AI Art & Video Gen App (iOS/Android/Web)

Acquire.com

A leading AI art and video creation app across iOS, Android, and web. Users turn text into stunning images and clips using best-in-class models.

A leading AI art and video creation app across iOS, Android, and web. Users turn text into stunning images and clips using best-in-class models. Awarded Google Play App of the Year and reached #1 in 100+ countries. Profitable since 2022. Traction at scale: 50M+ downloads, 14.8M registered users, 900K+ ratings, and 2B+ creations. Subscription-driven with 12,191 active subscribers and $77K MRR. 100% organic acquisition with ~3,000 daily downloads. Key Highlights ✅ $942K TTM revenue, $806K TTM...

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Actual performance

$77,000/yr

Made the leaderboard

Traction signals

Asking price$1,950,000

Annual revenue$924,000

Revenue multiple2.1x

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: ios, video, google · Missing: mobile apps, personal, entrepreneurs

83%83% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comFits revenue-generating acquisition profile · Strong signals: mrr, revenue, profit · Missing: arr, 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: model, google, user · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released

47%47% 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

8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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