Case Study: Milliman MedInsight achieves faster healthcare insights and AI-ready data scalability with Databricks

Protecting people’s health and well-being with AI

Milliman MedInsight, the healthcare analytics group within Milliman, faced growing data volume and complexity that made its legacy on-premises database systems too rigid and difficult to scale. To better support actuarial insights and consulting for more than 300 healthcare companies, the team turned to Databricks Data Intelligence Platform to modernize its data foundation and prepare for future AI-driven use cases.

Using Databricks, Milliman MedInsight adopted a lakehouse approach with Delta Lake, Auto Loader, and MLflow to streamline storage, incremental data processing, and machine learning workflows. The result was faster processing at large scale, stronger collaboration across data teams, and the creation of a Data Science Portal that gives customers self-service access to data and models, helping Milliman deliver better insights in less time while improving efficiency and productivity.

Milliman MedInsight

Iyibo Jack

Principal, Senior VP of Product Development