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Storage Cleaner app (iOS) – 15K+ Paid Subscribers

Acquire.com

A profitable iOS utility that keeps phones running fast for a fast‑growing audience of older users. With a clean, no‑frills interface, it clears storage, removes large files, and optimizes performance—no tech skills required.

A profitable iOS utility that keeps phones running fast for a fast‑growing audience of older users. With a clean, no‑frills interface, it clears storage, removes large files, and optimizes performance—no tech skills required. Recurring subscriptions and a loyal base drive steady, predictable cash flow. Launched in July 2023, the business has 15K+ paid subscribers, $4.77M TTM revenue, $1.77M TTM profit, 84% year‑over‑year growth, and ~$4.77M ARR. Built lean and bootstrapped, it’s low‑maintena...

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Actual performance

$397,500/yr
Made the leaderboard

Traction signals

Asking price$12,000,000
Annual revenue$4,770,000
Revenue multiple2.5x

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comFits revenue-generating acquisition profile · Strong signals: arr, revenue, profit · Missing: mrr, saas, margin
81%81% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: ios, users, profitable · Missing: mobile apps, personal, entrepreneurs
67%67% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface, users · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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