Neo4j blog

The knowledge layer for enterprise AI

A manifesto for context-rich enterprise AI

19 min read
Chart of the knowledge layer comprising ontologies, data, and memory

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

19 min read

Independent study: GraphRAG makes AI agents 80% more truthful

4 min read
Context graph diagram illustrating decision traces for AI agents

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

10 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 graph technology? And why it’s the future of enterprise AI

10 min read
Designing agentic AI for pharma & life sciences with graph technology: From complex evidence to explainable insights

Designing agentic AI for pharma & life sciences with graph technology: From complex evidence to explainable insights

5 min read

Improve GenAI challenges on AWS with graph technology

3 min read

Neo4j and Google Distributed Cloud: Bringing graph technology to air-gapped environments

6 min read

AI & graph technology: AI explainability

3 min read
Connections Improve Accuracy

AI & graph technology: Connections improve accuracy

2 min read

AI & graph technology: How graphs accelerate machine learning

2 min read

AI & graph technology: What are knowledge graphs?

6 min read

AI and graph technology: 4 ways graphs add context

6 min read
Learn more about moving towards AI standards with graph technology.

Toward AI standards: Graph technology as a fabric for context

4 min read
Learn more about how graphs provide context for responsible AI.

Toward AI standards: Graph technology for responsible AI

4 min read
Learn how to improve supply chain transparency.

Where graph technology & supply chain transparency meet corporate social responsibility

3 min read