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

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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

Watch Tilo Walter's presentation on how to harness graphs to build new business connections

The impact of graph-powered business leader social networks

Graph Data Science

Social networks in the database: Using a graph database

Demystifying graph neural networks

Watch Laura Drummer's presentation on how to use Neo4j for sentiment and social network analysis

Sentiment and social network analysis

Learn More about How Tom Sawyer Perspectives Breaks Down Criminal Networks

Breaking down crime networks with Tom Sawyer Perspectives

Graph database

What is graph technology? And why it’s the future of enterprise AI

Solve hard graph problems with Cypher 25

Analyze graphs directly in Snowflake — The wait is over

Graph database

What is a graph database?

Simplify modern application development with GraphQL on Neo4j AuraDB

GenAI
News

Neo4j + Google Cloud: Powering the next generation of AI and cloud innovation

Top 10 graph database use cases (with real-world case studies)