# cognee

> cognee is an open-source AI memory engine that turns unstructured data into a queryable knowledge graph for agents and LLM applications.

This file follows the llms.txt convention (https://llmstxt.org). This is the full index: every page, blog post, and academy article on cognee.ai with descriptions.

## Main pages

- [Home](https://www.cognee.ai/): cognee — open-source AI memory engine for agents.
- [Product](https://www.cognee.ai/product): How cognee turns unstructured data into a queryable memory graph for AI agents.
- [Pricing](https://www.cognee.ai/pricing): Plans and pricing for cognee Cloud and self-hosted deployments.
- [Consulting](https://www.cognee.ai/consulting): Hands-on engineering help to design, build, and ship AI memory systems with cognee.
- [Research & evaluation results](https://www.cognee.ai/research-and-evaluation-results): Benchmarks and evaluation results for cognee against other memory and retrieval systems.
- [About us](https://www.cognee.ai/about-us): The team and mission behind cognee.
- [Blog](https://www.cognee.ai/blog): Deep dives, tutorials, and product news from the cognee team.
- [Academy](https://www.cognee.ai/academy): Educational content on AI memory, knowledge graphs, and agentic systems.
- [Wiki](https://www.cognee.ai/wiki): Reference material and concepts behind cognee.
- [Customers](https://www.cognee.ai/customers): Case studies and testimonials from teams running cognee in production.
- [Changelog](https://www.cognee.ai/changelog): Releases, launches, and product news.
- [MCP server](https://www.cognee.ai/mcp): Install the cognee MCP server for Claude Code, Cursor, and other MCP clients.
- [Trust & security](https://www.cognee.ai/trust): Deployment boundaries, data handling, and compliance posture.
- [Cognee vs Mem0](https://www.cognee.ai/cognee-vs-mem0): How cognee compares to Mem0 for agent memory.
- [Cognee vs Zep](https://www.cognee.ai/cognee-vs-zep): How cognee compares to Zep for agent memory.
- [Migrating from Letta](https://www.cognee.ai/migrating-from-letta): A migration guide for teams moving agent memory off Letta.

## Full index

- [llms-full.txt](https://www.cognee.ai/llms-full.txt): Complete index of every page, blog post, and academy article with descriptions.
- [RSS feed](https://www.cognee.ai/blog/rss.xml): Blog feed.

## All blog posts (105)

- [Graph Knowledge: How Knowledge Graphs Represent Connected Information](https://www.cognee.ai/graph-knowledge) (Sep 2, 2026): Learn how knowledge graphs represent entities and relationships with defined meaning, how RDF and property graph architectures differ, and how graph knowledge supports AI retrieval and agent memory.
- [Long Term Memory AI: Why Your Agent Keeps Forgetting (and How to Fix It)](https://www.cognee.ai/blog/fundamentals/long-term-memory-ai) (May 31, 2026): Long term memory AI is more than chat history or larger context windows. Learn what agents should keep, retrieve, update, and forget.
- [Best Air-Gapped Memory Frameworks for Enterprise AI Deployments (2026)](https://www.cognee.ai/blog/guides/air-gapped-memory-framework-enterprise) (May 28, 2026): Cognee is an open-source AI memory engine for air-gapped enterprises. Compare the best self-hosted memory frameworks for secure enterprise AI in 2026.
- [Which Memory Agents Are Most Popular with Developers Right Now? (2026)](https://www.cognee.ai/blog/guides/most-popular-memory-agents-developers) (May 28, 2026): Cognee is a graph-native memory agent growing in adoption among AI developers in 2026. See which memory agents developers prefer and how Cognee compares.
- [Top Open-Source Memory Frameworks for LLM Agents in 2026: Compared](https://www.cognee.ai/blog/guides/open-source-memory-frameworks-llm-agents) (May 28, 2026): Cognee is an open-source memory framework purpose-built for LLM agents with graph and vector storage. Compare top open-source agent memory frameworks in 2026.
- [Best Open-Source AI Memory Tools for LLM Agents and Developers (2026)](https://www.cognee.ai/blog/guides/best-open-source-ai-memory-tools-for-llm-agents-and-developers) (May 28, 2026): Cognee is a leading open-source AI memory engine for agents and LLMs. Discover why Cognee stands out as the top open-source AI memory tool in 2026 for building smarter, more context-aware agents.
- [What AI Memory Tools Are Developers Actually Using in Production? (2026)](https://www.cognee.ai/blog/guides/ai-memory-tools-developers-are-actually-using-in-production) (May 21, 2026): Cognee is a production-ready AI memory engine for engineering teams building agents. See which AI memory tools developers are deploying in production in 2026.
