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
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

Introducing Neo4j GraphAware Financial Crime Intelligence

8 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

Demystifying graph neural networks

1 min read

From nodes to rows: A guide to querying Neo4j graph database in Pandas/SQL style using Cypher

12 min read

SustainGraph – a knowledge graph for the UN sustainability goals

4 min read

How to explore SAP sample data in Neo4j – Graph for ERP part 2

7 min read

Graphs for ease and scalability in the auto industry: The 5-minute interview with Michal Stefanak

3 min read
Knowledge graph-based chatbot with GPT-3 and Neo4j

Knowledge graph-based chatbot with GPT-3 and Neo4j

13 min read

The power of knowledge graphs and conversational AI

2 min read

An introduction to Needle – Neo4j’s design system

5 min read

GraphSummit 2023: 3 things to expect this year

3 min read

A new steer for the (Neo4j) drivers?

7 min read

Announcing the newest Neo4j and AWS partner solution

4 min read

Breaking out of data jail: How Arcurve better serves its clients with Neo4j Graph Data Science

4 min read