With Neo4j Bloom, you can more easily investigate your graphs, quickly prototype solutions and better
collaborate across different teams.
Bloom is already being used across a number of industries and uses, from accelerating the work of
researchers scrutinizing connections between disease pathways and developers creating graph applications
to data scientists and investigators working together on predictive fraud models.
Visualization is a critical tool for getting the most out of graph data science. Bloom enables data
scientists to follow their intuition in exploring interesting patterns, visualize algorithm results and
streamline conversations with subject matter experts.
Explore using the Graph Data Science Library and Neo4j Bloom with the white paper, Financial Fraud Detection with Graph Data Science: How Graph Algorithms &
Visualization Better Predict Emerging Fraud Patterns, and learn how to tap into the power of
graph technology for higher quality predictions.
Read about one example using the Graph Data Science Library and Neo4j Bloom for financial fraud