Case Study: European Multinational Insurance Company achieves a central ML & AI factory, rapid secure hybrid scaling and faster data scientist onboarding with Cloudera

Central machine learning and AI factory enabled data science teams to share use cases across the cloud

A large multinational European insurer with over 10 million customers and a broad product portfolio faced limits from its traditional data center: no GPUs, constrained resources, slow onboarding of data science teams, and the challenge of managing data across on‑premises and public cloud while maintaining strict security and governance. The company needed a central ML/AI factory and a scalable hybrid-cloud platform to industrialize data science, accelerate use cases, and reduce reliance on IT provisioning.

They implemented Cloudera Data Platform on Microsoft Azure with Cloudera Machine Learning (CML) and Shared Data Experience (SDX), enabling self-service data and compute provisioning, consistent user experience across environments, and MLOps for model deployment, monitoring, and governance. The result: elastic CPU/GPU capacity and autoscaling that cut provisioning from days to minutes, improved cost efficiency, secure hybrid operations, and faster, more efficient onboarding of data science teams—creating a central AI factory for scaled production ML.