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Optimize and deploy AI models for edge devices, NPUs, and local inference. Reduce latency, improve privacy, and cut cloud costs.
Run inference locally with sub-10ms latency. No network round-trips, no cloud delays.
Keep sensitive data on-device. No data leaves your infrastructure. PIPEDA compliant.
Eliminate cloud inference costs. Reduce bandwidth usage. Lower infrastructure requirements.
Quantize and compress models with int8, int4, fp8, and GGUF formats. Reduce model size by up to 75% while maintaining accuracy.
Detect and configure target device capabilities. Support for AI PCs, Jetsons, Android, iOS, Raspberry Pi, and custom devices.
Measure latency, throughput, and hardware utilization. Compare optimization strategies and get recommendations.
Download optimized bundles, SDK scaffolds, Docker images, and deployment templates. Ready-to-use code for your platform.
Get starter code in TypeScript, Python, Java, Swift, and more. Consistent APIs across platforms.
Run inference locally without sending data to the cloud. Perfect for sensitive applications and offline scenarios.
Deploy AI assistants that work without internet connectivity. Perfect for field workers, remote locations, and privacy-sensitive environments.
Local tutoring and learning assistants that work on student devices. No cloud dependency, reduced costs, improved privacy.
Real-time inference at the edge for robotics and IoT applications. Low latency, high reliability, minimal power consumption.
On-premise vision analytics for retail stores. Customer behavior analysis, inventory tracking, and forecasting without cloud costs.
Upload your model, configure your target device, and get optimized bundles ready for deployment. Start with a free optimization or schedule a consultation.