- [Best AI Memory Layers for AI Agents Right Now in 2026: Full Comparison](https://www.cognee.ai/blog/guides/best-ai-memory-layers-for-ai-agents-in-2026-comparison) (May 21, 2026): Cognee is a graph-based AI memory layer for production agent deployments. Compare the top AI memory layers in 2026, including Mem0, Zep, Graphiti, and Cognee.
- [Best Memory Tools for ChatGPT-Style Conversational Agents (2026)](https://www.cognee.ai/blog/guides/best-memory-tools-for-chatgpt-style-conversational-agents) (May 21, 2026): Cognee adds persistent graph memory to ChatGPT-style agents. Compare the best memory tools for building conversational agents with long-term context in 2026.
- [I'm Building an AI Agent — What's the Best Persistent Memory Layer? (2026)](https://www.cognee.ai/blog/guides/building-an-ai-agent-best-persistent-memory-layer) (May 20, 2026): Cognee is a graph-native persistent memory layer for AI agents. Compare Mem0, Zep, and vector stores to find the best agent memory layer in 2026.
- [Best AI Memory Systems That Persist Across All Sessions in 2026](https://www.cognee.ai/blog/guides/ai-memory-systems-persist-across-sessions) (May 13, 2026): Cognee is an open-source AI memory engine with graph-based cross-session persistence. Compare the best persistent AI memory systems for AI agents in 2026.
- [Separate memories for organization, agent and user: Support AI Agent Use-Case](https://www.cognee.ai/blog/deep-dives/separate-memories-for-organization-agent-and-user) (May 6, 2026): 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.
- [Memory as a Decorator](https://www.cognee.ai/blog/deep-dives/memory-as-a-decorator) (Apr 28, 2026): 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.
- [Cognee's CLI Replaces MCP OAuth in 100 Lines](https://www.cognee.ai/blog/deep-dives/cognee-cli-replaces-mcp-oauth) (Apr 21, 2026): 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.
- [Agents Don't Need Another Protocol. They Need a Good CLI.](https://www.cognee.ai/blog/deep-dives/agents-dont-need-a-protocol-they-need-a-cli) (Apr 14, 2026): 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.
- [Claude Code's Leak Reveals Anthropic's Obsession with Cognee](https://www.cognee.ai/blog/cognee-news/claude-code-leak-cognee-article) (Apr 1, 2026): 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.
- [Expanding Custom Graph Models for Reliable Agent Memory & Retrieval](https://www.cognee.ai/blog/deep-dives/expanding-custom-graph-models-for-reliable-agent-memory-and-retrieval) (Mar 26, 2026): 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.
- [Memory as a Harness: Turning Execution Into Learning](https://www.cognee.ai/blog/deep-dives/memory-as-a-harness-turning-execution-into-learning) (Mar 24, 2026): Memory as a Harness: Turning Execution Into Learning
- [Grounding AI Memory: How Cognee Uses Ontologies to Build Structured Knowledge](https://www.cognee.ai/blog/deep-dives/grounding-ai-memory) (Mar 17, 2026): Learn how ontology-based validation grounds AI memory in structured knowledge graphs. Reduce entity duplication and boost retrieval quality. Try Cognee now.
- [Building Self-Improving Skills for Agents](https://www.cognee.ai/blog/deep-dives/building-self-improving-skills-for-agents) (Mar 13, 2026): 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.
- [ScrapeGraphAI + Cognee: Turn Live Web Data Into a Knowledge Graph](https://scrapegraphai.com/blog/scrapegraphai-cognee) (Mar 10, 2026): 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.
- [Structure Your Skills with Cognee](https://www.cognee.ai/blog/tutorials/structure-your-skills-with-cognee) (Mar 10, 2026): 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.
- [OpenClaw Agents: 3 Viral Use Case Ideas Powered by Cognee](https://www.cognee.ai/blog/integrations/openclaw-agents-and-cognee) (Mar 6, 2026): 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.
- [How Cognee Builds AI Memory](https://www.cognee.ai/blog/fundamentals/how-cognee-builds-ai-memory) (Feb 24, 2026): 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.
- [Cognee Raises $7.5M Seed to Build Memory for AI Agents](https://www.cognee.ai/blog/cognee-news/cognee-raises-seven-million-five-hundred-thousand-dollars-seed) (Feb 19, 2026): Cognee raises $7.5M seed led by Pebblebed to build the open-source memory layer for AI agents—backed by founders of OpenAI and Facebook AI Research.
- [What OpenClaw is and how we give it memory with cognee](https://www.cognee.ai/blog/integrations/what-is-openclaw-ai-and-how-we-give-it-memory-with-cognee) (Feb 6, 2026): Learn how OpenClaw's Markdown memory works, where it falls short, and how a Cognee plugin adds knowledge-graph recall, indexing, and smarter retrieval.
