RogStudios

TrustMRR

DRAPED est une application mobile d'assistant IA pour la mode qui révolutionne la gestion de garde-robe. L'app utilise l'IA pour scanner et cataloguer automatiquement les vêtements via la caméra du téléphone, puis suggère 3 tenues personnalisées chaque matin en tenant compte de la météo et du planning. Pour Stripe, vous vendez un abonnement premium avec : Essai gratuit de 7 jours pour découvrir toutes les fonctionnalités Plans mensuels et annuels pour accéder aux suggestions IA illimitées, au sc

Visit product View on TrustMRRJan 5, 2026Social Media Apps B2C

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Actual performance

1customers

$32MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating3

MRR growth 30d-3.2%

Launch Intel predictions

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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRLess likely to generate early MRR · Strong signals: ai · Missing: api, 000, profitable

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: reviews, intuitive, videos

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, just released, open source

20%20% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: stripe · Missing: mac, agents, macos

13%13% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, just like, small businesses

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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