Launch Intel
StudyClock

StudyClock

TrustMRR

StudyClock is an AI-powered study and productivity platform for deep focus and smarter learning. It combines Pomodoro timers, countdowns, and presets with real time study rooms, notes, tasks, analytic

StudyClock is an AI-powered study and productivity platform for deep focus and smarter learning. It combines Pomodoro timers, countdowns, and presets with real time study rooms, notes, tasks, analytics, and gamification. Its AI suite includes flashcards, summarizer, study planner, mind maps, OCR, TTS, and practice exams delivering a complete, distraction free learning experience.

Visit productView on TrustMRRJan 1, 2026EducationOtherB2C
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Actual performance

2customers
$9MRR/mo
Did not reach leaderboard

Traction signals

Domain Rating9
MRR growth 30d+88.5%

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
65%65% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: tasks, notes · Missing: mac, agents, macos
48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
37%37% 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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: real time, smart · 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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