Inspiration
Living as a remote professional, I struggled to maintain language fluency beyond textbook learning—so I built a tool that embeds learning into daily life, not as an extra chore. Real-world interactions (calls, notifications, media) felt like the missing piece for genuine proficiency.
What it does
Language Immersion AI turns everyday phone use into seamless language learning: translated system notifications, AI-powered daily conversations, realistic phone call simulations, personalized media recommendations, and an AI journal for writing practice—all adapting to your CEFR proficiency level.
How we built it
Started with user research on professional language learners’ pain points, mapped core workflows (onboarding, notification translation, call simulation), built mobile-native interfaces (iOS/Android), integrated AI/translation APIs, and layered in progress-tracking & subscription logic. Tested with 50+ beta users to refine immersion progression rules.
Challenges we ran into
Balancing real-time notification translation with battery efficiency; ensuring AI conversation flow felt natural (not robotic); calibrating pronunciation feedback for regional accents; securing end-to-end encryption for user data while maintaining feature speed.
Accomplishments that we're proud of
Creating a truly adaptive immersion system that grows with users (15% to 100% translation); 60+ realistic call scenarios tailored to real-life needs; sub-2-second AI response times for conversations; seamless Stripe integration for fair subscription access.
What we learned
User-centric design beats "one-size-fits-all"—learners prioritize real-world utility over generic drills. AI accuracy depends on context (not just language), and mobile background services require meticulous optimization for performance/ privacy.
What's next for this project
Expand the media library to include more regional content (e.g., local podcasts/shows); add industry-specific call scenarios (business/healthcare); refine accent adaptation for pronunciation feedback; explore offline access for core practice features.
Built With
- amazon-web-services
- firebase
- kotlin
- reactnative
- swift
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