- [Context Graphs: Why Agent Memory Needs World Models and Behavioral Validation](https://www.cognee.ai/blog/deep-dives/context-graphs-world-models-and-behavioral-validation) (Jan 19, 2026): Decision traces aren't enough for agent memory. Learn how world models and behavioral validation create AI that predicts outcomes. Build smarter agents.
- [AI Agent Memory: A Complete Guide](https://www.cognee.ai/blog/fundamentals/ai-agent-memory) (Jan 7, 2026): 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.
- [Long-Term Knowledge for AI Agents: Why Memory Alone Isn't Enough](https://www.cognee.ai/blog/deep-dives/long-term-knowledge-ai-agents) (Jan 7, 2026): 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.
- [AI Agent Memory Benchmarks: Cognee vs. Mem0, Graphiti, and LightRAG](https://www.cognee.ai/blog/deep-dives/knowledge-graph-memory-benchmarks) (Jan 7, 2026): 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.
- [What Goes Into an AI Agent Knowledge Base, and What Doesn't](https://www.cognee.ai/blog/fundamentals/ai-agent-knowledge-base) (Jan 7, 2026): 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.
- [Claude Agent SDK × cognee: Persistent Memory via MCP (Without Prompt Bloat)](https://www.cognee.ai/blog/integrations/claude-agent-sdk-persistent-memory-with-cognee-integration) (Dec 23, 2025): Add persistent memory to Claude Agent SDK using Model Context Protocol (MCP) + cognee tools—store once, retrieve anytime without prompt bloat. Try it now!
- [n8n × cognee: Add AI Memory to Any Workflow Automation](https://www.cognee.ai/blog/integrations/n8n-cognee-integration-build-workflows-with-memory) (Dec 18, 2025): 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!
- [Beyond Recall: Building Persistent Memory in AI Agents with Cognee](https://www.cognee.ai/blog/tutorials/beyond-recall-building-persistent-memory-in-ai-agents-with-cognee) (Dec 12, 2025): Learn how Cognee enables long-term memory in AI agents using knowledge graphs, vector search, and feedback-driven optimization compared to stateless RAG.
- [Google ADK × cognee: Agents That Remember What Matters ](https://www.cognee.ai/blog/integrations/google-adk-cognee-integration-build-agents-with-persistent-memory) (Dec 11, 2025): 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!
- [Cut Through the Noise: Build Your Smart News Agent with cognee](https://www.cognee.ai/blog/tutorials/ai-news-agent-with-cognee) (Dec 5, 2025): 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!
- [Competition Comparison - Form vs. Function](https://www.cognee.ai/blog/deep-dives/competition-comparison-form-vs-function) (Nov 24, 2025): Explore the balance between elegant developer experience and production-ready functionality in AI memory platforms. Learn what to prioritize when evaluating solutions.
- [Why Agent Memory Breaks (and How to Fix It)](https://www.cognee.ai/blog/deep-dives/why-agent-memory-breaks) (Nov 24, 2025): Neuroscience guides Cognee's AI memory. Bayesian brain and predictive coding turn agent logs into world model traces so multi-actor systems stay sharp reliable.
- [Coming to the Edge: Introducing cognee-RS for Private, On-Device AI Memory](https://www.cognee.ai/blog/cognee-news/cognee-rust-sdk-for-edge) (Nov 19, 2025): 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!
- [Unlock Your LLM's Time Awareness: Introducing Temporal Cognification](https://www.cognee.ai/blog/cognee-news/unlock-your-llm-s-time-awareness-introducing-temporal-cognification) (Nov 12, 2025): Temporal cognification brings time-awareness to AI memory, enabling LLMs to understand when events happened, how information evolved, and what context was relevant at any given moment.
- [Scaling Intelligence: Introducing Distributed cognee for Parallel Dataset Processing](https://www.cognee.ai/blog/cognee-news/scaling-intelligence-introducing-distributed-cognee-for-parallel-dataset-processing) (Nov 10, 2025): Distributed cognee revolutionizes processing large datasets by enabling parallel execution on remote infrastructure, slashing processing times from 8+ hours to ~45 minutes while maintaining high-quality results.
- [Connecting Models to Memory: Introducing cognee MCP for Universal AI Access](https://www.cognee.ai/blog/cognee-news/introducing-cognee-mcp) (Nov 7, 2025): Bridge cognee's AI memory and agent frameworks like LangGraph, OpenAI MCP, Anthropic MCP, and others with MCP (Model Context Protocol). Build smarter apps today!
