LumifyHub – A productivity OS for work and personal growth

Hacker News

Hey! I’ve been working on LumifyHub – a productivity platform that brings together task management, journaling, time tracking, and personal goal-setting into one clean interface. I use the app for myself since before I was using Notion, Trello, iPhone Notes, and a few other apps to manage my work/personal life. LumifyHub tries to merge both worlds – your projects and your personal growth – into a single, distraction-free dashboard. What it does: Kanban boards for projects and tasks A work log timeline (this is great for devs!) Daily journaling and gratitude tracking You can explore all the features here: https://www.lumifyhub.io It's still early, and I’m actively building this solo, but I’d really appreciate any feedback. Thanks for checking it out!

Visit product View on Hacker NewsJun 20, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, single, tasks · Missing: mac, agents, macos

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

44%44% 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: platform, interface · Missing: plus, intuitive, reviews

22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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