Neo4j blog

Neo4j Context Engine: Rapidly build dependable enterprise agents

Neo4j Context Engine, now in private preview, enables AI agents to accurately answer questions about your business and reliably execute its processes.

5 min read

Vector RAG vs. GraphRAG: Which retrieval do you need?

10 min read

Introducing Neo4j GraphAware Financial Crime Intelligence

8 min read

Independent study: GraphRAG makes AI agents 80% more truthful

4 min read

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

Going meta: Wrapping up GraphRAG, vectors, and knowledge graphs

4 min read

Safeguarding elections: How graph technology powers groundbreaking research on political ads

6 min read

Using LlamaParse to create knowledge graphs from documents

5 min read

Topic extraction with Neo4j GDS for better semantic search in RAG applications

22 min read
Creating the GQL Database Language Standard.

Creating the GQL database language standard

8 min read

Graph-based metadata filtering to improve vector search in RAG applications

15 min read

Adding RAG to your GraphQL API

10 min read
GQL is here: Your Cypher queries in a GQL world.

GQL is here: Your Cypher queries in a GQL world

7 min read
GQL: The ISO Standard for Graphs Has Arrived!

GQL: The ISO standard for graphs has arrived

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

Building RAG applications with the Neo4j GenAI stack: a comprehensive guide

12 min read
Node embeddings in a knowledge graph.

The future of knowledge graph: Will structured and semantic search become one?

16 min read
What is retrieval-augmented generation RAG)?

What is retrieval-augmented generation (RAG)?

5 min read