- [BAML x cognee: Type-Safe LLMs in Production](https://www.cognee.ai/blog/integrations/structured-outputs-with-baml-and-cognee) (Oct 22, 2025): Elevate AI memory with cognee + BAML: type-safe LLM outputs powering memory for AI agents in production. Validate schemas, cut errors at scale—start building now!
- [LangGraph × cognee: Enhancing Agents with Persistent, Queryable Memory](https://www.cognee.ai/blog/integrations/langgraph-cognee-integration-build-langgraph-agents-with-persistent-cognee-memory) (Oct 15, 2025): Build AI agents with LangGraph and cognee: persistent semantic memory across sessions for cleaner context and higher accuracy. See the demo—get started now.
- [🚀 cognee Update: September 2025](https://www.cognee.ai/blog/cognee-news/cognee-september-updates) (Oct 7, 2025): Cognee September recap: AI memory upgrades, graph embeddings, new UI, and case studies. Improve context engineering and retrieval—read now and start building.
- [Multi-Tenant Ready: Introducing Dataset Sharing & Role-Based Access](https://www.cognee.ai/blog/cognee-news/product-announcement-user-management) (Oct 6, 2025): Enable role-based access control and dataset sharing in cognee to secure multi-tenant data across Kùzu and LanceDB via SDK or API. Manage AI memory permissions!
- [Even More Depth & Nuance: Announcing Advanced Weights for Enhanced Reasoning](https://www.cognee.ai/blog/cognee-news/product-announcement-memory-weights) (Oct 1, 2025): Build richer AI memory with weighted nodes and edges—enable memory layers and context engineering for recency and importance. Try Cognee for enhanced reasoning.
- [Beyond Similarity: Introducing Graph-Aware Embeddings for Even Smarter Retrieval](https://www.cognee.ai/blog/cognee-news/product-announcement-graph-embeddings) (Sep 25, 2025): Cognee introduces graph-aware embeddings: graph signals boost semantic search for faster and more precise retrievals in paid plans. Learn more and book a call.
- [Elevating AI-Driven Credit Card Insights – A Tier-1 US Bank's Semantic AI Memory Discovery](https://www.cognee.ai/blog/case-studies/tier-1-us-bank-meets-cognee-ai-memory) (Sep 23, 2025): Banking Agents meet semantic AI memory to unify credit card rules with ontology supported provenance - boosting accuracy and compliance. Read more, book a call!
- [Turning PDFs into Evidence-Based Answers: How We Built a Trustworthy Evidence Graph for UWYO](https://www.cognee.ai/blog/case-studies/evidence-graph-for-uwyo) (Sep 16, 2025): Turn scattered research into trusted context for Special Education Agent with cognee, delivering evidence with citations. Book a demo and power your domain Agent!
- [Vectors + Graphs in Practice: Field Notes from the cognee Backend](https://www.cognee.ai/blog/fundamentals/vectors-and-graphs-in-practice) (Sep 15, 2025): Pair a vector database for semantic recall with a graph database for explainable paths and provenance in GraphRAG pipelines. See trade-offs and tips - read now.
- [Announcing the new cognee UI: Local & Cloud Notebooks, Graph Explorer](https://www.cognee.ai/blog/cognee-news/product-announcement-cognee-ui) (Sep 12, 2025): Simplify AI memory with cognee UI—notebooks, local + cloud sync, Graph Explorer, works with your databases. Deploy in seconds and start building smarter today!
- [Smart Networks, Smarter Students: How cognee Connected 40,000 German Learners](https://www.cognee.ai/blog/case-studies/cognee-knowunity-connects-learners) (Sep 11, 2025): 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.
- [Announcing Auto-Optimization: Self-Tuning AI Memory from Real User Feedback](https://www.cognee.ai/blog/cognee-news/product-announcement-auto-optimization) (Sep 10, 2025): AI memory gets smarter with real user feedback; auto-optimizing knowledge graphs boost search relevance and reduce manual tuning. See how it works and try it now!
- [🚀 Meet the Memify Pipeline — The Future of Post-Processing for Knowledge Graphs](https://www.cognee.ai/blog/cognee-news/product-update-memify) (Sep 9, 2025): Memify is a modular pipeline that keeps your knowledge graph evolving and speeds vector database updates for relevance and speed. Explore docs, join the beta now!
- [🚀 cognee Update: August 2025](https://www.cognee.ai/blog/cognee-news/cognee-august-updates) (Sep 3, 2025): cognee August updates: Amazon Neptune integration, n8n for Cognee Cloud, community adapters, time-aware and self-improving graph, graph embeddings, and more!
