Forvibe for macOS

Product Hunt

Everything between your build and the App Store

Focus on building your mobile app, not the operational busywork. Forvibe streamlines the entire launch process for App Store and Google Play. We automate localization, store listings, and screenshot generation while handling AI landing pages, legal docs, and global subscription pricing. Don’t let launch friction slow you down. We handle the heavy lifting so you can ship faster, scale globally, and keep your focus on what truly matters: creating a great product.

Visit product View on Product HuntMar 18, 2026Mac Productivity Developer Tools

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Actual performance

105upvotes

15comments

Made the leaderboard

Traction signals

Makers1

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, google · Missing: agents, agent, cursor

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

33%33% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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