Operationalizing AI-Governed Market Intelligence with Control-M, Snowflake, Amazon Bedrock, AWS DataBrew, Amazon SES, and Amazon QuickSight

This article explains how to transition AI agents from experimental demos to production-grade governance pipelines by using Control-M for complex workflow orchestration. It demonstrates building an end-to-end system that integrates Amazon Bedrock, Snowflake, and various AWS services to automate a strategic portfolio rebalancing process. By managing data validation, dependency synchronization, and downstream automation, the solution ensures that AI-driven insights are reliable, traceable, and operationally actionable.