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.
Long-Form On-Device Transcription with SpeechAnalyzer in Rork Max's Native Swift
Implementation notes on rebuilding long-form, offline transcription with iOS 26's SpeechAnalyzer and SpeechTranscriber after hitting the walls of SFSpeechRecognizer. Covers model asset downloads, feeding audio through an AsyncStream, drawing volatile vs. final results, and the boundary design for Rork Max native code and bridging from Expo — with the pitfalls I actually hit.
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.
Quietly Dialing Back Heavy Work When the Device Gets Hot or Enters Low Power Mode
How to watch ProcessInfo's thermalState and Low Power Mode and degrade heavy work in stages when the device is hot or the battery is low, with working Swift code.
Receiving On-Device AI Output as Typed Data with Foundation Models Guided Generation
How to receive Foundation Models output as typed Swift structs instead of free text, with working code for Guided Generation and Tool Calling on-device.
On-Device Translation in a Rork Max App with iOS 18 — Free, Offline, Multilingual
Add free, offline, real-time translation to a Rork Max Swift app using the iOS 18 Translation framework. Covers checking language availability, batch translation, and avoiding empty results — all with working Swift code.
On-Device Image Tagging in Rork Max Swift Apps with Foundation Models Image Input
WWDC26 gave the on-device Foundation Models model image input. Here is how to add image tagging and captioning to a Rork Max Swift app entirely on-device, including the availability gate, structured output, and Vision interop.
Calling Apple Foundation Models from a Rork (Expo) App: Bridging On-Device AI Through a Native Module
Rork generates Expo (React Native) apps, but Apple Foundation Models ships as a Swift framework you can't touch from JavaScript. Here's how to write an Expo Modules API bridge, gate it by availability, and fall back to the cloud on unsupported devices.
After WWDC26, Reselecting What an Indie Should Build Right Now
Now that on-device AI is free for small developers, the premises of app planning have quietly shifted. Here are five questions to choose what to build with Rork at the concept stage.
Routing inference on-device first and escaping to the cloud only when it's worth it, in a Rork app
Build a tiered, fallback-based inference router in a Rork (Expo) app: cache to on-device to Private Cloud Compute to a remote API (Claude/Gemini). Working TypeScript covering budgets, timeouts, caching, and image routing.
A Three-Layer AI Cost Design for Rork Apps After Apple Opened Foundation Models to Small Developers
Apple now offers Foundation Models on Private Cloud Compute at no charge for developers under two million first downloads. Here is a three-layer cost architecture for Rork apps, with a simulation script and working bridge code.