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

Neo4j joins forces with IBM to bring graph intelligence to enterprise AI customers

5 min read
MIT Technology Review Insights report cover, Connecting AI agents to enterprise knowledge

MIT Technology Review Insights research explains why 13% of companies have a 61% AI success rate

6 min read
Agentic GraphRAG illustration showing an agent reasoning loop connected to a knowledge graph

Agentic GraphRAG: How does an AI agent use a knowledge graph?

9 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

What is agentic AI? The shift toward autonomous, goal-driven AI systems

15 min read

Implementing DRIFT search with Neo4j and LlamaIndex

12 min read

Build a private network path to Aura on AWS, Azure, and Google Cloud using Terraform

7 min read

Reflections on the 2025 Gartner® Cloud DBMS Magic Quadrant™ and the future of AI-ready data

7 min read

Introducing Neo4j’s native vector data type

5 min read
Stranger Graphs illustration

“Stranger Things” — The gate to true sight with graph intelligence

5 min read

Aura activity feed: Enhanced security and compliance for Neo4j Aura

3 min read

Modeling disruptions in the MTA subway

7 min read

Cypher and the cipher manuscript

21 min read

Build better recommendations with Aura graph analytics

10 min read

Conquering Neo4j errors: GQLSTATUS code to the rescue

5 min read

Why startups in the Google ecosystem choose Neo4j

4 min read