HNTD

HNTD

TrustMRR

AI-powered talent pipeline: search GitHub, score repositories with Claude, fill tech roles in days instead of months. HNTD is a SaaS platform that automates technical recruiting. Recruiters input crit

AI-powered talent pipeline: search GitHub, score repositories with Claude, fill tech roles in days instead of months. HNTD is a SaaS platform that automates technical recruiting. Recruiters input criteria (language, location, activity), the system scans GitHub and scores repositories, delivering candidates in a real-time dashboard. No LinkedIn, no cold pitching: results verified directly from actual code. Linkedin ->> www.linkedin.com/in/vladvrinceanu/ PS. the stripe key it's just a mockup

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Actual performance

Did not reach leaderboard

Traction signals

Domain Rating4

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: claude, stripe, activity · Missing: mac, agents, macos
76%76% 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
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: pipe, io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
23%23% 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
13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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