AI mobile apps I build with React Native and Expo
Expo is my default. It gives one TypeScript codebase for iOS and Android, EAS Build and Submit for the stores, and over-the-air updates so a prompt or UI fix ships without waiting for review. On top of it I add the AI layer: streaming chat with the Vercel AI SDK, speech-to-text and text-to-speech for voice assistants, camera and image understanding, and hybrid on-device plus cloud inference where privacy or offline use matters.
Behind the app there is always a backend I build for you — usually NestJS on PostgreSQL — that holds the API keys, meters usage, caches expensive calls and keeps AI costs predictable. Subscriptions run through RevenueCat, StoreKit and Play Billing, and analytics and crash reporting are wired in before launch, not after.
- Chat and voice assistants with streaming responses
- Camera and vision features: scanning, recognition, image-based search
- On-device inference with ExecuTorch, llama.rn or Core ML for offline and private use
- In-app subscriptions with RevenueCat, StoreKit and Play Billing
- Push notifications, offline-first sync and background processing
- App Store and Play Store submission, listing assets and OTA updates