PeptideTrack

PeptideTrack

TrustMRR

iOS subscription app for people on peptides, GLP-1s and TRT protocols. Users log doses on a reminder calendar, upload bloodwork with automatic out-of-range flagging, track body metrics and progress ph

iOS subscription app for people on peptides, GLP-1s and TRT protocols. Users log doses on a reminder calendar, upload bloodwork with automatic out-of-range flagging, track body metrics and progress photos, and size reconstitution doses on a visual syringe. Apple Health sync, 70+ peptide library, clinician-ready PDF/CSV export, moderated 18+ community. Capacitor + Supabase + RevenueCat. Localized in 12 languages. Pro at $39.99/yr or $9.99/mo.

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Actual performance

144customers
$616MRR/mo
Did not reach leaderboard

Traction signals

MRR growth 30d+126.1%

Launch Intel predictions

Analyze your own launch →
TrustMRRFits verified-revenue profile · Strong signals: ios, users · Missing: mobile apps, personal, entrepreneurs
70%70% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, user, visual · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, subscription · Missing: arr, mrr, profit
27%27% predicted probability of success on Acquire.com, 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
21%21% 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
12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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