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

See all articles

Sudhir Hasbe

Chief Product Officer, Neo4j

See all articles

Philip Rathle

Chief Technology Officer, Neo4j

See all articles

Most recent

Tim Nash Explains How to More Efficiently Query Custom Post Types in WordPress Using Neo4j

Cypher & GQL

Giving WordPress Some Relationship Advice with Neo4j [Community Post]

Developer

Solve scheduling problems with relationship coloring and Neo4j

Entity linking and relationship extraction with Relik in LlamaIndex

Main hall of the East Building of the National Gallery of Art, Washington, DC.

Graph databases explained: How relationships change everything

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

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

Learn more about the Pypher library that allows you to express Cypher queries in pure Python

Cypher & GQL

Now you can express Cypher queries in pure Python using Pypher [Community Post]

News

Sustainable competitive advantage: Enterprises unlock business value in their data relationships

Free Download O'Reilly Graph Algorithms book

Graph algorithms in Neo4j: Neo4j graph analytics

Your AI Agent Forgets Everything. So We Taught It to Remember — With a Graph.

Writing Cypher Queries That Don’t Lose Your Data

Understanding GraphSAGE

From first graph algorithm experiment to production with Aura Graph Analytics