Product Spotlight: TigerGraph

Big Data Trailblazer by Dr. Yu Xu, CEO

Who is TigerGraph?

TigerGraph is a platform for advanced analytics and machine learning on connected data. Based on the industry’s first and only distributed native graph database, TigerGraph’s proven technology supports advanced analytics and machine learning applications such as fraud detection, anti-money laundering (AML), entity resolution, customer 360, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis.

How does TigerGraph help organizations of all sizes?

Organizations of all sizes Connect, Analyze, and Learn from Data with TigerGraph:

  • Connect internal and external datasets and pipelines with a distributed Graph Database
  • UnitedHealth Group is connecting 200+ datasets and Kafka-based streaming data pipelines to deliver a real-time customer 360 to improve quality of care for 50 million members;
  • Xandr (part of AT&T) is connecting multiple data pipelines to build an identity graph for entity resolution to power the next-generation AdTech platform.
  • Analyze connected data for never-before insights with Advanced Analytics
  • Jaguar Land Rover has accelerated supply chain planning from three weeks to 45 minutes, reduced supplier risk by 35%, and has added 100 million pounds annually in profits.
  • NewDay, a leading specialist financial services provider and one of the largest issuers of credit cards in the UK, uses advanced graph analytics to prevent and preempt financial fraud.
  • Learn from the connected data with In-Database Machine Learning
  • Intuit has built an AI-based customer 360 with in-database machine learning for entity resolution, personalized recommendations, and fraud detection. Graph-based machine learning at Intuit has reduced at-risk (fraud) events by 50% while improving accuracy by 50%. reducing false positives.
  • 7 out of the top 10 banks are driving real-time fraud detection and credit risk assessment with in-database machine learning.

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