Case Study: a global healthcare leader accelerates AI/ML adoption with Provectus MLOps on AWS

Accelerating AI/ML Adoption with MLOps on AWS

Provectus worked with a large global company, a U.S.-based healthcare leader operating across consumer health, medical devices, and pharmaceuticals, to accelerate its adoption of AI/ML. The company needed a modern MLOps platform on AWS and Amazon SageMaker to standardize machine learning workflows, simplify onboarding, and reduce reliance on DevOps support as it transitioned away from legacy infrastructure.

Provectus implemented a cloud-native MLOps platform on AWS using Amazon SageMaker Projects, along with reusable infrastructure and AI/ML project templates, seed code, and documentation. The solution enabled faster, more reliable deployment of AI/ML applications, reduced manual infrastructure setup, lowered proof-of-concept costs, and sped up the approval process for new projects. As a result, the company could onboard data scientists and ML engineers more easily and scale AI/ML delivery across the organization.