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

Using GraphQL middleware with Neo4j GraphQL

Query, chomp, repeat

News

Sudhir Hasbe named president, technology at Neo4j

Exploring the Neo4j Spatial plugin: Custom procedures for spatial analysis

Neo4j MCP Server: Your ADHD-friendly house-moving assistant

Why I’m replacing my RAG-based chatbot with agents

How graph-powered supply chain improves sustainability

Exploring Neo4j Spatial: Path intersections using AIS data

Unleashing the power of schema: What’s new in the Neo4j GraphRAG package for Python

How to convert unstructured text to knowledge graphs using LLMs

GenAI

How to build a GenAI chatbot from technical documents using Neo4j and Unstructured.io

Exploring Neo4j Spatial: Layer management, spatial filtering, and intersection