CityVois – AI travel guide that tells stories and spots landmarks

Hacker News

Hi HN, I created [CityVois]( https://www.cityvois.com ) as an AI-powered travel assistant for solo travelers and cultural explorers. It detects your current location and nearby landmarks, and shares cultural and historical stories in both voice and text. It also allows users to recognize landmarks via photos – we currently support over 18,000 globally. For now, we've curated citywalk routes in cities across China and Japan, designed to help users explore hidden stories around them without relying on traditional guidebooks. Technically, the app is built with Flutter, uses Firebase for backend services, and combines GPS with image recognition for real-time landmark detection. Would love any feedback, thoughts, or suggestions – especially around UX for solo travelers and improving performance. Thanks!

Visit product View on Hacker NewsJul 29, 2025

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

88%88% 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.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos

28%28% 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, 000, io · Missing: https docs, excited, just released

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

11%11% 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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