Ververica Case Study: Humn.ai

Humn.ai uses Ververica Platform and Apache Flink to build a Machine Learning-based platform producing dynamic risk assessment models and real-time pricing for tomorrow’s insurance industry.

Humn.ai deployed Ververica Platform with Apache Flink to harden production Flink jobs seamlessly and quickly.

They developed a Machine Learning-based platform that is Kubernetes-native and implements ML-based algorithms for calculating the risk of vehicles in real-time. The risk scores for each insured asset is calculated dynamically and then updates a premium variable part of the insurance policy in real-time.

This case study includes:

• The challenges Humn.ai faced with their previous technology stack and how Apache Flink helped in resolving them
• The results  achieved by deploying Ververica Platform and Apache Flink to production
• A detailed overview of Humn.ai's experience using Ververica Platform