Offline-first note-taking web application

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Hi HN! Cryptaa is an offline-first note taking web application that focuses on speed and security. I've been working on it for a few months, and decided to show it as I think it is good enough for daily usage (I've been dogfooding it). I had a few "simple" requirements for my application: - Manual data encryption & decryption: I'm not overly paranoid about data security/data breaching, but sometimes, I do want my data to be stored securely (login credentials or credit card numbers). If I really need the functionality, I can encrypt the text on another website, then paste it to the application. It is not the best UX, however. - Speed: it should feel fast/snappy enough (if you definitely want a number, maybe it is less than 100ms). - Many devices (at least mobile/Android and desktop/Linux) data synchronization: I have an Android phone, and two Linux desktops, and want to have the same data between them. - Web version: I don't like installing new applications whether it's on my phone nor my computer. It surprised me as I found nothing that ticks all the boxes, so I decided to build Cryptaa. The technical stack is Svelte/SvelteKit, XState, and Triplit. The source code is available at https://github.com/thanhnguyen2187/cryptaa . Please let me know if you find the application useful or have any question/suggestion! Thanks!

Visit product View on Hacker NewsJun 25, 2024

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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

63%63% 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: computer, new, code · Missing: mac, agents, macos

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

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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