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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

Learn more about the GraphQL Foundation and building fullstack graph applications.

Neo4j joins GraphQL foundation as a founding member

Check out all who participated in Neo4j's Graph Visualization Day.

Graph V-Day (Graph Visualization Day) recap

Check out this interview with Weidong Yang, CEO of Kineviz.

Bringing wonder to data: 5-minute interview with Weidong Yang

Learn more about GraphXR, which enables graph exploration in virtual reality.

Graph visualization

Adding GraphXR as a graph app in Neo4j Desktop

Free Download O'Reilly Graph Algorithms book

Graph algorithms in Neo4j: Label propagation

Graph Data Science

Google Summer of Code for graph-based software analytics

Check out this 5-minute interview with James Gray, Direct of Product for Big Data at Phunware.

Mobile experiences at scale: 5-minute interview with James Gray

Discover the benefits of our updated Neo4j online training course.

Cypher & GQL

Check out the newly revamped intro to Neo4j online training course

Free Download O'Reilly Graph Algorithms book

Graph algorithms in Neo4j: Weakly connected components

Check out this 5-minute interview with Alex Babeanu from Nulli.

Simplifying identity management: 5-minute interview with Alex Babeanu

Check out this data model on a choose your own adventure series.

Vampire Express: Graphing a classic ’80s choose your own adventure story

Watch Irena Iriarte-Carretero's presentation on mapping ontologies in graphs for personalization.

Mapping ontologies in graphs for personalization