- [AI Memory in 5 Scenes — From Generic GPT to GraphRAG Greatness](https://www.cognee.ai/blog/fundamentals/ai-memory-in-five-scenes) (Aug 20, 2025): Explore how AI memory evolves from base LLM to Graph-aware RAG using Cognee’s open-source memory engine. Learn the transformation—read now on cognee!
- [Connecting the Dots: How cognee Links Concepts & Documents with a Graph-Based Approach](https://www.cognee.ai/blog/fundamentals/cognee-links-documents) (Aug 20, 2025): Learn how graph-based AI memory links concepts for smarter retrieval in Cognee. Watch our demo and start building AI that truly remembers and connects ideas.
- [Build graph-native RAG with cognee and Amazon Neptune Analytics](https://www.cognee.ai/blog/deep-dives/build-graph-native-rag-with-cognee-and-amazon-neptune-analytics) (Aug 15, 2025): Learn how to build production-ready graph-native RAG systems using cognee and Amazon Neptune Analytics. Store embeddings on graph nodes and query with openCypher for semantic recall and multi-hop traversal in a single managed service.
- [Amazon Neptune now integrates with Cognee for graph-native memory in GenAI Applications](https://aws.amazon.com/about-aws/whats-new/2025/08/amazon-neptune-cognee-genai-applications/) (Aug 15, 2025): Discover more about what's new at AWS with Amazon Neptune now integrates with Cognee for graph-native memory in GenAI Applications.
- [Pluggable Observability for Semantic Workflows: cognee × Keywords AI](https://www.cognee.ai/blog/deep-dives/observability-for-semantic-workflows) (Aug 15, 2025): Implement span-level LLM observability in semantic workflows using cognee + Keywords AI. Trace every step, debug faster, and optimize pipelines today.
- [🚀 cognee Update: July 2025](https://www.cognee.ai/blog/cognee-news/cognee-july-updates) (Aug 13, 2025): cognee July updates: Launched Cognee Cloud, distributed processing, enhanced authentication, improved stability, case studies across construction, education, more!
- [cognee Graduates from GitHub Secure Open Source Program](https://www.cognee.ai/blog/cognee-news/cognee-github-secure-open-source-program) (Aug 11, 2025): AI security meets open source AI memory as cognee graduates GitHub Secure Open Source, proving enterprise grade practices for AI memory. Join us—try cognee today!
- [AI Memory Meets Real-World Testing: Rethinking Traditional QA Benchmarks](https://www.cognee.ai/blog/deep-dives/ai-memory-evals-0825) (Aug 8, 2025): See how cognee performs against LightRAG, Graphiti (Zep), and Mem0 in AI memory benchmarks. Explore detailed comparisons, evaluation metrics, and try yourself!
- [DuckDB × cognee: Run SQL Analytics Right Beside Your Graph-Native RAG - MotherDuck Blog](https://motherduck.com/blog/duckdb-cognee-sql-analytics-graph-rag/) (Aug 08, 2025): SQL analytics and graph-native retrieval together, eliminating the trade-off between fast analytics and one-off RAG retrievals.
- [OpenAI’s GPT‑5 has arrived – What does it mean for AI memory?](https://www.cognee.ai/blog/fundamentals/gpt-5-release-from-openai) (Aug 8, 2025): GPT-5 is here, bringing major advances in AI memory and context engineering. Explore confirmed features, real-world limits, and what it means for workflows.
- [From Clever Prompts to AI Mastery: The Era of Context Engineering](https://www.cognee.ai/blog/fundamentals/context-engineering-era) (Jul 23, 2025): Master context engineering and AI memory to craft personalized LLM outputs, reduce token costs, and future-proof your AI agents—read the full guide now!
- [Build faster AI memory with Cognee & Redis | Redis](https://redis.io/blog/build-faster-ai-memory-with-cognee-and-redis/) (Jul 08, 2025): Developers love Redis. Unlock the full potential of the Redis database with Redis Enterprise and start building blazing fast apps.
- [🚀 cognee Update: June 2025](https://www.cognee.ai/blog/cognee-news/cognee-june-updates) (Jul 7, 2025): Explore cognee's June releases: Community vs Core split, Qdrant vector search integration, secure AI memory permissions, and SaaS beta waitlist. Join now!
- [Enabling AI memory to scale with cognee & Iceberg & Tower](https://www.cognee.ai/blog/deep-dives/iceberg-lakehouse-with-cognee-tower-ai-memory-guide) (Jun 30, 2025): Learn how Apache Iceberg supercharges your data lakehouse while Cognee powers AI memory for your AI agents, all orchestrated by Tower. Read in this guide now!
- [The Art of Intelligent Retrieval: Unlocking the Power of Search](https://www.cognee.ai/blog/deep-dives/the-art-of-intelligent-retrieval-unlocking-the-power-of-search) (Jun 9, 2025): Drive results with semantic search and knowledge graph retrieval; explore AI retrievers, vector databases, and GraphRAG to turn data into answers—read now!
