ToolsSeptember 1, 2026via AWS Machine Learning Blog
How ZS democratized secure ad-hoc analytics with Amazon SageMaker
Why it matters
A practitioner case study showing how to operationalize SageMaker at scale with security and compliance built in — directly actionable for teams deploying ML platforms across regulated industries.
Key signals
- 1,000+ daily active users
- 200+ SageMaker domains
- Healthcare-grade governance implemented
- ZS case study on AWS SageMaker
- Focus on developer agility + security balance
- 1,000+ daily active users across ZS's SageMaker platform
- 200+ SageMaker domains deployed
- Healthcare-grade governance and security requirements met
- Focus on developer agility + compliance balance
- AWS SageMaker as the underlying infrastructure
The hook
1,000+ daily users. ZS scaled secure analytics on SageMaker without sacrificing governance — a blueprint for enterprises scaling AI infrastructure.
Learn how ZS built a security-hardened Amazon SageMaker platform that balances developer agility with healthcare-grade governance, serving 1,000+ daily active users across 200+ SageMaker domains.