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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

Independent study: GraphRAG makes AI agents 80% more truthful

Illustration representing a context graph for AI agent memory

Agentic AI

What is a context graph?

Welcome, GraphAware

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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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Connected Intelligence: Scaling Graph-Powered Reasoning Across the AI Ecosystem

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

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Neo4j Google Cloud Marketplace listings

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Build AI agents that make better decisions on GCP with Neo4j

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Connected context and persistent memory: Neo4j providers for the Microsoft Agent Framework

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A knowledge layer for your agentic systems on Google Cloud

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Building a Neo4j graph agent for Gemini Enterprise

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How to create and integrate an Okta OIDC service account with Neo4j

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Neo4j GraphML detects network intrusion in Snowflake

Architecting graph-based agentic system: When a regulator asks “Why was this loan approved?”

Architecting graph-based agentic system: When a regulator asks “Why was this loan approved?”