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I Made a Platform for React Native Cloud Components
Hacker NewsI Made a Platform for React Native Cloud Components
Hey HN, I'm a web/mobile developer and I decided to create a platform for storing React components and translations for React Native. This platform allows you to upload your JS/TS components directly to the cloud through CLI and then change UI without full mobile update. It's also fully open-sourced. I hope that this tool will be helpful and allow you to save time and create mobile apps faster. Would love your feedback pls Igor
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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, open · Missing: mac, agents, macos81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: mobile apps, apps · Missing: ios, personal, entrepreneurs45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue15%15% 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, crypto8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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