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
Learn what agentic RAG is, how it works, which design patterns to use, and when it beats traditional RAG.

Agentic RAG: What it is, how it works, and when to use it

17 min read
Agent Memory

A knowledge layer for your agentic systems on Google Cloud

4 min read

The data strategy that makes truly personalized customer experiences possible

9 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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Aura Graph Analytics: A Technical Deep Dive

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Introducing Neo4j Aura Graph Analytics: Scalable, Easy-to-Deploy Graph Analytics for Any Data Source

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Agentic GraphRAG for Commercial Contracts

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Simplify Modern Application Development With GraphQL on Neo4j AuraDB

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Text2Cypher: The Impact of Difficult Example Selection

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Is a Knowledge Graph a Graph Database?

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Transform Static Risk Assessment Into a Dynamic Data-Driven Strategy

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LLM Knowledge Graph Builder Back-End Architecture and API Overview

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Build an Intelligent Movie Search With Neo4j and Vertex AI

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Neo4j and Google Distributed Cloud: Bringing Graph Technology to Air-Gapped Environments

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Google Cloud & Neo4j: Teaming Up at the Intersection of Knowledge Graphs, Agents, MCP, and Natural Language Interfaces

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Neo4j + Google Cloud: Powering the Next  Generation of AI and Cloud Innovation

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