Question 1

What is qtrl?

Accepted Answer

qtrl is an AI-powered QA platform that combines structured test management with autonomous browser testing. You write high-level instructions describing what to test, and qtrl's AI agents execute those tests in real browsers. It handles test case organization, execution, reporting, and traceability in one place.

Question 2

Who is qtrl for?

Accepted Answer

qtrl is built for QA teams, product-led engineering teams, and organizations that need to scale testing without losing control. It works well for teams outgrowing manual testing, teams replacing legacy tools like TestRail, and enterprises that need audit trails and governance for AI-powered testing.

Question 3

How is qtrl different from TestRail or Qase?

Accepted Answer

TestRail and Qase are test management tools. qtrl is test management plus AI-powered execution. You get organized test cases and runs like you would in TestRail, but qtrl also executes tests autonomously in real browsers, self-heals when the UI changes, and builds knowledge about your application over time. No separate automation framework needed.

Question 4

Can I use qtrl with Playwright or Cypress?

Accepted Answer

Yes. qtrl sits above your test execution framework. You can use it alongside Playwright, Cypress, or any other framework. qtrl handles the test management, orchestration, and AI-powered execution layer, while your existing framework handles the tests you've already built.

Question 5

Does qtrl support CI/CD integration?

Accepted Answer

Yes. qtrl integrates with your CI/CD pipeline so you can trigger test runs on every deployment. Results feed back into your release process with clear pass/fail signals and traceability.

Question 6

What browsers does qtrl support?

Accepted Answer

qtrl's AI agents execute tests in real Chromium-based browsers. Tests run in isolated browser sessions with full support for authentication, cookies, and session management.

Question 7

Is there a free tier?

Accepted Answer

Yes. The Free Trial lasts one month and includes 5,000 credits and 1 user. It gives you full access to core features so you can evaluate qtrl before committing to a paid plan. No credit card required.

Question 8

How do credits work?

Accepted Answer

Credits are consumed each time a task runs. The number of credits used depends on the complexity of the task. Simple tasks use fewer credits, while longer or more involved tasks use more. Credits reset monthly at the start of your billing cycle.

Question 9

What happens if I run out of credits?

Accepted Answer

Any task already in progress will complete, but you won't be able to start new tasks until your credits reset next month. You can upgrade to a higher plan for more credits.

Question 10

Do you offer annual billing?

Accepted Answer

Yes. Contact our sales team for annual billing options. Annual plans typically include a discount compared to monthly billing.

Question 11

How does Enterprise pricing work?

Accepted Answer

Enterprise plans are customized to your needs. We can adjust credit limits, provide unlimited users, SSO/SAML, and custom SLAs. Contact our sales team to discuss your requirements.

Question 12

What is agentic testing?

Accepted Answer

Agentic testing is the shift from scripted test automation to autonomous AI agents that navigate real browsers, self-heal when the UI changes, and build knowledge about your application over time. Instead of following a fixed sequence of steps, an agentic test pursues an objective (like "verify checkout with a discount code") and figures out how to get there at runtime.

Question 13

Can AI replace my QA team?

Accepted Answer

No. AI can handle certain types of execution (running predefined tests, exploring known flows), but it can't replace the judgment a good QA engineer brings. Deciding what to test, understanding which user flows carry the most business risk, and catching subtle UX regressions require domain knowledge and product intuition that AI doesn't have. The teams that succeed treat AI as a multiplier for their QA team, not a replacement.

Question 14

Do AI-generated tests need maintenance?

Accepted Answer

Self-healing handles selector-level changes well: a button that moved, a class name that changed, a form field that got restructured. Where it breaks down is at the intent level. When your checkout flow changes from three steps to two, the AI can still find buttons, but it doesn't know the flow itself changed. Selector maintenance drops significantly, but you still need humans reviewing whether tests match current product behavior.

Question 15

What are the risks of AI testing?

Accepted Answer

The biggest risks are false confidence (AI produces thorough-looking results but tests the same flows repeatedly), hallucinated assertions (checks that sound reasonable but don't match expected behavior), and lack of audit trails. The practical pattern that avoids these: AI generates tests, a human reviews and approves them, then approved tests run automatically.

Question 16

Should I use Playwright or Cypress in 2026?

Accepted Answer

Playwright has become the default for new projects, with 33 million weekly npm downloads vs Cypress's 7 million. It offers cross-browser support (Chromium, Firefox, WebKit), free built-in parallelization, and multi-language support. Cypress still has an excellent developer experience for frontend-focused JS teams. If you're already productive with Cypress and not hitting its architectural limits, switching for the sake of it doesn't make sense.

Question 17

What is MCP (Model Context Protocol)?

Accepted Answer

MCP stands for Model Context Protocol. Anthropic open-sourced it in late 2024 as a standard way for AI models to interact with external tools and services. For browser automation, an MCP server wraps a browser engine and exposes actions (click, type, navigate, screenshot) as structured tools that an LLM can call.

