Applauncher

TrustMRR

Applauncher is a community-powered launchpad for indie apps. Creators submit their apps and get discovered by early adopters who earn credits for engaging — leaving reviews, trying apps, and sharing feedback. With a built-in credit economy, gamified engagement (daily spins, referral bonuses), and tiered plans for serious creators, Applauncher bridges the gap between indie makers and their first users. Free to start, with Pro and Launch Boost tiers for creators who want more visibility.

Visit product View on TrustMRRMar 19, 2026Marketing Apps stripe

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating7

Launch Intel predictions

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

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps, users · Missing: mobile apps, ios, personal

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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