Autonomous regression testing for Oil, Gas & Energy
Autonomous regression testing for oil, gas & energy. Energy operators manage safety-critical procedures and vast equipment and materials catalogues across field sites.
Autonomous Regression Testing for Energy Infrastructure
Energy operators manage safety-critical procedures and vast equipment and materials catalogues across diverse field sites. Allmaz provides an autonomous testing solution designed to validate complex enterprise web applications, ensuring that safety SOPs and massive master data records remain consistent across software updates. By utilizing AI computer-use agents, the platform moves beyond fragile, selector-based scripts to a reasoning-based approach that observes the UI and executes actions based on high-level objectives. As part of the Argus self-hosted platform, this engine integrates seamlessly with QA and pentest workflows, sharing a unified configuration for models, credentials, and cost accounting. It is specifically engineered for the rigors of enterprise environments, supporting multi-role workflows and strict security protocols. This ensures that the software powering critical energy infrastructure is resilient, verified, and capable of handling the complex interactions between creators, approvers, and suppliers without compromising data integrity.
Solving Energy Sector Software Challenges
Automate validation of complex safety SOPs and runbooks without the need for constant manual script updates
Ensure data consistency across massive equipment and materials master data sets through autonomous verification
Verify multi-vendor supplier records using multi-role workflow testing in independent browser sessions
Eliminate fragile selector-based tests that typically break during UI updates by using AI reasoning and screenshots
Maintain strict security and data sovereignty via a self-hosted deployment with encrypted secret stores
Reduce testing overhead for shift-based field operations software by automating long, frequently changing scenarios
Enterprise-Grade Testing Capabilities
AI Computer-Use Agents
Agents observe screenshots and reason through actions to perform regression testing, moving away from rigid coordinates or selectors.
Multi-Role Workflow Validation
Simulate real-world energy operations where creators, approvers, and suppliers each operate in fresh, independently authenticated browser sessions.
Self-Hosted Infrastructure
Deployed as ten containers with a shared artifact volume, removing external SaaS dependencies for sensitive energy infrastructure data.
Deterministic Security
Logins are performed by scripts using an encrypted secret store, ensuring AI agents never handle raw credentials.
Independent Verification
Assertions are checked by a separate verifier rather than the agent performing the work, ensuring objective validation of safety-critical flows.
The Autonomous Testing Process
Frequently Asked Questions
Does the AI automatically file bug reports in our system?
No. The AI flags suspected product bugs with a ready-to-file report; a human must review and file it, as the AI never asserts a defect on its own authority.
How does this integrate with existing testing tools like Playwright?
It complements Playwright. Use deterministic scripts for stable, simple flows and AI agents for long, multi-role, or frequently changing scenarios.
Is the system locked into a specific AI model provider?
No, the platform is model-agnostic. Model selection is managed in the database and can be changed per run without redeploying code.
How is the cost of AI model usage tracked?
Every model call is metered, with costs aggregated from the individual call level up to the step, scenario, suite, and release.
How does the system handle authentication for different user roles?
Login is performed deterministically by script—never by the agent—with credentials resolved through an encrypted secret store to ensure security.
Secure Your Critical Energy Workflows
Implement autonomous regression testing to ensure your safety-critical procedures and material catalogues are always production-ready.
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