Question 18

What is Playwright MCP?

Accepted Answer

Playwright MCP is Microsoft's official MCP server that lets AI agents control browsers through Playwright. It uses accessibility tree snapshots instead of screenshots, so you don't need a vision model. It supports cross-browser testing and can output TypeScript Playwright test scripts as it goes. The newer CLI mode reduces token consumption by roughly 4x.

Question 19

How does Stagehand compare to Playwright MCP?

Accepted Answer

They solve different problems. Playwright MCP gives AI agents raw browser access via the MCP protocol. Stagehand is a full automation framework that blends deterministic code with AI-powered actions through three primitives: act, extract, and observe. Stagehand has built-in self-healing and element caching; Playwright MCP has broader browser support and IDE integration. You can use them together.

Question 20

Is test management still necessary with AI testing?

Accepted Answer

More than ever. AI agents need structured inputs: what to test, expected behavior, which environments to target. Without test management, AI testing is just expensive random clicking. The teams getting the most from AI invested in structure first, then layered AI on top.

Question 21

When does manual testing break down?

Accepted Answer

Manual testing scales linearly with effort, but product complexity grows exponentially. At ten features, one QA engineer can verify the critical paths. At a hundred features, the combinatorial surface is too large for any human team to cover by hand. The symptoms: release cadence slows, regression bugs appear in working features, developers start routing around QA entirely.

Question 22

What does in-house test automation really cost?

Accepted Answer

More than most teams expect. The initial framework build takes months, not weeks. Then there's ongoing maintenance (every UI change breaks tests), the flakiness tax (debugging intermittent failures, re-running pipelines), infrastructure costs (CI runners, browser services, parallel execution), and the opportunity cost of engineers maintaining tests instead of building product.

Question 23

Why are teams leaving TestRail?

Accepted Answer

After Idera's acquisition, TestRail saw slower development, buggier releases, and longer support response times. The Jira integration requires a TestRail license for anyone to see linked test cases. Over 38 outages have been logged in the past four years. And there are no native AI capabilities for test generation or execution, which competing tools have been shipping since 2023.

Question 24

Do AI coding tools introduce more bugs?

Accepted Answer

The data suggests yes. While PRs per author increased 20% year-over-year, incidents per pull request climbed 23.5% and change failure rates rose roughly 30% (Cortex 2026 benchmark). CodeRabbit's analysis found AI-generated PRs contain 1.7x more issues than human-written ones, with a 75% increase in logic and correctness errors.

Question 25

Is AI-generated code secure?

Accepted Answer

Often not. Veracode's 2025 report found 45% of AI-generated code samples failed basic security tests. AI-generated code is 2.74x more likely to contain XSS vulnerabilities and 1.88x more likely to introduce improper password handling. Stanford researchers found developers using AI assistants were more likely to introduce security bugs and, worryingly, more likely to rate their insecure code as secure.

Question 26

Should AI test its own code?

Accepted Answer

No. When the same model produces both the code and the validation, assumptions get confirmed instead of tested. The result: a test suite with high coverage but a low mutation score that catches almost nothing. Use AI to generate test scenarios in plain language, then have a human or separate system review and approve them.

Question 27

When does the EU AI Act take effect?

Accepted Answer

The EU AI Act hits full enforcement on August 2, 2026. If your team builds, deploys, or tests software that uses AI in any meaningful way and you're selling into Europe, this regulation applies regardless of where your company is based. Fines for non-compliance reach up to 35 million euros or 7% of global annual turnover.

Question 28

What does the EU AI Act require from QA teams?

Accepted Answer

Five things: (1) traceability from requirements to test results, (2) bias and accuracy validation across protected characteristics, (3) data quality assurance for training and test datasets, (4) documentation that human oversight mechanisms work, and (5) post-deployment monitoring that continues after release. Your QA process is now auditable by regulators.

Question 29

How do you test non-deterministic AI systems?

Accepted Answer

With different techniques: metamorphic testing (checking relationships between inputs and outputs instead of exact values), statistical acceptance bands (defining performance ranges and testing over many runs), adversarial robustness testing (deliberately trying to break the system with bad inputs), and drift monitoring (continuously checking that production performance stays within declared thresholds).

Question 30

What is metamorphic testing?

Accepted Answer

Metamorphic testing checks relationships between inputs and outputs rather than asserting exact values. Example: if your sentiment classifier labels "This product is great" as positive, then "This product is absolutely great" should also be positive. For bias detection, swap a candidate's name or gender on an identical resume; if the ranking changes, you've found discriminatory behavior.

Frequently Asked Questions

About qtrl

Pricing & Plans

AI-Powered Testing

Test Frameworks & Tools

Test Management & Scaling QA

AI Code Quality & Security

EU AI Act & Compliance