AI-Ready Software Engineering
Cross-Platform Mobile Apps
Flutter and React Native mobile applications with on-device ML inference, real-time AI feature integration, and production-grade cloud connectivity.
The problem
Enterprise AI features tacked onto existing mobile apps suffer from poor state management for async AI responses, missing offline capability, and camera/microphone integrations that were never designed for ML pipelines.
Our approach
We build mobile applications AI-first from the ground up: on-device ML inference, real-time streaming integration, camera overlay UIs for computer vision, and background task sync.
How we deliver it.
Mobile is where enterprise AI meets end users, and where most AI features underdeliver because the app was bolted onto the AI after the fact.
What's included
Every deliverable, defined.
01Flutter (iOS + Android) and React Native development
02On-device ML inference with TensorFlow Lite / Core ML
03Real-time streaming: WebSockets and SSE on mobile
04Camera overlay UIs for computer vision features
05Voice input with streaming speech-to-text integration
06Offline-first architecture with background sync
07Riverpod / Zustand state management for AI interactions
08App Store and Google Play deployment with CI/CD