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

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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

Knowledge Graphs

How knowledge graphs drive more sales with real-time recommendation engines

Neo4j’s Emil Eifrem and FirstMark’s Matt Turck on the graph database explosion

Graph embeddings: AI that learns from your data to solve problems

Neo4j as an embedded database: The key use cases of graph databases

Emil Eifrem BizTech Interview

Emil Eifrem

Emil Eifrem on Neo4j’s rise, rapid growth in APAC, and the thrill of competition

Check out Emil's statement on Neo4j's largest funding round in database history.

Neo4j raises the largest funding round in database history

Neo4j has been selected as the winner of the “Graph DBS Solution of the Year” award by Data Breakthrough!

News

Neo4j honored with 2021 Data Breakthrough Award for graph DBS solution of the year

Graph data platforms: A brief introduction

Graph algorithms for community detection & recommendations

Check out this interview with Charlie Beveridge of Accenture.

Knowledge graphs & navigating the future of AI: An interview with Charlie Beveridge of Accenture

Why leading telecoms use Neo4j: The 5-minute interview with Jesús Barrasa, global director of telecoms at Neo4j

Watch this webinar on how Neo4j's graph platform improves the representation of network automation

Network & IT operations

Graph-based, real-time inventory & topology for network automation [Video]