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

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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

Exploring Drug Interactions: 5-Minute Interview with Amin Jalali

Learn how EY used Neo4j to design enterprise HR applications at scale.

Designing the Enterprise: HR Applications at Scale

Learn how graph technology improve the KYC process.

From Know Your Customer to Know Your Network: A Paradigm Shift Empowered by Neo4j

Rethink Your Master Data: From MDM to Innovation

Check out this tv show in which they use graph theory to solve crimes.

Graph Data Science

#GraphCast: Numb3rs and Graph Theory

Learn more about Cloud Foundry and Neo4j.

Neo4j and Cloud Foundry

Upgrade your Graph Data Science library now (or miss out on cool new features)

Master data management

Rethink Your Master Data: Addressing Governance, Risk and Compliance

Graph Data Science

The Power of Graph Data Science: 5-Minute Interview with Alicia Frame

Building the enterprise knowledge graph

Learn about Drivine, a database client for Node.js and Typescript

Introducing Drivine: Graph Database Client for Node.js and Typescript

Master data management

Rethink Your Master Data: How Graphs and MDM Intersect