Neo4j blog

Agentic AI

The knowledge layer for enterprise AI

A manifesto for context-rich enterprise AI

Chart of the knowledge layer comprising ontologies, data, and memory

Scaling Karpathy’s LLM wiki: Why your knowledge base needs a graph

Independent study: GraphRAG makes AI agents 80% more truthful

Context graph diagram illustrating decision traces for AI agents

Agentic AI

What are decision traces in a context graph? How they reveal agentic reasoning

Featured voices

Emil Eifrem

CEO & Founder, Neo4j

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Sudhir Hasbe

Chief Product Officer, Neo4j

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Philip Rathle

Chief Technology Officer, Neo4j

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Most recent

Diagram of OneLake, Microsoft Fabric, and Neo4j.

News

Announcing general availability of Neo4j Graph Intelligence for Microsoft Fabric

Streamline data ingestion with the Neo4j Aura Import API

Security

Use sentiment analysis to understand risk appetite

New GraphAcademy course: Aura Fundamentals

US government building

From data chaos to clarity: How connected data can improve US government decision-making

A constellation of Orion represented as a graph with nodes and relationships.

GenAI

Advanced RAG techniques for high-performance LLM applications

Solve hard graph problems with Cypher 25

Find similar patient journeys with Neo4j Aura graph analytics

Analyze graphs directly in Snowflake — The wait is over

How a $28 part can bring down a $5M machine—and how GenAI stops it

Production-proofing your Neo4j Cypher MCP server

Going meta: Two years of knowledge graphs