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.

See All Articles

Sudhir Hasbe

Chief Product Officer, Neo4j

See All Articles

Philip Rathle

Chief Technology Officer, Neo4j

See All Articles

Most Recent

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

Developer

Boundary Graph: Exploring the IPL Through the Lens of Graphs

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

Why LeBron James Shouldn’t Drive Your Recommendations: The Intuition Behind the Jaccard Coefficient

Graph Database

Building a Seamless Data Pipeline with Neo4j CDC and GCP Pub/Sub

Getting Started With MCP Servers: A Technical Deep Dive

Scaling Without Limits: Infinigraph Is Now Generally Available

Vector search with filters in Neo4j v2026.01 (Preview)

Powering India’s AI Future with Graph Intelligence

Powering India’s AI Future with Graph Intelligence

Empowering Microsoft Agent Framework with Neo4j Knowledge Graphs

Developer

How to Deploy The Neo4j MCP Server to GCP Cloud Run

Why AI Teams Are Moving From Prompt Engineering to Context Engineering