"Flawesome” – A Digital Diary with Some Aditional Flawesome Features :)

Hacker News

Its a completely free, Open-source cross platform application written in React and Electron. Its combination of a Calendar, Rich Text Editor, a Sticky Notes and a ToDo list. The Editor, Sticky Notes and Todo list are driven by the calendar that will help you organize your work and thoughts per day. This makes it more like a digital diary with some additional features. A spotlight like search component is also integrated to help you search the content. https://github.com/ashishBharadwaj/flawesome Give it shot! If you like it Give a Star on Github. It really Helps :)

Visit product View on Hacker NewsApr 23, 2020

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Actual performance

6points

Did not reach leaderboard

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: notes, open · Missing: mac, agents, macos

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

16%16% 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

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

Incorrect prediction on native model

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