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

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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

Check out the 7 best Neo4j blog from 2018.

News

7 seriously awesome Neo4j blogs from 2018

Catch this week's GraphCast on Euler's formula and graph duality – an interesting graph theory proof

Graph visualization

GraphCast: Euler’s formula (a graph theory proof)

Learn about KeneteK and LARUS announcement with a new graph partnership.

KeneteK & LARUS announce a new graph partnership

Free Download O'Reilly Graph Algorithms book

Graph algorithms in Neo4j: Single source shortest path

Learn about the evolution of graph database technology towards intelligent systems.

The evolution and future of graph technology: Intelligent systems

Learn more about Neo4j's inaugural CFO, Mike Asher, in this interview with CEO Emil Eifrem

News

It’s high time Neo4j had a CFO – here’s who we chose [Interview]

Read this interview with Denise Persson, CMO of Snowflake and Neo4j's newest board member.

News

Please welcome Denise Persson – CMO at Snowflake – to the Neo4j board [Interview]

Learn the trade-offs of each type of graph database technology, including property graphs and RDF

Graph databases for beginners: Other graph technologies

Free Download O'Reilly Graph Algorithms book

Graph algorithms in Neo4j: Shortest path

Watch this GraphCast video on graph algorithms and Game of Thrones

GraphCast: Graph algorithms & Game of Thrones

Watch Geoffrey Horrell's presentation on intelligent recommendation engines for financial analysts

Intelligent recommendation engine for financial analysts

Data visualization for machine learning (ML)

Evaluating investor performance using Neo4j, GraphXR and ML