Unforget, the note-taking app I always wanted: offline first, encrypted

Hacker News

Hi HN! I created Unforget out of years of frustration with Google Keep and the lack of alternative that met all my needs. I hope you find it useful too! Features include: - import from Google Keep - offline first including search - sync when online - own your data and fully encrypted - Desktop, mobile, web - lightweight, progressive web app without Electron.js - markdown support - programmable with public APIs - open source [1] While I still use org mode for long-form notes with lots of code, Unforget has become my go-to for quickly jotting down ideas and to-do lists after migrating the thousands of notes I had on Google Keep. In addition, I'm thrilled to announce the opening of our software agency, Computing Den [2]. We specialize in helping businesses transition from legacy software, manual workflows, and Excel spreadsheets to modern, automated systems. Please get it touch to discuss how we can help you or if you wish to join our team. [1] https://github.com/computing-den/unforget [2] https://computing-den.com

Visit product View on Hacker NewsJun 11, 2024

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

79%79% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

25%25% 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

14%14% 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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