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

Developer

Describing a property graph data model

Enhancing word embedding with Graph Neural Networks

Graph Data Science

Unlock the power of graph data science with AuraDS Enterprise on AWS

Slice and dice your graph data with Neo4j Bloom

Angular with @Neo4j/GraphQL and the Nest.js backend

Demystifying graph neural networks

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

SustainGraph – a knowledge graph for the UN sustainability goals

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

Knowledge graph

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

Knowledge graph-based chatbot with GPT-3 and Neo4j

Knowledge graph-based chatbot with GPT-3 and Neo4j

The power of knowledge graphs and conversational AI