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.

Visualization of how Neo4j Graph Intelligence reveals hidden patterns in massive datasets

How Graph Intelligence Drives Breakthroughs in Science and Society

iscover the best tool for context engineering and build agentic AI with MCP, knowledge graphs, GraphRAG, and practical evaluation and tracing.

Agentic AI

Best Tools for Context Engineering in Agentic AI Systems

The Data Strategy That Makes Truly Personalized Customer Experiences Possible

Featured Voices

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

Context Graphs and AI Memory Across the Globe

Meet Lenny’s Memory: Building Context Graphs for AI Agents

Agentic AI vs. Generative AI: Why Agents Need Memory, Context, and Guardrails

Why AI Teams Are Moving From Prompt Engineering to Context Engineering

Agentic AI

Hands On With Context Graphs And Neo4j

What Is Context Engineering in AI Agents? A Practical Guide

Model Context Protocol (MCP)

GenAI

What Is Model Context Protocol (MCP)?

Context-Aware Knowledge Graph Chatbot With GPT-4 and Neo4j

You Want Some Join Context? Neo4j Has You Covered

Knowledge Graph book

Knowledge Graphs: Data in Context for Responsive Businesses [New Book]

Learn about responsible AI and gain practical tips.

Responsible AI: The Critical Need for Context (and Practical Tips)

Discover why we need to guide responsible AI.

Real Examples of Why We Need Context for Responsible AI