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

See all articles

Sudhir Hasbe

Chief Product Officer, Neo4j

See all articles

Philip Rathle

Chief Technology Officer, Neo4j

See all articles

Most recent

RAG tutorial: How to build a RAG system on a knowledge graph

Quickly build a React agent with LangGraph and MCP

IP filtering for Neo4j Aura—Simpler and stronger network security

Using GraphQL middleware with Neo4j GraphQL

Query, chomp, repeat

News

Sudhir Hasbe named president, technology at Neo4j

Exploring the Neo4j Spatial plugin: Custom procedures for spatial analysis

Neo4j MCP Server: Your ADHD-friendly house-moving assistant

Why I’m replacing my RAG-based chatbot with agents

How graph-powered supply chain improves sustainability

Exploring Neo4j Spatial: Path intersections using AIS data

Unleashing the power of schema: What’s new in the Neo4j GraphRAG package for Python