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In The Office Tracker – Track your RTO requirements automatically

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In The Office Tracker – Track your RTO requirements automatically

Hello HN! I wanted to share my free, native , MacOS app that uses Wifi scanning to automatically keep track if you're in the office or not! It let's you keep track of your RTO requirements to make sure you don't get in trouble :) If people really like it I can make an iOS version and an Android version and a Windows version and a Linux version. After RTO, we all started using spreadsheets to track our time, but I hated having to remember to go into that spreadsheet every day and mark when I was in or not. So, I decided to waste months learning Swift UI to make this app instead! Please share your RTO stories below if you need some catharsis :) It's my first time making a "real" app. I'm by day a Java backend engineer. https://intheofficetracker.com

Visit productView on Hacker NewsNov 27, 2025
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3points
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Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios · Missing: supports, reddit linkedin, podcasting
81%81% 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: mac, macos, using · Missing: agents, agent, cursor
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: ios, month · Missing: mobile apps, personal, entrepreneurs
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
45%45% 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
19%19% 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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