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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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Most recent

Graph database

Capgemini turns data and AI into connected intelligence with Neo4j and Databricks

iscover the best tool for context engineering and build agentic AI with MCP, knowledge graphs, GraphRAG, and practical evaluation and tracing.

Agentic AI

Best tools for context engineering in agentic AI systems

Why healthcare CIOs can’t afford to scale AI without a knowledge graph foundation

Neo4j Community Edition advances for graph-powered AI and intelligent applications

Graph database

Neo4j Community Edition advances for graph-powered AI and intelligent applications

Neo4j and Databricks - Data to Knowledge

Graph database

Power connected intelligence for AI and analytics with Neo4j and Databricks

Neo4j brings high speed identity resolution to the Snowflake AI Data Cloud

Hey LLM, you’re using OPTIONAL MATCH wrong. Here’s the Cypher that actually works.

Agentic architecture is the system design that enables agentic systems to work efficiently towards the goal.

Agentic AI

What is agentic AI architecture? Common patterns and when to use them

What is GraphRAG?

The data strategy that makes truly personalized customer experiences possible

Visualization of how Neo4j Graph Intelligence reveals hidden patterns in massive datasets

How graph intelligence drives breakthroughs in science and society

Finding the fastest way out: How Dijkstra’s algorithm finds shortest paths