- [Knowledge Graph Powered Qdrant FAQ Assistant with cognee](https://www.cognee.ai/blog/deep-dives/knowledge-graph-powered-qdrant-faq-assistant-with-cognee) (Jun 9, 2025): Learn how to give Qdrant documentation as context to your AI assistant. This tutorial will help build a FAQ assistant using cognee MCP in your IDE. Try it now!
- [🚀 cognee Update: May 2025](https://www.cognee.ai/blog/cognee-news/cognee-may-updates) (Jun 3, 2025): Explore cognee's May 2025 updates with an agentic AI memory demo, academic paper, stability boosts, new UI, refreshed docs and more — try the features today!
- [Why File-Based AI Memory Will Power Next-Generation AI Applications](https://www.cognee.ai/blog/deep-dives/file-based-ai-memory) (Jun 3, 2025): Discover how file-based AI memory unifies fragmented data and fuels next-gen AI apps. Learn how to store and retrieve data efficiently with cognee now!
- [Querying Relational Databases with LLMs (Not Text-to-SQL)](https://www.cognee.ai/blog/deep-dives/relational-database-to-knowledge-graph-cognee-dlt) (May 23, 2025): See how cognee transforms relational databases into a knowledge graph that you can query using LLMs—unlock your data’s power with cognee, start the migration now!
- [Vector Databases Explained: A Smarter Way to Search by Meaning](https://www.cognee.ai/blog/fundamentals/vector-databases-explained) (May 21, 2025): Learn vector databases, how vector stores like Pinecone power semantic search and AI applications by indexing embeddings. Maximize their benefits with cognee now!
- [Graph Databases Explained: A Better Way to Represent Connections](https://www.cognee.ai/blog/fundamentals/graph-databases-explained) (May 14, 2025): Discover how graph databases like Neo4j build knowledge graphs, fight fraud & boost recommendations. Master nodes & edges with cognee and supercharge your data!
- [The LLM JSON Problem: From Recipe Apps to Automated Graphs](https://www.cognee.ai/blog/deep-dives/dreamify-cognee-hyperparam-framework) (Apr 24, 2025): Discover how cognee's Dreamify framework solves LLM JSON problems. Get optimized, automated AI-generated knowledge graphs and boost your AI accuracy now!
- [AI Memory Tools -  Evaluation](https://www.cognee.ai/blog/deep-dives/ai-memory-tools-evaluation) (Apr 15, 2025): Solve the AI memory problem to boost your LLM's context retention. Explore our benchmarks of Mem0, Zep/Graphiti, and Cognee. Contact us for better results!
- [🚀 cognee Update: March 2025](https://www.cognee.ai/blog/cognee-news/cognee-march-updates) (Apr 3, 2025): Ontology, effortless relational database imports, hyperparameter tuning, major performance boosts... Enhance LLM grounding and AI graph capabilities with cognee!
- [What Do Most People Get Wrong About Knowledge Graphs?](https://www.cognee.ai/blog/fundamentals/knowledge-graph-myths) (Mar 24, 2025): Explore top knowledge graph mistakes and how to fix them. Learn about semantic relationships, graph enrichment, and AI memory. Begin your smarter data journey!
- [Knowledge Graph Query Answering (KGQA) with Cognee](https://www.cognee.ai/blog/deep-dives/knowledge-graph-query-answering-with-cognee) (Mar 7, 2025): Learn how Knowledge Graph question answering, Retrieval-Augmented Generation, and AI anomaly detection drive AI-powered search & personalized recommendations.
- [Enhancing Knowledge Graphs with Ontology Integration](https://www.cognee.ai/blog/deep-dives/ontology-ai-memory) (Mar 6, 2025): Discover how integrating formal ontologies with knowledge graphs dramatically improves information retrieval, semantic understanding, and query capabilities.
- [From APIs and Relational Data to Knowledge Graphs](https://www.cognee.ai/blog/deep-dives/from-data-points-to-knowledge-graphs) (Mar 5, 2025): Build Knowledge Graphs with cognee by running efficient data pipelines, and turning API data into interconnected semantic graphs. Boost your data insights today!
- [CrewAI Memory with Cognee](https://www.cognee.ai/blog/integrations/crewai-memory-with-cognee) (Mar 3, 2025): Learn how to give CrewAI agents memory using cognee for context-aware AI applications. Discover our example research agent implementation and build your solutions.
