I was tearing apart competitor APKs by hand every release. So I automated it.

I ship a small Android app and kept doing the same manual job: download a competitor's new APK, unpack it, and work out what actually changed — features, onboarding, paywall structure, which growth SDKs they picked up. It ate a weekend each time and I still missed things.

So I built the thing that does it. It reads each shipped release and diffs it against the previous one.

Five teardowns are published, free, no signup:

• Turbo AI deleted their session-replay vendor entirely. OpenReplay went from ~400 dex references to zero.
• Bible Chat shipped new premium copy to only half their locales. Arabic, Japanese, Korean and Chinese fall back to English.
• RIZZ moved to server-configurable paywalls and left the free tier exactly where it was.
• Cal AI kept all eight SKUs and quietly opened a Stripe web checkout next to store billing.
• Glam AI's entire release was campaign creative. Barely any code changed.

It's static analysis: I read the binary Play serves and never run the app. So I can't see server-side experiments, remote paywall layouts, or the final localized price — and the reports say that outright instead of guessing.

Every finding is labelled observed or inferred. No estimated downloads, no estimated revenue, nothing modelled.