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

Dual indexing Neo4j and Solr for a unified platform

Top 10 use cases: Identity and Access Management

Machine learning

Graph in the auto industry: The 5-minute interview with Elena Kohlwey

Neo4j Browser embraces the Monaco Editor

Top 10 use cases: Data lineage

Catch this week's GraphCast: Presenting succinct explanations on graphs and graph databases.

Graph Data Science

GraphCast: Introduction to graph theory: What is a graph?

Take this new certification exam to become a certified Neo4j Graph Data Science professional.

New certification exam available: Neo4j Graph Data Science

Master data management

Top 10 use cases: Master Data Management

Graphs in China: 5-minute interview with Richard Wu & George Zhang

NODES

Unearthing historical networks using Neo4j and archival documents

Network & IT operations

Top 10 use cases: Empowering network and IT operations management

Sandbox spring cleaning