Neo4j Blog

GenAI
News

Neo4j Invests $100 Million in GenAI and Launches Key Agentic AI Innovations

Neo4j announces a $100 million investment in GenAI to fuel product innovation and help customers scale reliable intelligent systems.

Illustration of AI at the center of the bullseye

Illustration showing how vector similarity, Cypher templates, and text-to-Cypher meet to create the Aura Agent

GenAI
News

Neo4j Aura Agent: Create Your Own GraphRAG Agent in Minutes

Stranger Graphs illustration

News

“Stranger Things” — The Gate to True Sight With Graph Intelligence

Security

Use Sentiment Analysis to Understand Risk Appetite

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

Adding Retrieval-Augmented Generation (RAG) to Your GraphQL API

GQL is here: Your Cypher queries in a GQL world.

Cypher & GQL

GQL is Here: Your Cypher Queries in a GQL World

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