Codera

TrustMRR

Codera is an iOS app that lets you build fully functional React Native apps using nothing but natural language. Describe your app idea, and Codera generates the code, previews it live, and gets you fr

Visit product View on TrustMRRJan 27, 2026Artificial Intelligence Mobile App B2C

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Actual performance

6customers

$72MRR/mo

Did not reach leaderboard

Traction signals

MRR growth 30d+630.5%

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: apps, using, coding · Missing: mac, agents, macos

86%86% 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.

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

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

29%29% 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

26%26% 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

11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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