I

I built Skyhunt – A VPN-powered tool to find cheap flights globally

Hacker News

I built Skyhunt – A VPN-powered tool to find cheap flights globally

Hi, I’m Alonso. After 6 months of coding during late nights and weekends, I’m excited to share Skyhunt, an app that compares flight prices across 30+ countries by automatically using VPNs. The idea came from my frustration with manually switching VPNs and searching for the same flights on platforms like Skyscanner to find the lowest prices. Skyhunt automates this process, saving time and money by showing the best global deals in one place. Key features: * Automated VPN searches: Compare prices in multiple countries effortlessly. * Save time: No more repetitive manual searches. * Optimize costs: Take advantage of regional price differences to find the lowest fares. Skyhunt is perfect for frequent travelers like me or anyone looking to explore the world while spending less. It’s currently in a functional beta stage, and I’d love to get feedback from the community to make it even better. You can try Skyhunt here: https://skyhunt.app/ If you have any questions or suggestions, I’d be happy to answer them in the comments. Thanks for taking the time to check it out!

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Actual performance

4points
7comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: vpn · Missing: supports, reddit linkedin, podcasting
95%95% 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 · Strong signals: using, coding · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews
52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, scanner · Missing: mobile apps, ios, personal
41%41% 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
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
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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