Solarm – a simple iOS sunrise alarm I made to improve waking up

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I’ve always struggled with waking up feeling groggy, even with enough sleep. A few months ago I started experimenting with waking up around local sunrise instead of using a fixed alarm time. It ended up helping me more than I expected — mornings felt calmer, and the wake-up was less abrupt. I couldn’t find an app that did this cleanly without a bunch of extra features, so I built Solarm: a small iOS app that adjusts your alarm based on the sunrise in your location. What it does - calculates the sunrise for your city each day - adjusts your wake-up time automatically - optional “sunrise + X minutes” offset - works even with Do Not Disturb - no accounts, no backend, everything on-device Why I’m posting I’d like to hear impressions from people who care about sleep, circadian rhythm, or just smoother mornings. I’m especially interested in how well the sunrise-based approach works (or doesn’t) for others. App Store link: https://apps.apple.com/ua/app/sunrise-alarm-natural-clock/id... I also have free offer codes for anyone who wants to try the full version — just mention it in the comments, I will provide you a link. Thanks for taking a look. Happy to answer questions.

Visit product View on Hacker NewsNov 30, 2025

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

94%94% 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, apps, using · Missing: mac, agents, macos

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

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

63%63% 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

47%47% 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

35%35% 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 · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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