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

Illustration representing a context graph for AI agent memory

Agentic AI

What is a context graph?

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

Catch this week's GraphCast on the Bloom Series, which features some of Neo4j Bloom's best features.

Graph visualization

GraphCast: Bloom series

Learn more about GraphConnect 2020 call for papers.

GraphConnect 2020: Call for papers closing November 15

Learn how graphs add business value.

How Boston Scientific improves manufacturing quality using graph analytics

What is CCPA compliance? A definition

Overcoming CCPA compliance challenges: What is CCPA?

Global GraphHack 2019 winners announced.

Announcing the Global GraphHack winners!

Learn more about Neo4j's new Educator Program for classroom instruction.

Empowering educators: Neo4j’s new program for classroom instruction

Turning data into actionable knowledge: 5-minute interview with David Meza

Global GraphHack 2019 winners announced.

Check out some global GraphHack projects & help us pick the winners!

Learn more about the new GQL project.

Cypher & GQL

Bringing the newly approved GQL project into focus

Catch this week's GraphCast: How Lyft Drives Data Discovery

GraphCast: How Lyft drives data discovery

Check out this interview with Lyft about using Neo4j.

Graph Data Science

Live from Lyft: Q&A with Mark Grover, product manager at Lyft

Learn how to innovate on real-time recommendations with Neo4j.

5 ways to innovate and delight users with real-time recommendations