How ZS democratized secure ad-hoc analytics with Amazon SageMaker
1,000+ daily users. ZS scaled secure analytics on SageMaker without sacrificing governance — a blueprint for enterprises scaling AI infrastructure.
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.
The key facts
10 to know1,000+ 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
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: 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.