ApplyCandid

Indie Hackers

AI that scores, tailors, and applies to jobs for you

Job hunting eats hours on repetitive tailoring and manual applications. ApplyCandid scores your fit against a listing, tailors your resume, and applies for you on LinkedIn, Indeed, and Naukri — so you spend that time on

Visit product View on Indie HackersAug 1, 2026commitment-side-project employees-0 founders-code-yes

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Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on Product Hunt, 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

28%28% 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

12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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