custom deployment? Chat with our engineers!