qtrl is an AI-powered QA platform that combines enterprise-grade test management with autonomous browser-testing agents, letting teams manage manual and automated tests in one place and progress to AI-assisted execution at their own pace.
What is qtrl?
qtrl is a QA platform that takes test cases, requirements, and natural-language instructions as input and produces structured test runs, coverage reports, and real-time quality dashboards. It runs as a SaaS web application and is built by the qtrl team (qtrl.ai). The platform supports both manual test management and AI-generated browser tests executed in real browser environments, not simulations.
Key Features
- Autonomous QA Agents — Execute instructions on demand or on a schedule across multiple environments (dev, staging, production) in real browsers; agents follow user-defined rules and never expose secrets to the AI.
- Enterprise-Grade Test Management — Centralized test cases, plans, and runs with full traceability and audit trails, supporting manual and automated workflows for compliance.
- Progressive Automation — Start with human-written manual tests, then move to AI-generated tests when ready; qtrl suggests new tests based on coverage gaps and lets teams review, approve, and refine each step.
- Adaptive Memory — Builds a living knowledge base of your application by learning from exploration, test execution, and issues, making context-aware test generation smarter over time.
- Multi-Environment Executions — Run tests across development, testing, staging, and production with per-environment variables and encrypted secrets; secrets are never exposed to the AI agent.
- CI/CD Integration — Supports pipeline feedback loops and continuous quality checks, working with existing tools.
Who is it for?
- Product-led engineering teams — Use qtrl to automate regression testing without dedicated QA engineers, starting from manual test cases and gradually introducing AI agents.
- QA teams scaling beyond manual — Organize test cases, plan runs, and track coverage in a centralized system while letting AI agents cover repetitive browser checks.
- Enterprises needing governance — Use audit trails, permissioned autonomy levels, and requirements traceability to maintain compliance while adopting AI-assisted testing.
What can you do with qtrl?
- Manual test management — Write and organize test cases (e.g., "Authentication Suite" with 3 tests), execute runs, and track pass/fail status per environment.
- AI-generated UI tests — Describe a test in natural language (e.g., "Login Flow Test" with steps like navigate to /login, enter credentials, verify dashboard) and have qtrl’s agent generate and execute it in a real browser.
- Progressive automation — Start with 0% automated coverage (as shown in the "Authentication Suite" example: 0 automated, 12% coverage) and increase automation as trusted AI suggestions appear.
- Multi-environment validation — Run the same test across dev, staging, and production with environment-specific variables and secrets, without exposing credentials to the AI.
How does qtrl work?
Teams start by creating manual test cases in the central test management system. When ready, they describe a test in plain English and qtrl’s autonomous agent generates and executes it in a real browser. The platform learns from every interaction—test execution, coverage gaps, issue reports—and suggests new tests or improvements. A four-step progression (Start simple → Increase automation → Unlock intelligence → Stay in control) guides teams from manual to fully autonomous QA while keeping permissioned oversight at each stage.
FAQ
Does qtrl run tests in real browsers or simulations?
qtrl runs tests in real browser environments, not headless simulations. This ensures that test results accurately reflect actual user experiences across different environments.
