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Mobile app that helps consumers find class action settlements they qualify for and claim their money

Acquire.com

An iOS and Android app that helps US consumers find class-action settlements they qualify for and claim the money they're owed. Launched August 2025, it reached ~$905K TTM proceeds and ~$1.22M ARR (peak $1.83M in June 2026), with 500K+ downloads, ~19,500 active paying subscribers, and a 111,500-person email list.

An iOS and Android app that helps US consumers find class-action settlements they qualify for and claim the money they're owed. Launched August 2025, it reached ~$905K TTM proceeds and ~$1.22M ARR (peak $1.83M in June 2026), with 500K+ downloads, ~19,500 active paying subscribers, and a 111,500-person email list. Revenue runs on two streams: weekly and annual subscriptions (via RevenueCat), plus law-firm affiliate partnerships that monetize claimant leads ($141K in May 2026 alone). It runs ...

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Actual performance

$101,666/yr
Made the leaderboard

Traction signals

Asking price$2,800,000
Annual revenue$1,220,000
Revenue multiple2.3x

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
88%88% 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.
Acquire.comFits revenue-generating acquisition profile · Strong signals: arr, revenue, ttm · Missing: mrr, profit, saas
83%83% 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 · Missing: mobile apps, personal, entrepreneurs
59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: email · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews
37%37% predicted probability of success on AppSumo, 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
23%23% 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
10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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