Rejourney - Open-source revenue leak prediction for web and mobile apps
Show HN: Rejourney – Open-source revenue leak prediction for web and mobile apps
Rejourney is a lightweight, open-source observability tool designed to detect revenue leaks in web and mobile applications. By monitoring critical business transitions like checkout, activation, and subscription renewals, it compares current cohorts against healthy baselines to identify potential failures before they impact the bottom line. Supporting platforms like Next.js, React Native, and Swift, Rejourney combines session replay with journey maps, heatmaps, and API performance data to provide a complete investigative surface. This self-hostable solution helps teams pinpoint the exact user experience or technical error causing lost revenue, enabling faster fixes and improved product stability.
Revenue is an outcome, not a useful unit of diagnosis. Rejourney protects explicit business states such as signup, checkout, and renewal by using leading signals to rank risk before a lagging aggregate makes it obvious.
- Doches
> Endpoint views break down request volume, errors, latency, and status codes. Crash and ANR detail adds the app version, device, and thread context around a failure. This is where a problematic UI transition can be connected to a backend or runtime condition.
The project README reads like a first draft straight out of Claude, and it's incredibly off-putting. The 'Show HN' post here is so much better; clearly you're capable of writing a decent explanation of what this project is, its history, and for whom you've built it. Take the time and write the damn README yourself.
If you expect human attention, put in human effort.
You're a sophomore at UT, so as a UTCS alum (:wave: from a fellow Turing Scholar) I'm not letting you off the hook. Unless things have majorly changed, I know you're taking 6 hours of writing-heavy coursework.
- jcjmcclean
This looks really interesting. I've used LogRocket a lot across a number of businesses with varying volume, mainly to try to uncover these kinds of issues. I know they have an AI layer now but I'd love to try this as an AI native alternative which gets straight to the problem solving. It could save hours of manually watching playback and a lot of effort coming up with potential problems/solutions etc.