Neo4j blog

Neo4j Context Engine: Rapidly build dependable enterprise agents

Neo4j Context Engine, now in private preview, enables AI agents to accurately answer questions about your business and reliably execute its processes.

5 min read
MIT Technology Review Insights report cover, Connecting AI agents to enterprise knowledge

MIT Technology Review Insights research explains why 13% of companies have a 61% AI success rate

6 min read
Agentic GraphRAG illustration showing an agent reasoning loop connected to a knowledge graph

Agentic GraphRAG: How does an AI agent use a knowledge graph?

9 min read

Introducing Neo4j GraphAware Financial Crime Intelligence

8 min read

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

Implement an automated report-generation agent with crewAI and Neo4j

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Introduction to the Neo4j LLM knowledge graph builder

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Integrate Qdrant and Neo4j to enhance your RAG pipeline

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Eagerness in Neo4j query planning explained with a little fairytale

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Integrate Neo4j with Symfony: Handling multiple connections

7 min read

Neo4j v5 long-term support and the continued evolution

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Building knowledge graph agents with LlamaIndex workflows

18 min read

MicroPython and Neo4j

5 min read

Neo4j joins Linux Foundation for AI and Data

3 min read

Neo4j in 2024: Delivering on our vision of cloud-first graph technology

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Query Neo4j from Tcl

Query Neo4j from Tcl

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Creating beauty with Cypher reduce()

11 min read