Test an application without writing scripts
Test an application without writing scripts with Argus QA: a practical, on-prem approach built for Azerbaijani teams.
Autonomous Regression Testing for Enterprise Web Apps
Argus QA delivers autonomous regression testing for enterprise web applications by leveraging AI computer-use agents. Unlike traditional automation that relies on fragile selectors or coordinates, Argus utilizes versioned YAML objectives that define roles, assertions, and step/time budgets. This shift allows teams to execute complex, multi-role workflows—such as those involving creators, approvers, and suppliers—without the constant overhead of manual script maintenance, as the agents observe screenshots and reason through actions in real-time. As one of the three core engines of the Argus self-hosted platform, the QA engine integrates seamlessly with AI and pentest capabilities. It is designed to complement existing tools like Playwright, using deterministic scripts for stable flows while deploying AI agents for long, frequently changing, or multi-role scenarios. By providing a model-agnostic architecture and a self-hosted containerized deployment, Argus QA ensures that enterprise teams maintain full data sovereignty and operational flexibility while scaling their testing coverage.
Enterprise-Grade QA Efficiency
Eliminate selector fragility by using objective-based YAML scenarios instead of hardcoded coordinates
Orchestrate complex multi-role workflows using independent, authenticated browser sessions for each role
Optimize operational spend via a two-tier model execution strategy that escalates to stronger models only on failure
Ensure total data sovereignty and security through a self-hosted deployment of ten containers with no external SaaS dependency
Streamline the defect lifecycle with ready-to-file reports that allow humans to review and file bugs without AI overreach
Maintain a single source of truth by synchronizing test cases and results bidirectionally with management tools like Qase.io
Core Technical Capabilities
Autonomous AI Agents
Agents observe screenshots and state their reasoning to take actions. Route memory distills successful paths into step intents to guide future runs.
Multi-Role Orchestration
Support for creator, approver, and supplier roles, each running in a fresh session with credentials managed via an encrypted secret store.
Model-Agnostic Architecture
Configure providers and reasoning effort via database settings. Change models instantly without redeploying code.
Independent Verification
To ensure accuracy, assertions are checked by an independent verifier rather than the agent performing the task.
Detailed Failure Classification
Failures are categorized as product defects, agent failures, environment issues, assertion failures, loops, step limits, or timeouts.
Cost Accounting
Every model call is metered, with costs aggregated from the individual call up to the full release suite.
The Autonomous Testing Workflow
Frequently Asked Questions
Does Argus QA replace traditional scripting tools?
No, it complements them. Use deterministic scripts for stable flows and AI agents for long, multi-role, or frequently changing scenarios.
How is security handled for logins?
Login is performed deterministically by script, not the agent, and credentials are resolved through an encrypted secret store.
Does the AI automatically file bugs in Jira?
No. The AI flags suspected bugs with a report, but a human must review and file the defect to ensure accuracy.
Is the platform a SaaS product?
No, it is self-hosted using ten containers and a shared artifact volume, removing external SaaS dependencies.
How does the system handle model costs and selection?
Model selection is managed in the database and updated per run without redeployment. Every call is metered, and costs are aggregated from the call level up to the full release suite.
Ready to automate your regression testing?
Deploy Argus QA to your infrastructure and start testing without the script burden.
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