An app to learn about the world

Hacker News

Hi everyone, I made an app to learn about countries of the world, including landmarks, culture, history, flags, and much more! The idea is to make learning fun and engaging, but at the same time provide a clear, structured path, that makes learning effective and meaningful. It has multiple game modes, where you can learn, play, compete and socialize with peers. Check it out and let me know what you think! The app is free to download: iOS: https://apps.apple.com/us/app/globo-learn-world-geography/id... Google Play: https://play.google.com/store/apps/details?id=app.getglobo.a...

Visit product View on Hacker NewsDec 26, 2025

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Actual performance

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Did not reach leaderboard

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TrustMRRFits verified-revenue profile · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

72%72% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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