Rork × Multimodal AI: Design Patterns for Building Intelligent Apps with Camera, Voice, and Text
Learn how to build multimodal AI apps with Rork that seamlessly integrate camera image recognition, voice input, and text analysis. Covers unified input layers, AI orchestration across Gemini, Claude, and Core ML, UX flow design, and production-ready error handling.
On-Device Image Classification: TFLite on React Native or Core ML on Rork Max — How I Chose After Building Both
Adding on-device image classification means choosing between TFLite on React Native and Core ML on Rork Max. I built the same feature both ways, measured the end-to-end breakdown, and worked out what the decision actually hinges on.
When Your Rork Hybrid AI Quietly Drifts to the Cloud and the Bill Creeps Up — Field Notes on Instrumenting Routing Decisions
A router that splits work across on-device, edge, and cloud layers will quietly drift toward the cloud when no one logs its decisions — flat traffic, rising bill. These are field notes on instrumenting routing to isolate the cause.
Design On-Device Core ML So Cold Start and Heat Don't Break It
Put on-device Core ML in the native Swift that Rork Max generates and you hit two walls before accuracy: the first inference is slow, and the device heats up and slows down. Here is a design built around cold start and a thermal budget, with working Swift.
Rork Max × ARKit × Core ML Integration Guide — Building Next-Gen Apps with AI and Augmented Reality
Master advanced AR development with Rork Max by combining ARKit and Core ML for real-time object recognition, 3D scene understanding, and on-device AI inference. Complete guide from LiDAR integration to App Store submission.
Building Apple Intelligence Apps with Rork Max — Writing Tools, Image Playground & Genmoji API Integration Guide
Learn how to integrate Apple Intelligence APIs — Writing Tools, Image Playground, and Genmoji — into native Swift apps using Rork Max, with working code examples and App Store submission best practices.