I

I built KanjiMaster.ai – A tool for learning Japanese Kanji

Hacker News

I built KanjiMaster.ai – A tool for learning Japanese Kanji

20 years ago, I struggled to learn Japanese Kanji and wished there was a tool to make it easier. Fast forward to today — I’ve built one: < https://kanjimaster.ai >. It’s my first product, and it’s a web app where you can explore kanji, create study collections, and test your knowledge with quizzes. Features: - Search thousands of kanji with meanings, readings, and real-world examples - Create custom kanji collections - Take quizzes to test readings, translations, and recognition - Track your learning progress My goal is to build the ultimate Kanji study app, and I’m just getting started. I’d love to hear what you think — any feedback is welcome!

Visit product View on Hacker NewsFeb 20, 2025

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

90%90% 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 · Missing: mac, agents, macos

63%63% 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

54%54% 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

39%39% 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 · Missing: plus, platform, intuitive

35%35% 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

17%17% 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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