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
Allmaz provides a self-hosted AI testing platform specifically engineered for public bodies and government agencies that demand absolute data sovereignty. By deploying the system on-premise via a containerized architecture, agencies ensure that sensitive citizen data and critical infrastructure details never leave their controlled environment, eliminating the risks associated with external SaaS dependencies while automating the regression testing of complex enterprise web applications. Unlike traditional automation, the platform utilizes AI computer-use agents that interact with applications through visual observation and reasoning. This approach allows for the automation of long, multi-role workflows that are typically too volatile for standard scripts. By combining deterministic login processes with autonomous agent execution, government entities can maintain a rigorous quality assurance standard that adapts to frequently changing application interfaces without sacrificing security or auditability.
Addressing Public Sector Challenges
Guarantees total data sovereignty through a fully self-hosted, on-premise deployment of ten containers.
Eliminates external SaaS dependencies to protect sensitive citizen data and maintain strict regulatory compliance.
Accelerates regression cycles for complex public-service applications using autonomous AI agents.
Provides comprehensive audit transparency with persisted, step-by-step execution logs for every action taken.
Enables collision-free parallel testing in shared environments through run-scoped test data naming.
Reduces operational overhead by complementing existing Playwright scripts with AI for high-volatility scenarios.
Enterprise-Grade Testing Capabilities
Secure Credential Management
Logins are performed deterministically by script rather than the agent, with credentials resolving through an encrypted secret store to ensure security.
Multi-Role Workflow Validation
Simulate complex government processes where creators, approvers, and suppliers each run in fresh, independently authenticated browser sessions.
Independent Verification
To ensure accuracy and auditability, assertions are checked by an independent verifier rather than the agent that performed the action.
Model-Agnostic Architecture
Model selection is managed via database configuration, allowing agencies to switch providers or models without redeploying code.
Collision-Free Parallel Testing
Run-scoped test data naming allows multiple parallel agents to operate within a shared environment without colliding.
The Autonomous Testing Process
Frequently Asked Questions
How is citizen data protected during testing?
The platform is entirely self-hosted using ten containers and a shared artifact volume, ensuring no external SaaS dependency and keeping all data within your own secure infrastructure.
Does this replace existing automation tools like Playwright?
No, it is designed to complement them. Use deterministic scripts for stable, repetitive flows and AI agents for long, multi-role, or frequently changing scenarios.
How are the costs of AI model usage managed and tracked?
Every model call is metered, and costs are aggregated hierarchically from the individual call level up to the step, scenario, suite, and release level.
How does the system handle complex multi-user approvals?
It supports multi-role workflows where different roles, such as a creator and an approver, operate in separate, independently authenticated browser sessions.
How does the AI identify product bugs without making false claims?
The AI flags suspected bugs with a ready-to-file report, but a human must review and file it; the AI never asserts a defect on its own authority.
Secure Your Public Infrastructure
Deploy our self-hosted AI testing platform to maintain data sovereignty and accelerate your regression testing.
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