InputDojo

Language learners preparing for standardized exams face a specific problem: generic apps don’t map to the vocabulary lists and grammar patterns that exams actually test, so practice time and test-day readiness stay poorly correlated. InputDojo addresses this by building study plans around exam structures — JLPT and HSK levels — and layering spaced repetition over vocabulary drawn from authentic content rather than curated textbook sentences. The workflow runs on both mobile and web, so reviews fit into transit time, and speech practice with instant feedback closes the loop that silent flashcard drills leave open.

The differentiating feature is AI-personalized content from native media. Instead of a fixed corpus, the vendor describes a system that surfaces vocabulary in context from real-world material, which means the words you encounter look and sound the way a native speaker actually uses them. Spaced repetition then schedules those words based on individual mastery signals rather than a generic decay curve — so a learner who nails ‘kanji reading’ but fumbles pitch accent gets a different review schedule than one with the opposite gap.

Where InputDojo fits well: self-directed learners who want exam-aligned structure without enrolling in a course, or learners studying less common language pairs that mainstream apps underserve. Where it breaks: the platform has no API the vendor describes, no self-hosted option, and no data export path visible in the source documentation. Learners who want to integrate progress tracking into a broader LMS or analyze their own retention data will find the platform a closed system. AI features — including the personalized study plan layer and speech feedback — are paid-only features, meaning the free tier is closer to a trial than a permanent option for the core value proposition.