CuberPal

TrustMRR

CuberPal is an AI-powered speedcubing coach for iOS that helps Rubik's Cube solvers of all levels improve their times. Users can record or upload their solves and receive instant AI analysis that breaks down every phase of the solve — Cross, F2L, OLL, and PLL — pinpointing exactly where time is being lost. The app also includes structured CFOP learning modules, a built-in cube solver for step-by-step solutions to any scramble, spaced repetition algorithm drills (including ZBLL and COLL sets), an

Visit product View on TrustMRRJan 27, 2026Mobile Apps Mobile App B2C

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Actual performance

29customers

$121MRR/mo

Did not reach leaderboard

Traction signals

MRR growth 30d+39.9%

Launch Intel predictions

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

91%91% 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, users · Missing: mobile apps, personal, entrepreneurs

64%64% 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: user · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

19%19% 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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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.

Incorrect prediction on native model

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