qtrl.ai
qtrl scales your QA from test management to autonomous AI agents without losing control.

About qtrl.ai
qtrl.ai is the modern QA platform that shatters the old trade-off between control and speed. It’s built for engineering and QA teams who are tired of choosing between slow, manual processes and brittle, expensive automation. qtrl brings enterprise-grade test management, intelligent automation, and autonomous AI agents into a single, cohesive platform. Its core value proposition is a progressive automation model: you can start with simple, structured test management on day one and gradually introduce AI-assisted and fully autonomous testing as your team is ready. This makes it perfect for product-led engineering teams, scaling QA departments, and enterprises that need robust governance without sacrificing velocity. qtrl provides clear visibility into quality through real-time dashboards, traces requirements to coverage, and turns every test run into structured data for smarter decision-making. It’s not just another tool; it’s a strategic upgrade designed to scale quality intelligently and sustainably.
Features of qtrl.ai
Autonomous QA Agents
This is where qtrl's AI layer truly shines. Built-in autonomous agents can generate robust UI tests directly from natural language descriptions, maintain them as your application evolves, and execute them at scale across multiple browsers and environments. They operate on-demand or continuously, following your defined rules and executing in real browsers—not simulations—for authentic results. This feature transforms test creation from a coding task into a strategic conversation.
Enterprise-Grade Test Management
qtrl provides a centralized command center for all your QA activities. Organize test cases, plan and execute test runs, and maintain full traceability from requirements to coverage. The platform supports both manual and automated workflows and is built with compliance and auditability in mind, creating complete audit trails for every action. It’s the solid foundation of structure and oversight that makes advanced automation safe.
Progressive Automation Model
This isn't an all-or-nothing AI gamble. qtrl's progressive model lets you start with human-written test instructions. As confidence grows, you can move to AI-generated tests, with full review and approval at every step. The platform even analyzes coverage gaps and suggests new tests to fill them. You control the pace, increasing autonomy only when it proves its value, ensuring trust is earned, not assumed.
Governance by Design & Adaptive Memory
qtrl is built for enterprise trust. It offers permissioned autonomy levels, full visibility into agent actions, and enterprise-ready security, ensuring no black-box decisions. Coupled with its Adaptive Memory, which builds a living knowledge base of your application from every interaction, qtrl gets smarter and more context-aware over time while always operating within your governance framework.
Use Cases of qtrl.ai
Scaling Beyond Manual Testing
For QA teams overwhelmed by repetitive manual checks, qtrl provides a clear path forward. Start by structuring manual test cases in the platform, then gradually introduce AI agents to automate the most tedious flows. This allows teams to scale test coverage and frequency without linearly increasing headcount, freeing human testers for more complex, exploratory work.
Modernizing Legacy QA Workflows
Companies stuck with outdated, script-heavy automation suites can use qtrl to break free from maintenance hell. The AI agents can generate new, maintainable tests from natural language, and the adaptive memory helps understand the application context. This enables a gradual migration to a more intelligent and resilient automation strategy without a risky, full-scale rewrite.
Ensuring Governance in Autonomous QA
Enterprises that require strict compliance, traceability, and audit trails can safely explore AI-powered testing with qtrl. The platform's governance-by-design approach provides permission controls, full audit logs, and the ability to review and approve every AI-generated test before it runs. This makes autonomous QA viable for regulated industries.
Accelerating Product-Led Engineering Teams
Fast-moving product teams need quality to keep pace with development. qtrl integrates with CI/CD pipelines and requirements management tools, creating continuous quality feedback loops. AI agents can execute tests across multiple environments per commit, giving developers immediate confidence and reducing the bottleneck on dedicated QA resources.
Frequently Asked Questions
How does qtrl's AI handle changes in my application's UI?
qtrl's autonomous agents are coupled with an Adaptive Memory system that learns from your application. When the UI evolves, the AI uses this context to understand the changes and can automatically update the affected test steps, significantly reducing maintenance overhead compared to traditional coded scripts. All changes are suggested for review before being applied.
Is my test data and application access secure with an AI agent?
Absolutely. Security is foundational. qtrl operates with enterprise-ready security protocols. For executions, you can use per-environment variables and encrypted secrets, which are never exposed to the AI agent. The system is designed to execute tests without retaining sensitive data, and all access is governed by strict permission controls.
Do I need to be an automation expert to use qtrl?
Not at all! qtrl is designed for progression. You can start by using it as a powerful test management tool with no automation. When you're ready, you can begin by writing simple, natural language instructions for the AI to execute. The platform guides you toward more advanced automation as your team's comfort and needs grow.
Can I integrate qtrl with my existing tools and pipelines?
Yes, qtrl is built for real workflows. It offers integrations for requirements management and full support for CI/CD pipelines. This allows you to trigger test runs automatically from your build processes and feed quality metrics back into your development lifecycle, creating seamless feedback loops without disrupting your current toolkit.



