The app I built to manage my anxiety

Hacker News

Hey HN, I'm excited to introduce Lume to you today! As the developer behind this wellness companion, I created Lume to help people get ahead of their stress and anxiety by alerting them before they even feel it. Lume isn't just another wellness tracker. It’s built with proactive insights, using patterns in your data to help you understand and manage stress and anxiety in real-time. My own experience inspired this approach – I noticed how shifts in my resting heart rate often correlated with rising stress, and I wanted a way to address it sooner. Lume gives users that early nudge, along with personalized tips to help keep stress in check before it overwhelms. One thing I’m particularly proud of is how Lume caters to a balanced lifestyle. It’s more than just tracking – Lume’s insights span across daily pillars like sleep, exercise, and mindfulness, making it a well-rounded companion for your mental well-being. If Lume resonates with you, I’d love your support! Thank you for being a part of this journey toward a calmer, more balanced life: https://apps.apple.com/app/lume-stress-wellness-coach/id6627...

Visit product View on Hacker NewsNov 18, 2024

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

84%84% 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, user · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, apps, users · Missing: mobile apps, ios, 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: excited, io · Missing: https docs, just released, exist

36%36% 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: soon, users · Missing: plus, platform, intuitive

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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