Graph Data Science
by Neo4j · Data and analytics · San Mateo, United States
Graph algorithms and machine learning on connected data
What Graph Data Science does
- Anomaly and fraud detection
- Recommendation engines
- Route optimization
What Graph Data Science is used for
- Detect fraud and anomalies across industries
- Build recommendation engines from user behaviour
- Manage supply chain inefficiencies with what-if scenarios
Who Graph Data Science is for
- Insurers
About Neo4j
Graph database and AI knowledge layer platform for connected data storage, querying, and analytics.
Neo4j in the vendor registry: its products, features and similar vendors.
Also by Neo4j
- Neo4j Graph Database: Native graph database queried with Cypher
- AuraDB: Fully managed cloud graph database
- Neo4j Bloom: Visual graph exploration tool
- GraphRAG: Graph-based retrieval for generative AI applications
- Virtual Graph: Create and query a knowledge graph on existing data.
- Aura Graph Analytics: Run graph algorithms on any data across any cloud.
More in this category: Data and analytics platforms for financial services.
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