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

Augmented intelligence: 5-minute interview with Demian Bellumio, NEORIS

Neo4j certified professionals now get access to advanced-level virtual training sessions

Learn how ETL tools work, including basics of graph ETL which converts RDBMS to graph databases.

Graph Data Science

Graph databases for beginners: The basics of graph ETL

Graph-Powered Recommendations: How Smart Recommendations Drive Value

Learn about social knowledge graphs to improve remote collaboration.

Knowledge graph

GraphCast: How a social knowledge graph improves remote collaboration

Learn about practical applications of Neo4j 4.0.

Practical applications of Neo4j 4.0

Stay agile with graph by shifting left and designing consistent architecture that eliminates migrations.

Being in Control and Staying Agile with Graph Requires Shifting Left at ING

Financial Fraud Detection with Graph Data Science: Identifying Fraud Rings

Lean Graph Data Models Drive Fast Innovation: A Fireside Chat with David Fox, Senior Software Engineer at Adobe

Learn about Neo4j Bloom, a data visualization tool

Graph visualization

Neo4j Is in Bloom Everywhere This Spring

Learn how Previa is using Neo4j to reimagine health care.

How Previa is reimagining healthcare

Financial Fraud Detection with Graph Data Science: Identifying First-Party Fraud