Daily Reliever – An AI-Powered Daily Journal for Motivation

Hacker News

Hello HN, I'm excited to share Daily Reliever ( https://gen-gen.web.app/ ), an experimental web app that leverages AI to offer personalized motivation based on your daily experiences. Simply input your day's events and receive motivational feedback instantly. Built using Flutter, this tool is for anyone needing a bit of positivity and motivation at day's end. Despite language and cultural barriers, I've worked to make it inclusive and intuitive with the help of AI. Your feedback is invaluable as I continue refining it. Remember, it's a supplementary tool, not a replacement for professional help. Enjoy exploring! Thank you!

Visit product View on Hacker NewsJun 19, 2023

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

68%68% 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: using · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

46%46% 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, lua, io · Missing: https docs, just released, exist

40%40% 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: intuitive · Missing: plus, platform, reviews

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

20%20% 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.

Correct prediction on native model

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