FlyOnTime, a Chrome Extension that helps you book better flights

Hacker News

If you're anything like me you've realized that US air travel has become quite a raw deal recently. Macroeconomic forces aside, the customer experience sucks. Flights are delayed all the time, connections are missed, and the prices are still sky-high (no pun intended). Digging into the data I found that not all flights are created equal. You've probably heard the phrase "I flew X, they are way better than Y" where X could be Delta and Y could be Spirit. So I made a Chrome Extension that shows you on hover the predicted probability of delay and cancellation for every single US domestic flight. Check it out here: flyontime.app

Visit product View on Hacker NewsJun 15, 2024

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

70%70% 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: mac, single · Missing: agents, macos, agent

66%66% 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: ide, io · Missing: https docs, excited, just released

48%48% 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: way · Missing: mobile apps, ios, personal

45%45% 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

43%43% 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

16%16% 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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