AI

AI-powered body fat estimates and progress tracking from photos, without expensive equipment

Acquire.com

A mobile fitness app that uses AI-powered photo analysis to estimate body fat percentage and help users monitor changes in body composition over time. Available on iOS and Android, the app allows users to scan their physique and track visual progress as part of their fitness journey without requiring specialized body composition equipment.

A mobile fitness app that uses AI-powered photo analysis to estimate body fat percentage and help users monitor changes in body composition over time. Available on iOS and Android, the app allows users to scan their physique and track visual progress as part of their fitness journey without requiring specialized body composition equipment. The business monetizes through recurring monthly and annual subscriptions and is designed to require minimal ongoing maintenance. Key Highlights ✅ Approxi...

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Actual performance

Did not reach leaderboard

Traction signals

Asking price$25,000

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: ios, month, monthly · Missing: mobile apps, personal, entrepreneurs
82%82% 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 · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, visual · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: recurring, subscription · Missing: arr, mrr, revenue
25%25% predicted probability of success on Acquire.com, 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: io · Missing: https docs, excited, just released
24%24% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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