We used investor tools to find the best startups to work at

Hacker News

hey y'all -- can you please tell us if our job search tool sucks? :D we built it using an investor platform called Harmonic.ai to gather startup data, then contextualize it so that job seekers could find out about the most exciting startups hiring first (like if they just raised, growing headcount fast, have an ex-unicorn founder, etc). pretty sure we're the first platform doing anything like this. anyway, let me know what you think. really excited to launch this thing soon! getting feedback from the hn community first is really fun :)

Visit product View on Hacker NewsJun 28, 2022

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

81%81% 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.

Hacker NewsStrong engagement from HN community · Strong signals: excited · Missing: https docs, just released, exist

68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

19%19% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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