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

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

Graphs for business transformation: The 5-minute interview with Trinette Brownhill

Knowledge Graph book

Knowledge graphs: Data in context for responsive businesses [New Book]

Check out this interview with Robert Allison of Kineviz.

Graph analytics for business users: 5-minute interview with Robert Allison of Kineviz

Discover how real-time recommendations support a number of different use cases that translate into business value.

Real-time recommendations

Powering recommendations with a graph database: Proven business benefits [+ case studies]

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

The impact of graph-powered business leader social networks

Watch Andy Mulholland's Talk on How Internet of Things (IoT) Graphs Intersect with Business Needs

IoT: Where do graphs fit with business requirements

Connected Intelligence: Operationalizing Production-Grade Graph Solutions Across Enterprise Networks

Developer

What 40 AI Agents Revealed About the Future of Graph Intelligence

A workbench for teams to query, explore, and visualize graph data

A workbench for teams to query, explore, and visualize graph data

Zero-Copy Graph Reasoning on Snowflake: Getting Started With Neo4j Virtual Graph

Zero-Copy Graph Reasoning on Snowflake: Getting Started With Neo4j Virtual Graph

Developer

Graph and Lakehouse, Friends at Last

Knowledge graph

Taxonomy vs. ontology vs. knowledge graph: What’s the difference?