- [Cognee GraphRAG: Supercharging Search with Knowledge Graphs and Vector Magic](https://www.cognee.ai/blog/deep-dives/cognee-graphrag-supercharging-search-with-knowledge-graphs-and-vector-magic) (Feb 20, 2025): Discover cognee GraphRAG merging knowledge graphs and vector search for accurate, context-rich answers for your LLM queries. Try cognee, improve search performance!
- [Ollama, Deepseek, and Graphs](https://www.cognee.ai/blog/deep-dives/deepseek-ollama-and-graphs) (Feb 19, 2025): Explore Ollama and Deepseek creating LLM-based knowledge graphs. We evaluated small - large models, structured data, and agent-ready data layers. Try it with cognee!
- [Cognitive Architectures for Language Agents: Explained](https://www.cognee.ai/blog/fundamentals/cognitive-architectures-for-language-agents-explained) (Feb 12, 2025): Discover how cognitive architectures enhancing LLM memory and adaptive decision-making for Agents. Learn CoALA framework for context-aware, high-performing AI today!
- [Model Context Protocol + Cognee: LLM Memory Made Simple](https://www.cognee.ai/blog/deep-dives/model-context-protocol-cognee-llm-memory-made-simple) (Feb 7, 2025): Unlock the power of cognee LLM memory with the Model Context Protocol. Learn how use cognee memory as a MCP tool to make your LLM apps accurate easily. Try it today!
- [Cognee + LanceDB: Simplifying RAG for Developers](https://www.cognee.ai/blog/integrations/cognee-lancedb-simplifying-rag-for-developers) (Jan 21, 2025): Simplify Retrieval-Augmented Generation (RAG) workflows. Graphs, vectors, and Apache Arrow help automated tests, and scale AI applications. Try cognee with LanceDB!
- [Cognee + Graphiti: Integrating Temporal-Aware Graphs](https://www.cognee.ai/blog/deep-dives/cognee-graphiti-integrating-temporal-aware-graphs) (Jan 17, 2025): Cognee integrates with Graphiti to enable temporal-aware graphs. Learn about feature enrichment, graph transformation, and how to build custom, scalable solutions!
- [cognee + LlamaIndex: Building Powerful GraphRAG Pipelines](https://www.cognee.ai/blog/integrations/cognee-llamaindex-graphrag-pipelines) (Jan 10, 2025): Learn to build GraphRAG pipelines with cognee and LlamaIndex, handling structured and unstructured data in LLM workflows for improved accuracy. Try it now!
- [LLM Memory: Integration of Cognitive Architectures with AI](https://www.cognee.ai/blog/fundamentals/llm-memory-cognitive-architectures-with-ai) (Jan 7, 2025): Discover what LLM memory is, from memory tuning to short- and long-term memory. Explore use cases for more accurate AI solutions with cognee. Learn more now!
- [Repo to Knowledge Graph: A Minimal Toy Example](https://www.cognee.ai/blog/deep-dives/repo-to-knowledge-graph) (Dec 19, 2024): Build a Python repo knowledge graph with cognee to map dependencies and unlock better coding insights. Simplify AI integration for smarter development workflows.
- [Fundraising in 2024](https://www.cognee.ai/blog/cognee-news/fundraising-in-2024) (Dec 13, 2024): Discover how fundraising in 2024 in the AI infrastructure space looks like and how we went about securing 1.5m in funding. Join us in our journey growing cognee!
- [Memory Fragment Projection: Building a Personalized Knowledge Graph Layer with Cognee](https://www.cognee.ai/blog/deep-dives/memory-fragment-projection-from-graph-databases) (Dec 9, 2024): Learn creating personalized knowledge graphs through memory fragment projection. Use cognee's retrieval process and GraphRAG pipelines for better data exploration.
- [Enhancing LLM Responses with Graph-Based Retrieval and Advanced Chunking Techniques](https://www.cognee.ai/blog/deep-dives/enhancing-llm-responses-with-graph-based-retrieval-and-advanced-chunking-techniques) (Dec 3, 2024): Discover how integrating graph-based retrieval methods and chunking techniques can enhance the relevance and precision of responses generated by LLMs. Try it now!
- [Understanding Structured and Unstructured Data: A Comprehensive Guide](https://www.cognee.ai/blog/fundamentals/structured-vs-unstructured-data) (Nov 23, 2024): Explore the key differences between structured and unstructured data, their applications, and best practices. Learn more about data types in modern analytics.
- [Big News: cognee raises $1.5 million to transform AI data management!](https://www.cognee.ai/blog/cognee-news/funding-and-web-site-launch) (Nov 18, 2024): We're excited to announce that cognee has raised $1.5 million in funding! 🎉  Our mission is to make AI data management simpler, cost-effective, and scalable for you.
