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

Neo4j Graph Data Science Library 1.6: Fastest path to production

Visualized IP asset information and its lineage influencing dependencies like inventions, products, revenues, IP filing strategy, and related legal cases, i.e. infringements and litigation.

The bigger picture: See IP assets as an interactive dependencies map

Webinars, Demos, Connections – Oh My!

Graph Data Science

Webinars, demos, connections – oh my!

Developer

Running Django-Neomodel within a Docker container

APOC hidden gems: What you could have missed

Emil Eifrem on the Origins of Neo4j and the Ubiquity of Graphs

Emil Eifrem

Emil Eifrem on the origins of Neo4j and the ubiquity of graphs

Graph Data Science

Spreading the word: The 5-minute interview with Reshama Shaikh

How the financial services industry uses graph technology [Infographic]

Don't forget to register for NODES 2021 – the largest graph developer conference of the year.

NODES

GraphCast: The largest graph developer conference is back for 2021!

Celebrating Asian American and Pacific Islander Heritage Month at Neo4j

News

Celebrating Asian American and Pacific Islander Heritage Month at Neo4j

Overview of the Neo4j graph data platform

Discover the top 5 graph analytics takeaways from Gartner's Data & Analytics Summit

Top 5 graph analytics takeaways from Gartner’s Data & Analytics Summit