Universal Model Translation

From research to production. From any framework to any platform.

The Challenge

AI research moves fast, but production systems don't. Example: the best model for your use case is in JAX, but your infrastructure is PyTorch. The target is Apple Silicon, but the model was built for CUDA.

The Solution

I translate AI models across frameworks and adapt them to your target hardware. Shorten the path from research to production across platforms.

Universal Model Translation - AI models across frameworks and hardware

Examples

Towards milli-joules per token? AI on the Apple Watch

Ultra-efficient AI inference on wearable devices using MLX and Apple Silicon optimization.

Ready to Get Started?

Send a short email with your AI challenge and we'll take it from there.

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