Flight search that shows aircraft and airline safety records

Hacker News

I built this flight safety search tool because I've always been nervous about flying. Like actually very nervous every time I fly even if its unwarranted. I've always been told the chances of any incidents on planes are extremely unlikely but after looking into this further it seems like airlines and models play the most important factor. Some airlines and plane models have had a lot more problems than others... Recent aviation incidents and quality concerns only heightened those feelings. The app lets you check detailed safety records for specific aircraft and airlines before booking, helping make informed decisions about your flights. Looking ahead, I'm working on adding verified pilot profiles - imagine being able to see your pilots' experience and safety records before takeoff. It's something that doesn't exist today but could really change how we think about flight safety.

Visit product View on Hacker NewsApr 19, 2025

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

81%81% 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

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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.

Incorrect prediction on native model

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