Neo4j Blog

From data to intelligence: Why every enterprise needs an AI knowledge layer

The knowledge layer maps and resolves data so AI can accurately answer questions, make better decisions, and be explainable.

4 min read
Illustration of how a supplier graph connectes materials, routes, and contracts

What’s invisible in your supply chain could cost you

7 min read

Agent tools: What they are, how they work, and how AI agents use them

13 min read
Agent Memory

A knowledge layer for your agentic systems on Google Cloud

4 min read

Emil Eifrem

CEO & Co-Founder, Neo4j, Inc.

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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

Neo4j GraphML Detects Network Intrusion in Snowflake

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Evaluating Graph Retrieval in MCP Agentic Systems

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Neo4j Named a 2025 Gartner® Peer Insights™ Customers’ Choice for Cloud Database Management Systems

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Agentic GraphRAG for Commercial Contracts

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Building Knowledge Graph Agents With LlamaIndex Workflows

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GraphRAG Field Guide: Navigating the World of Advanced RAG Patterns

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The GraphRAG Manifesto.

The GraphRAG Manifesto: Adding Knowledge to GenAI

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Knowledge Graph vs. Vector RAG: Benchmarking, Optimization Levers, and a Financial Analysis Example

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RDF vs. Knowledge Graph: Choosing the Right Approach for Implementing Knowledge Graphs.

RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph

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Going Meta: Wrapping Up GraphRAG, Vectors, and Knowledge Graphs

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Generative Transformation from ER Diagram to Graph Model Using Google’s Gemini Pro

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Try Neo4j’s Next-Gen Graph-Native Store Format

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