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I

I build an algorithm to prevent jet lag when you fly overseas

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I build an algorithm to prevent jet lag when you fly overseas

Hi, I'm Andrew, the founder of inShift. I've been researching jet lag, night work, and circadian biology for 4+ years. I started building it to help my nurse girlfriend shift her body clock for night work. But we got a bunch of requests from business travelers. So we helped C-level folks fly to Silicon Valley and be 100% ready for crucial business meetings. We also helped a team of sales guys who fly frequently between Europe and Asia. It is a mobile calendar app supported with hardware and a personal advisor. How big of a problem is jetlag for you? Have you tried to solve it? P.S. I'm curious to hear from founders flying overseas for YC batches or investor meetings.

Visit productView on Hacker NewsMay 13, 2024
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
92%92% 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.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
53%53% 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
32%32% 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
29%29% 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.

Incorrect prediction on native model

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