Neo4j blog

Introducing Neo4j GraphAware Financial Crime Intelligence

Move from fragmented data to connected intelligence, for better detection, deeper investigations, and defensible decisions.

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

Production-proofing your Neo4j Cypher MCP server

Going meta: Two years of knowledge graphs

Explore iterative refinement for Text2Cypher

Verify Neo4j Cypher queries with CyVer

Managing risk in a manufacturing plant with Neo4j Aura graph analytics

Illustration of AI at the center of the bullseye

GenAI
News

Neo4j invests $100 million in GenAI and launches key agentic AI innovations

Illustration showing how vector similarity, Cypher templates, and text-to-Cypher meet to create the Aura Agent

GenAI
News

Neo4j Aura Agent: Create your own GraphRAG agent in minutes

Reinventing retail: How Neo4j, Oneture, and AWS can power multi-agent store advisers

Bolster your cybersecurity by visualizing attack graphs with Neo4j & G.V()

Knowledge graph generation

Introducing ToolsRetriever in the Neo4j GraphRAG Python package

The Neo4j Startup Program: Tomorrow’s AI unicorns build on Neo4j