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.

Illustration of how a supplier graph connectes materials, routes, and contracts

What’s invisible in your supply chain could cost you

Agentic AI

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

Agent Memory

A knowledge layer for your agentic systems on Google Cloud

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

GQL: The ISO Standard for Graphs Has Arrived!

GQL: The ISO Standard for Graphs Has Arrived

Building RAG Applications With the Neo4j GenAI Stack: A Comprehensive Guide

Building RAG Applications With the Neo4j GenAI Stack: A Comprehensive Guide

Node embeddings in a knowledge graph.

The Future of Knowledge Graph: Will Structured and Semantic Search Become One?

What is retrieval-augmented generation RAG)?

GenAI

What Is Retrieval-Augmented Generation (RAG)?

Entity resolved knowledge graphs: A tutorial

Entity Resolved Knowledge Graphs: A Tutorial

GQL, the future of graph databases is here.

ISO GQL: A Defining Moment in the History of Database Innovation

LangChain Library now supports Neo4j vector index.

LangChain Library Adds Full Support for Neo4j Vector Index

Developer

Maximizing Your Neo4j Project’s Potential: An In-depth Guide to Solution Assessment

Graph Data Models for RAG Applications

Neo4j Brings GraphRAG Capabilities for GenAI to Google Cloud

Neo4j Is Now SOC2 Type 2 Compliant

Enhancing RAG with Neo4j Cypher and Vector Templates Using LangChain Agents