Neo4j blog

Agentic AI

The knowledge layer for enterprise AI

A manifesto for context-rich enterprise AI

Chart of the knowledge layer comprising ontologies, data, and memory

Scaling Karpathy’s LLM wiki: Why your knowledge base needs a graph

Independent study: GraphRAG makes AI agents 80% more truthful

Context graph diagram illustrating decision traces for AI agents

Agentic AI

What are decision traces in a context graph? How they reveal agentic reasoning

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

openCypher will pave the road to GQL for Cypher implementations.

Cypher & GQL

openCypher will pave the road to GQL for Cypher implementers

How to configure Neo4j Aura with AWS PrivateLink.

How to configure Neo4j Aura with AWS PrivateLink

Neo4j Joins the Connect with Confluent Partner Program.

AuraDB
News

Neo4j joins the Connect with Confluent partner program

Bringing the Mahabharata epic to life: a Neo4j-powered chatbot with Google Gemini (part 2)

10 Inspiring Projects to Spark Your NODES 2024 Presentation

10 inspiring projects to Spark your NODES 2024 presentation

New Security Feature in Neo4j Aura: Customer Managed Keys

New security feature in Neo4j Aura: Customer Managed Keys

Unveiling the Mahabharata’s web: analyzing epic relationships with Neo4j graph database (part 1)

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

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

Using LlamaParse to create knowledge graphs from documents

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

Creating the GQL Database Language Standard.

Cypher & GQL

Creating the GQL database language standard