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.

Agentic AI

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

Agent Memory

A knowledge layer for your agentic systems on Google Cloud

The data strategy that makes truly personalized customer experiences possible

Featured Voices

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

Developer

“Boost” the power of your AI agents: Integrating Neo4j MCP with Laravel

Developer

Build AI Agents That Make Better Decisions on GCP with Neo4j

Meet Lenny’s Memory: Building Context Graphs for AI Agents

What Is Context Engineering in AI Agents? A Practical Guide

Build AI Agents With Google’s MCP Toolbox and Neo4j Knowledge Graphs

When Your Agents Share a Brain: Building Multi-Agent Memory with Neo4j

When Your Agents Share a Brain: Building Multi-Agent Memory with Neo4j

Using Agents to Secure Satellites’ Supply Chain Systems

Using Agents to Secure Satellites’ Supply Chain Systems

Agentic AI vs. Generative AI: Why Agents Need Memory, Context, and Guardrails

Building Knowledge Graph Agents With LlamaIndex Workflows

Enhancing RAG with Neo4j Cypher and Vector Templates Using LangChain Agents

JSON-based Agents With Ollama & LangChain

Building Stateful AI: Integrating Aura Agent Lifecycle with MCP and Persistent Memory