Convosphere – Real-life proximity chat

Hacker News

The idea for Convosphere came to me a few years ago, when I was visiting a friend in Sardinia. I had just landed at the airport and needed to get to the train station. I wanted to share a taxi with someone else but didn’t feel like going around asking people one by one. That’s when it struck me: what if there were an app that allowed me to instantly connect with everyone nearby – like a group chat for people in the same location? That became the seed of the project. On the technical side, Convosphere is built with Flutter for cross-platform development, and the backend currently runs on Firebase+Firestore. The app is available as a web app, Android, and iOS, and it supports location-based group and one-to-one chat, events, and a trust score system for safer interactions. You can try Convosphere at the following links: WebSite: https://site.convosphere.app/ WebApp: https://convosphere.app/ Android: https://play.google.com/store/apps/details?id=com.convospher... iOS: https://apps.apple.com/it/app/convosphere/id6737458247 Feedback welcome!

Visit product View on Hacker NewsAug 21, 2025

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3points

4comments

Did not reach leaderboard

Launch Intel predictions

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

87%87% 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: apple, google, apps · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

45%45% predicted probability of success on AppSumo, 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

34%34% 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

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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