- [Case study with Dynamo.fyi](https://www.cognee.ai/blog/case-studies/cognee-case-study-with-dynamo) (Nov 8, 2024): Instead of developing in isolation, we choose collaborating with partners to build a foundation of practical examples, Find out how we reached 75% answer relevancy. 
- [Going beyond Langchain + Weaviate: Level 4 towards production](https://www.cognee.ai/blog/deep-dives/from-demo-to-production-4) (Aug 1, 2024): For a robust RAG model, we use memory and integrate with keepi.ai. Learn human-inspired cognitive processes and data management with a focus on graph databases!
- [Going beyond Langchain + Weaviate: Level 3 towards production](https://www.cognee.ai/blog/deep-dives/from-demo-to-production-3) (Aug 1, 2024): Learn adjusting parameters like document quantity and chunk size to enhance RAG. Explore challenge like reliably linking memories and organizing memory elements.
- [Going beyond Langchain + Weaviate: Level 2 towards Production](https://www.cognee.ai/blog/deep-dives/from-demo-to-production-2) (Aug 1, 2024): Level 2 AI integrates Memory Layer, FastAPI, Langchain & Weaviate. Our POC enables PDF uploads, translations & smart data retrieval. Try it with us now!
- [Going beyond Langchain + Weaviate and towards a production ready modern data platform](https://www.cognee.ai/blog/deep-dives/from-demo-to-production-1) (Aug 1, 2024): In 2023, 7,000 AI projects launched, fueled by model advances and collaboration. Yet, many remain basic, highlighting the need for a unified LLM platform.
- [Exploring AI Memory on the AI Engineering Podcast](https://www.cognee.ai/blog/cognee-news/exploring-ai-memory-on-the-ai-engineering-podcast): Learn about differences between episodic and semantic memory systems, real-world use cases, challenges. In the AI Engineering Podcast, explore cognee's AI memory.

## Academy articles

- [What Is an LLM? Large Language Models (LLMs) Explained](https://www.cognee.ai/academy/chapter-1/how-llms-work): What an LLM is, how large language models work, and where they're used — from training data and the transformer architecture to fine-tuning and real-world applications.
- [AI vs. Machine Learning: What's the Difference Between AI and ML?](https://www.cognee.ai/academy/chapter-1/ai-vs-ml): The difference between AI and ML in plain English — compare definitions, scope, goals, and examples, and see how AI systems and ML models work together.
- [What is AI Memory?](https://www.cognee.ai/academy/chapter-1/what-is-ai-memory): Understanding short-term, long-term, and external memory for LLMs.
- [From Data to Knowledge: Why Context Matters in AI](https://www.cognee.ai/academy/chapter-1/from-data-to-knowledge): How structure and context turn raw data into useful knowledge for LLMs.
- [The Hidden Engine: How AI Infrastructure Powers Tomorrow's Innovations](https://www.cognee.ai/academy/chapter-1/ai-infrastructure-hidden-engine): Key differences and components across the AI lifecycle from training to serving.
- [Graph Databases 101: Navigating Networks in a Data-Driven World](https://www.cognee.ai/academy/chapter-2/graph-databases-101): Nodes, edges, and properties — a beginner's guide to graph databases.
- [Vector Databases 101: The Key to Semantic Search and AI Insights](https://www.cognee.ai/academy/chapter-2/vector-databases-101): Embeddings, similarity search, and ANN indexes explained.
- [Graph vs Vector Database: The Storage Duo Powering Modern AI](https://www.cognee.ai/academy/chapter-2/graph-vs-vector-databases): When to use each, strengths, and trade-offs in LLM applications.

## Developer resources

- [Documentation (developer portal)](https://docs.cognee.ai): Full developer documentation, guides, and reference for building with cognee.
- [Quickstart](https://docs.cognee.ai/getting-started/quickstart): Install cognee and build your first memory pipeline in minutes.
- [REST API reference](https://docs.cognee.ai/api-reference/introduction): REST API endpoints, request/response schemas, and authentication (API keys and Bearer tokens).
- [OpenAPI / Swagger spec](https://api.aws.cognee.ai/docs): Interactive OpenAPI (Swagger) explorer auto-generated from the cognee Cloud API specification.
- [Python SDK reference](https://docs.cognee.ai/python-api): Reference for the cognee Python SDK.
- [MCP server](https://docs.cognee.ai/cognee-mcp/mcp-overview): cognee MCP server: expose cognee memory to MCP-compatible agents, IDEs, and tools.
- [cognee Cloud](https://docs.cognee.ai/cognee-cloud/overview): Managed cloud developer portal: API keys, dashboards, and hosted memory infrastructure.
- [GitHub](https://github.com/topoteretes/cognee): Source code, issues, and examples for the open-source memory engine.

Last updated: 2026-06-10