Neo4j blog

Welcome, GraphAware

Neo4j is acquiring GraphAware, our longtime partner and a leading provider of intelligence analysis software for government agencies.

New research finds enterprises earn 230% ROI with Neo4j Graph Intelligence Platform

Context graphs: Why AI agents need three types of memory

Introducing Neo4j Virtual Graph: Graph reasoning on the data you already have

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

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

Agentic AI

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

Introducing Neo4j Agent Skills

Introducing Asynchronous I/O in Neo4j using io_uring

SumoDB in Neo4j: Graph Analytics of Grand Sumo

Building stateful AI: Integrating Aura Agent lifecycle with MCP and persistent memory

Precise economic policy in a world of chaos

GraphAcademy content is moved into Neo4j Aura, and an Aura Agent used to provide MCP server access to VS Code, Cursor, and Claude agents.

Can I use Aura Agents to create an MCP enabled teacher?

Graph database

From agents to analytics: What’s new from Neo4j on Google Cloud

Integrating Neo4j with Google Genkit: A Practical Guide

Graph database

Connected intelligence: Scaling graph-powered reasoning across the AI ecosystem

From Identity Vacuum to Identity Driven Access Control: Securing LLM Agents in the Enterprise

Developer

“Boost” the power of your AI agents: Integrating Neo4j MCP with Laravel