Scaling agentic workflows with native case management in Amazon Quick Automate
AWS Machine Learning Sumit Wasuja
Amazon Quick Automate adds native case management to help enterprises run AI agents at scale, tracking work items through defined lifecycle stages while handling human oversight and parallel processing. The service enables organizations to process thousands of work items in production by providing visibility into workflow state, exception handling, and human-in-the-loop capabilities with built-in audit logging. Case management allows enterprises to automate complex business processes reliably by separating data ingestion from processing, enabling multiple parallel processors to handle concurrent work items and meet service level agreements.
Why it matters
In this post, we show you how to combine case management with agentic automation capabilities in Quick Automate. We introduce case management and explore the lifecycle of cases in an agentic workflow from case creation through processing to resolution. We cover how to create and manage single or multiple cases, automatically track and update status, handle exceptions, and incorporate Human-in-the-loop (HITL) steps within workflows. We also show the case creator-processor pattern that enables dynamic scaling. Finally, we walk through how to structure case management for enterprise processes, including HITL and case tracking, through a real-life use case.
