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

What is AI-ready data? How a knowledge layer gets you there

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

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

Enhancing the accuracy of RAG applications with knowledge graphs