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Zenitizer – Clean and Simple Meditation for Apple Devices

Hacker News

Zenitizer – Clean and Simple Meditation for Apple Devices

Hey everyone! After running a public beta for Zenitizer over the last couple months, it is now officially available to download on the App Store: https://zenitizer.app/install My goal was to create a clean and simple (yet highly customizable) timer for "unguided meditations" (i.e. no spoken word content). The timer is customizable with a range of different bells and soothing background soundscapes. Regular interval bells remind the user to return their focus on the breath when thoughts drift off. You can save your favorite timer presets as "routines" and quickly play them via Siri or Home Screen Widgets. Users are motivated to keep up a regular meditation practice by setting a daily goal and tracking their meditation streak: It is sufficient to meditate even one minute a day to keep the streak - you only need to reach your goal to grow the streak. I wanted to prevent users from feeling pressure about breaking streaks and reward them for meditating at all, however little. Personally, I am particularly happy about Zenitizer's deep Shortcuts integration. Just say "Hey Siri, meditate with Zenitizer" or "Check my Zenitizer streak". With Shortcuts, you can also build cool automations like starting a meditation, setting a HomeKit scene and enabling Do Not Disturb Focus Mode with a single command.

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Indie HackersFits the IH revenue-focused audience · 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.
TrustMRRFits verified-revenue profile · Strong signals: personal, month, users · Missing: mobile apps, ios, entrepreneurs
66%66% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, user, single · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
42%42% 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
30%30% 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
20%20% 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.

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