Building a Governed AI Model Supply Chain: Integrating AWS SageMaker and the JFrog Platform

Amazon SageMaker streamlines the training and deployment of machine learning models, but as AI adoption grows, organizations need to focus more on governance rather than just speed. Integrating SageMaker with JFrog Artifactory helps create a secure, auditable AI supply chain by addressing challenges such as versioning, access control, and environment promotion. Unlike Amazon S3, which lacks nuanced management features, JFrog Artifactory centralizes model management, allowing for structured environment separation and immutable versioning. This integration supports a unified model orchestration process, secure model lineage, and dynamic runtime model resolution, offering a single source of truth and enhancing security and compliance across diverse environments. By centralizing the management of model artifacts, this approach balances the need for rapid innovation with the comprehensive lifecycle control required for enterprise-grade quality and security, making it particularly beneficial for organizations with multiple AI teams or those operating under stringent compliance requirements.