The Cognee Blog

Technical Note: Understanding the Token Cost of Persistent AI Memory

Technical Note: Understanding the Token Cost of Persistent AI Memory

Behind the Viral Numbers: How We Got 7x Cheaper and 145% Better

Behind the Viral Numbers: How We Got 7x Cheaper and 145% Better

cognee 1.0: The Open-Source Memory Platform for AI Agents

cognee 1.0: The Open-Source Memory Platform for AI Agents

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All postsNewsFundamentalsCase studiesDeep divesTutorialsIntegrations
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IntegrationsFeb 6, 2026

What OpenClaw is and how we give it memory with cognee

Learn how OpenClaw's Markdown memory works, where it falls short, and how a Cognee plugin adds knowledge-graph recall, indexing, and smarter retrieval.
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Deep DivesJan 19, 2026

Context Graphs: Why Agent Memory Needs World Models and Behavioral Validation

Decision traces aren't enough for agent memory. Learn how world models and behavioral validation create AI that predicts outcomes. Build smarter agents.
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FundamentalsJan 7, 2026

AI Agent Memory: A Complete Guide

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.
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Deep DivesJan 7, 2026

Long-Term Knowledge for AI Agents: Why Memory Alone Isn't Enough

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.
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Deep DivesJan 7, 2026

AI Agent Memory Benchmarks: Cognee vs. Mem0, Graphiti, and LightRAG

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.
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FundamentalsJan 7, 2026

What Goes Into an AI Agent Knowledge Base, and What Doesn't

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.
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IntegrationsDec 23, 2025

Claude Agent SDK × cognee: Persistent Memory via MCP (Without Prompt Bloat)

Add persistent memory to Claude Agent SDK using Model Context Protocol (MCP) + cognee tools—store once, retrieve anytime without prompt bloat. Try it now!
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IntegrationsDec 18, 2025

n8n × cognee: Add AI Memory to Any Workflow Automation

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!
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TutorialsDec 12, 2025

Beyond Recall: Building Persistent Memory in AI Agents with Cognee

Learn how Cognee enables long-term memory in AI agents using knowledge graphs, vector search, and feedback-driven optimization compared to stateless RAG.
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Latest News

cognee 1.0: The Open-Source Memory Platform for AI Agents
cognee 1.0 is the first open-source memory platform built around a memory-native API — remember, recall, improve, forget — with full data ownership and deployment flexibility from managed cloud to edge.
Claude Code's Leak Reveals Anthropic's Obsession with Cognee
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.
Cognee Raises $7.5M Seed to Build Memory for AI Agents
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.

Latest Fundamentals

AI Knowledge Base: Building a Retrieval-Ready Knowledge Layer
An AI knowledge base needs more than stored documents. Source context, entity relationships, and plural retrieval strategies are what turn stored data into reliable, agent-ready knowledge.
What Is a Knowledge Base? (and Why Most of Them Stop Working)
A knowledge base is a centralized system for storing reusable information — but most fail because of ownership gaps, drift, and no clear sense of what actually belongs in them.
LLM vs Generative AI: Comparing Models, Memory, and Architecture
Generative AI and LLMs are not the same thing. Learn the real difference, why architecture matters more than model size, and what memory and retrieval actually do.

Latest Case studies

Elevating AI-Driven Credit Card Insights: A Tier-1 US Bank's Semantic AI Memory Discovery
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
Turn scattered research into trusted context for Special Education Agent with cognee, delivering evidence with citations. Book a demo and power your domain Agent!
Smart Networks, Smarter Students: How cognee Connected 40,000 German Learners
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.

Latest Deep dives

Technical Note: Understanding the Token Cost of Persistent AI Memory
Persistent memory trades an upfront ingestion cost for cheaper queries. We measure where the tokens go in cognee, model the trade-off, and find break-even at roughly 23–26 repeated queries — after which the gap keeps widening.
Behind the Viral Numbers: How We Got 7x Cheaper and 145% Better
Our LinkedIn and X videos put two numbers on screen — 7x cheaper than chat and 145% better than the best alternative. Here's exactly where each one came from, linked to our BEAM report.
cognee on BEAM: SOTA Results Without a Benchmark-Specific Memory System
cognee beat SOTA on BEAM's 100k-token setting by 6.5% and matched SOTA at 10M tokens using only default open-source features — no custom benchmark-specific architecture.

Latest Tutorials

Structure Your Skills with Cognee
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.
Beyond Recall: Building Persistent Memory in AI Agents with Cognee
Learn how Cognee enables long-term memory in AI agents using knowledge graphs, vector search, and feedback-driven optimization compared to stateless RAG.
Cut Through the Noise: Build Your Smart News Agent with cognee
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!

Latest Integrations

Cut Cognee's Vector Memory by 8x with Qdrant's TurboQuant
Use Qdrant TurboQuant in cognee with one env var to shrink stored vectors by about 8x without retraining, codebooks, or per-dataset tuning.
ScrapeGraphAI + Cognee: Turn Live Web Data Into a Knowledge Graph
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.
OpenClaw Agents: 3 Viral Use Case Ideas Powered by Cognee
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.
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