Mirai

By running AI entirely on-device on iPhone, iPad, Mac, and Apple Silicon hardware Mirai delivers instant responses, ensures that sensitive user data never leaves the device, and reduces AI operating costs by up to 40% compared to equivalent cloud-based deployments.

The platform supports a range of model sizes from 0.3 billion to 7 billion parameters, all optimized specifically for Apple's hardware architecture and neural engine.

This size range covers the full spectrum from lightweight models suitable for simple classification and conversational tasks to more capable models that can handle complex reasoning, code generation, and nuanced language understanding giving developers the flexibility to match model capability to task requirements without overpaying for unnecessary compute power.

Developer experience is a central design priority for Mirai. Integration is designed to be fast enough that a single developer can set up on-device AI within minutes rather than days, without requiring a dedicated machine learning team or extensive MLOps infrastructure.

The platform provides a clean SDK with straightforward APIs, handling the complex model optimization, quantization, and hardware acceleration layers underneath so that developers can focus on building product features rather than AI infrastructure.

Mirai's intelligent routing engine goes beyond simple model deployment by automatically balancing performance, privacy, and cost across different inference scenarios.

Rather than forcing all AI calls through the same model regardless of complexity, the routing engine evaluates each request and directs it to the most appropriate model variant maximizing response quality while minimizing unnecessary resource consumption.