MagicRail's City Suggest API – Fast Autocomplete for Your App

Hacker News

Hey HN, We’re excited to introduce MagicRail’s City Suggest API, designed to make your location-based apps faster and more intuitive. Whether you’re building travel apps, logistics platforms, or geolocation services, our API helps users find cities instantly with autocomplete functionality. Key features: -Autocomplete city search with minimal latency -Global database with accurate city data -Simple API integration with flexible usage tiers -Powered by high-precision geolocation data for enhanced accuracy Our API delivers results as users type, making it perfect for any use case requiring quick city search functionality. Check out the blog for more details and a demo: https://blog.magicrail.io/supercharge-your-app-with-magicrai... We’d love your feedback and thoughts on how we can improve it further!

Visit product View on Hacker NewsSep 23, 2024

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

77%77% 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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, io · 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.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, intuitive, users · Missing: plus, reviews, host

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · 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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