AI-powered calorie tracker with photo analysis, ready-to-scale, live on App Store with 3700 users

Acquire.com

An IOS App, A personalized nutrition tracking tool designed to help users build better habits, monitor meals, and achieve lasting health and wellness goals through the power of AI. ✅ Track your meal and the calories inside with a picture of your food. ✅ AI-Driven Personalized Insights – Tailors nutrition recommendations based on individual habits and goals ✅ Habit-Building Features – Encourages sustainable routines for long-term health improvements ✅ Data-Driven Meal Monitoring – Tracks an...

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Actual performance

Did not reach leaderboard

Traction signals

Asking price$9,900

Launch Intel predictions

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

87%87% 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.

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

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

39%39% 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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

28%28% 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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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