Neo4j blog

Introducing Neo4j GraphAware Financial Crime Intelligence

Move from fragmented data to connected intelligence, for better detection, deeper investigations, and defensible decisions.

Vector RAG vs. GraphRAG: Which retrieval do you need?

Scaling Karpathy’s LLM wiki: Why your knowledge base needs a graph

Independent study: GraphRAG makes AI agents 80% more truthful

Featured voices

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

Check out this week's #GraphCast on the FinCEN Files

GraphCast: Follow the money, untangling complex fraud networks with Emil Eifrem

Observable graphs

Developer

Language Buffet: Using Neo4j with GraalVM

Developer

Making sense of news, the Knowledge Graph way

Top 10 use cases: Knowledge Graphs

Knowledge graph

Exploring graphs with BearingPoint: The 5-minute interview

Learn about Neo4j Aura Enterprise

Introducing Neo4j AuraDB Enterprise [GA release]

NeoDash: Build Neo4j dashboards without writing any front-end code

Gram: A data graph format

Real-time recommendations

Top 10 use cases: Real-time recommendations

Discover how to use graph theory to determine the possible number of orders in which you can watch all the Marvel movies.

Graph Data Science

GraphCast: Using graph theory to find the number of Marvel watch orders

Neerav Vyas, Realogy, discusses the value of integrating graph databases into their lead conversion process.

Machine learning

Driving innovation and powering advanced analytics with Neo4j