Test a multi-role approval workflow

Argus QA provides autonomous regression testing for enterprise web applications by leveraging AI computer-use agents to validate complex, multi-step approval processes. Unlike traditional testing tools, it manages intricate workflows where multiple personas—such as creators, approvers, and suppliers—must interact with a system in sequence. By executing these long and frequently changing workflows in independent, authenticated browser sessions, Argus QA ensures that critical business logic remains intact across different user roles without the fragility associated with traditional selector-based testing. As a core engine of the self-hosted Argus platform, the QA module integrates seamlessly with AI and pentest engines, sharing a unified configuration for models, credentials, and cost accounting. The system replaces rigid coordinates and selectors with versioned YAML objectives, allowing agents to observe screenshots, reason through the current state, and execute actions one turn at a time. This approach allows enterprises to maintain high testing velocity and reliability even as the user interface evolves, providing a scalable alternative to manual regression for high-complexity enterprise software.