I made a running app that turns your runs to a virtual garden

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I started running 5 years ago and it completely changed me. Recently, I decided to train for my first marathon and needed something more than just tracking my runs to motivate me. I noticed all the apps currently available are just trackers and route finders, but nothing has solved the problem of consistency. So I thought of combining the basic idea of the Forest app with running and created a small app for myself which would reward me with plants and trees for my runs. I am not a mobile developer but then i came across Capacitor. Since I knew Next.js and have been working with it for the past 2 years, I built the app with it. I started using it and showed it to some of my friends and they really liked it. The gamification gave me a mental boost of planting more trees and plants in my virtual garden and just seeing it flourish made me happy. Then I decided to publish it on Play Store and also built it for iOS devices as many of my friends had iPhones. It took weeks to build and release them after brutal and lengthy reviews from both the stores. Running has taught me to keep moving further, one step at a time and the journey of building the app was just like that. I wanted to share the app with all the people who are just starting out running and with the experienced folks who want to make their runs mean something. The app is Run&Grow: https://runandgrow.com

Visit product View on Hacker NewsMay 27, 2025

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

93%93% 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: apps, new, using · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps · Missing: mobile apps, personal, entrepreneurs

52%52% predicted probability of success on TrustMRR, 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

50%50% 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: reviews · Missing: plus, platform, intuitive

40%40% 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

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

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