Our client, a prominent US Health Insurer, aimed to enhance their Data Science team’s efficiency by transitioning statistical models from legacy tools to advanced MLOps practices. This migration aimed at supporting underwriting, care management, and other functions while paving the way for scalable, enterprise-wide applications.
We empowered our client with an MLOps assessment playbook, offering a phased execution roadmap for model migration. Our solution included a PoC, MLOps Assessment Framework, and a Technology Architecture Blueprint, delivering a clear path with resourcing, cost estimates, and functional capabilities for each phase. The client gained a comprehensive guide to enhance their Data Science team’s efficiency.