Break Your Tests. We Dare You.

Pie builds a Contextual Model of your application during Discovery. We don't just memorize coordinates; we memorize the function and relationships of the element. If a "Submit" button becomes a "Go" icon but performs the same action in the same flow, our agent identifies it based on behavior and surrounding context, just like a human user would.

Pie differentiates between UI evolution (adapt) and broken functionality (fail). If a button is present but the click doesn't trigger the expected outcome, the test fails. Self-healing finds elements—it doesn't ignore broken logic.

Yes. Because Pie is vision-native, we don't get blocked by Shadow DOM encapsulation or complex iframe nesting. If the element renders on the screen and is interactive for a user, our agent can see it and test it.

Yes. For pixel-perfect validation, we offer Visual Regression Testing. In this mode, we flag visual deviations (like a button moving 5px) as issues rather than adapting to them. You choose when you want flexibility (functional tests) and when you want strictness (visual tests).

It happens in real-time during execution. There is no "re-training" downtime. As the agent explores the screen, it resolves the element instantly. Your pipeline speed remains unaffected.

Pie excels with messy, legacy UIs—precisely because we don't rely on clean, consistent markup. Your legacy app probably has inconsistent IDs, inline styles, jQuery spaghetti, and tables for layout. None of this matters. If your QA team can manually test it, Pie can autonomously test it. Vision-based self-healing works regardless of DOM quality.

During Discovery, agents test under different user roles: logged out, standard user, admin. For an Admin-only Delete button, Pie expects it as Admin (validates presence) and expects it absent for standard users (flags if present—security issue). For custom scenarios, use Pie Canvas to specify role-based test logic in plain English.

Run them in parallel. Gradually deprecate brittle scripts as confidence grows.

• Week 1-2: Run Pie Discovery, compare coverage to existing suite
• Week 3-4: Add Pie to CI/CD, run alongside Selenium (not replacing yet)
• Month 2: Start deprecating high-maintenance Selenium tests (the ones that break every sprint)
• Month 3+: Full cutover to Pie for regression, keep Selenium for niche edge cases if needed

Most teams deprecate 80% of Selenium scripts within 60 days once they see Pie's maintenance-free coverage.

Yes. Every test execution includes live video recording, step-by-step action logs with reasoning, visual annotations showing element recognition, and decision explanations. If a test passes but you're skeptical about how, watch the replay. See exactly what the agent saw, why it adapted, and how it validated outcomes.

No. Pie scales horizontally using The Pie Farm (massively parallel infrastructure). As your app grows, more agents deploy simultaneously. Your execution time stays constant because we scale infrastructure automatically.

Complexity doesn't create linear slowdown because tests execute in parallel.

Vision-based recognition is language-agnostic. We identify buttons by appearance (size, color, position) and semantic role (primary CTA in form), not by language-specific text. If you change "Submit" to "Senden" (German) or "送信" (Japanese), Pie adapts automatically.

When a feature's core behavior changes (not just UI styling), you update the test intent in plain English.

Pie adapts to the new flow structure automatically. You specify what to test, not how to navigate selectors.

Pie's models are trained on millions of UI interactions across thousands of applications.

Self-healing isn't 100% perfect—but neither are manually maintained selectors that break silently when markup changes. The difference: Pie's errors are caught and corrected systematically, while selector brittleness is an ongoing maintenance tax.