Neo4j Blog

From data to intelligence: Why every enterprise needs an AI knowledge layer

The knowledge layer maps and resolves data so AI can accurately answer questions, make better decisions, and be explainable.

4 min read

Agent tools: What they are, how they work, and how AI agents use them

13 min read
Agent Memory

A knowledge layer for your agentic systems on Google Cloud

4 min read

The data strategy that makes truly personalized customer experiences possible

9 min read

Emil Eifrem

CEO & Co-Founder, Neo4j, Inc.

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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

Now available: dedicated Neo4j field engineers empowering AI startups

5 min read

Introducing Create Context Graph

13 min read

How a Neo4j semantic layer makes your Text-to-SQL agent smarter and cheaper

12 min read
NODES 2026 Call for Papers open until June 15, 2026

NODES 2026 Is Coming Up: Submit Your Talk

2 min read
ServiceNow+Neo4j

Turning ServiceNow Data into Connected Enterprise Intelligence

11 min read

Building Graph-Based Agentic Systems: Failures, Fixes, and How the Answer Gets There — Part 2

20 min read

SumoDB in Neo4j: Graph Analytics in Snowflake — Part 2

5 min read
Get start With Neo4j Aura Cloud Graph Database Network

Getting Started With Neo4j Aura: A Guide to the Leading Cloud Graph Database

3 min read
Learn what agentic RAG is, how it works, which design patterns to use, and when it beats traditional RAG.

Agentic RAG: What it is, how it works, and when to use it

17 min read

Introducing Neo4j Agent Skills

5 min read

Introducing Asynchronous I/O in Neo4j using io_uring

5 min read

SumoDB in Neo4j: Graph Analytics of Grand Sumo

5 min read