Applya

TrustMRR

Applya is an AI-powered career tool that helps job seekers tailor resumes and cover letters for each role in 60 seconds. Users upload one master resume, paste any job description, and instantly generate ATS-optimized application assets with skill-gap analysis, impact phrasing, and PDF/Word downloads.

Visit product View on TrustMRRFeb 8, 2026Productivity Software B2C

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Actual performance

3customers

$68MRR/mo

Did not reach leaderboard

Traction signals

Domain Rating13

Launch Intel predictions

Analyze your own launch →

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

79%79% 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.

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

47%47% 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

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

27%27% 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

13%13% 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

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

Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos

7%7% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Correct prediction on native model

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