For Developers

Intelligence for every device.Defined by you.

Three open-source tools that take you from model optimization to a published App Store app — no cloud required.

1
OptimizeEdge StudioCompress & optimize models
2
IntegrateEdge RuntimeOn-device inference SDK
3
ShipEdge ScaffoldGenerate a publishable app
11.3xPrefill SpeedupANE-GPU co-scheduling
79%GPU Power ReductionDisaggregated inference
20xFaster Model LoadingZero-copy memory mapping

Edge Studio

Preview

AI-powered model analysis & surgical optimization

Intelligent analysis engine that automatically detects redundant layers, inefficient neurons, and optimization opportunities. Our proprietary 7-step progressive pipeline performs neuron-level surgical pruning — not coarse-grained compression — with real-time perplexity monitoring to guarantee output quality.

  • ▶Intelligent model analysis: auto-detect redundant layers & low-efficiency neurons
  • ▶Neuron-level surgical pruning with perplexity-guided quality control
  • ▶7-step progressive optimization: vocab → neuron → layer → quantization
  • ▶Built-in benchmark at every step (disk, RAM, tok/s, PPL)

Edge Runtime

Preview

Proprietary inference algorithms for Apple Silicon

Purpose-built inference engine with proprietary ANE-GPU co-scheduling, disaggregated inference architecture, and zero-copy model loading. Not a wrapper — original algorithms that achieve 11.3x prefill speedup and 79% GPU power reduction through ANE batch dispatch and concurrent pipeline execution.

  • ▶Proprietary ANE-GPU co-scheduling: 11.3x prefill acceleration
  • ▶Disaggregated inference: ANE prefill + GPU decode in parallel
  • ▶Zero-copy model loading: 20x faster with no memory spike
  • ▶Native support for Edge Studio's non-standard optimized architectures

Edge Scaffold

Preview

The definitive edge AI deployment solution

The only end-to-end pipeline from optimized model to published App Store app. Integrates Edge Runtime's proprietary inference, On-Demand Resources for intelligent model delivery, and built-in ESG carbon tracking — a complete deployment solution that no other platform offers.

  • ▶End-to-end: optimized model → App Store app in one pipeline
  • ▶ODR-powered intelligent model delivery (no bundling large files)
  • ▶One config file: app name, model, system prompt — ship in minutes
  • ▶Built-in ESG carbon savings tracking for sustainability compliance

Quick Start

import EdgeInference

let engine = LLMEngine()
try await engine.load(config: .find(modelID: "qwen3.5-0.8b")!)

for try await chunk in engine.generate(
    messages: [.user("What is edge AI?")]
) {
    print(chunk.text, terminator: "")
}

5 lines of Swift — load a model, stream tokens. That's it.

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