Launch Intel
Readbrew

Readbrew

TrustMRR

Readbrew is a beautifully crafted book tracking app that helps you build a consistent reading habit. Track your books, log reading sessions, set goals, and watch your progress come to life with streak

Readbrew is a beautifully crafted book tracking app that helps you build a consistent reading habit. Track your books, log reading sessions, set goals, and watch your progress come to life with streaks, heatmaps, and reading stats — all in a calm, distraction-free experience.

Visit productView on TrustMRRFeb 25, 2026Mobile AppsMobile AppB2C
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Actual performance

4customers
$8MRR/mo
Did not reach leaderboard

Traction signals

Domain Rating1
MRR growth 30d-77.0%

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
22%22% 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
22%22% 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
17%17% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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