Autonomous regression testing for Government
Autonomous regression testing for government. Public bodies require on-premise systems so citizen data never leaves the country.
Autonomous Regression Testing for Government
Ensure the stability of critical public services with a self-hosted AI testing platform designed for strict data sovereignty. Our solution provides autonomous regression testing for enterprise web applications using AI computer-use agents. By operating entirely on-premise via a containerized deployment, the platform ensures that sensitive citizen data never leaves the country, meeting the most rigorous regulatory requirements for data residency and security. Unlike traditional testing tools, the system utilizes a model-agnostic architecture that separates reasoning from execution. It complements existing deterministic scripts by deploying AI agents to handle long, multi-role, and frequently changing scenarios. This hybrid approach allows government agencies to maintain stable core flows while autonomously validating complex business logic across multiple user roles, all while maintaining a full audit trail of every action, build stamp, and model expenditure.
Addressing Public Sector Challenges
Guaranteed data sovereignty via a self-hosted, ten-container deployment with no external SaaS dependency.
Enhanced audit transparency with detailed records of every step, build stamps, and identity-linked run logs.
Reduced manual overhead for complex workflows through AI agents that reason through screenshots and objectives.
Accelerated defect detection by identifying product bugs independently before they impact citizen-facing services.
Secure credential management using an encrypted secret store for deterministic, script-based logins.
Optimized operational costs through a two-tier model execution strategy and granular call-level metering.
Enterprise-Grade Testing Capabilities
Multi-Role Workflow Validation
Simulate complex government processes where creators, approvers, and suppliers each operate in fresh, independently authenticated browser sessions.
Model-Agnostic Architecture
Switch AI models via database configuration without redeploying code, utilizing a two-tier execution system to optimize costs.
Independent Verification
Assertions are checked by an independent verifier rather than the agent performing the work, ensuring objective results.
Deterministic Integration
Complements existing tools like Playwright by using scripts for stable flows and AI agents for long, frequently changing scenarios.
Comprehensive Cost Accounting
Every model call is metered and aggregated from the call level up to the release, providing full visibility into testing spend.
The Autonomous Testing Process
Frequently Asked Questions
How is citizen data protected during testing?
The platform is self-hosted using ten containers and a shared artifact volume, ensuring no external SaaS dependency and that data remains within your own infrastructure.
Does the AI automatically file bugs in our tracking system?
No. To maintain human authority, the AI identifies suspected defects and generates a report, but a human must review and manually file it to Jira or Qase.
How does the system handle complex, multi-step government workflows?
It uses multi-role workflows with separate authenticated sessions and 'route memory,' which distills successful paths into step intents to guide future runs.
Can we integrate this with our existing test management tools?
Yes, it integrates with Qase.io, importing test cases verbatim and posting results back to the run with links to evidence, while skipping API-tagged tests.
How are AI model costs managed and optimized?
The system uses a two-tier execution model where a cost-effective model runs first, escalating to a stronger model only upon agent-side failure, with all costs metered per call.
Secure Your Public Infrastructure
Deploy our self-hosted AI testing engine to ensure your government applications remain stable and compliant.
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