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

Independent study: GraphRAG makes AI agents 80% more truthful

Illustration representing a context graph for AI agent memory

Agentic AI

What is a context graph?

Welcome, GraphAware

Featured voices

Emil Eifrem

CEO & Founder, Neo4j

See all articles

Sudhir Hasbe

Chief Product Officer, Neo4j

See all articles

Philip Rathle

Chief Technology Officer, Neo4j

See all articles

Most recent

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

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