Pie

Pie learns your product by using it. It maps the flows customers actually take instead of following a script someone wrote once. You point it at your app and it figures out the paths worth testing, so there's no test authoring on your side. The upside is coverage that tracks your real product, not a stale set of assertions.

Every pull request gets exercised the way your users would experience it in a live environment. Pie reads the diff, walks the affected flow, and checks whether the change holds up. This is the part that catches regressions before a customer does, so you're not the one explaining a broken checkout in the exec channel while the rest of the team is already shipping the next thing.

The agent looks past simple pass or fail. It reports things like a button that won't click because its loading state never resets, which is the kind of bug a scripted assertion often misses. That wider net means fewer issues reach production through a gap your tests didn't cover.

When Pie finds a break, it doesn't just file a ticket and leave the diagnosis to someone who's already busy with the next release. It drafts a fix and opens a pull request for your team to review, sometimes showing the root cause and the exact line that caused it. Reviewing a proposed change is faster than diagnosing a report from scratch, and your engineers stay in control of what merges.

There's nothing to maintain. Pie runs quietly in the background and re-tests as your codebase moves, so you're not rewriting selectors every time the UI changes. The result is a test layer that keeps working on its own, rather than one that rots until someone abandons it.

Pie tests across web and mobile, and it handles apps that ship in multiple markets and builds. For teams with the same product on several platforms, that means one agent watching all of them instead of a different testing tool per surface.