Nordic Edge AI

Ultra-low-power edge AI across the industry's broadest range of applications

Your data. Your model. Your edge.

From saving bandwidth and energy to more responsive real-time performance, implementing AI in your embedded applications offers massive benefits beyond the buzzwords. Nordic Semiconductor offers two unique technologies, Neuton models and Axon NPU, exclusively to our customers, to cover the industry's broadest range of devices, applications, and customer needs.

Neuton models

Custom Neuton models are ultra-tiny edge AI models built from your data using our patented network-growing algorithm, ideal for running edge AI on any Nordic SoC or SiP using its main application core (CPU).

10×: Smaller memory footprint than TensorFlow Lite models

10×: Faster and more energy efficient than TensorFlow Lite models on the CPU

< 5 KB: Average memory footprint of custom Neuton models created with our framework

Axon NPU

The Axon NPU is our dedicated AI accelerator core, designed to increase the speed and efficiency of TensorFlow Lite models, built into our most capable SoCs.

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15×: Faster and more energy efficient than running the same TensorFlow Lite model on the CPU

8×: More energy efficient compared to the closest competing product

7×: Faster inference than the closest competing product

Nordic Edge AI Lab

Nordic Edge AI Lab is your gateway to ultra-efficient edge intelligence. In the Edge AI Lab, you can create high-performance AI models ready to deploy on Nordic’s ultra-low-power SoCs, for both CPU-run and NPU-accelerated edge AI.

Choose between three different paths for edge AI model creation:

Custom Neuton models - Ultra-efficient CPU-run edge AI for any Nordic SoC
Text-to-wake-word - No-data generation of wake word models for Axon NPU
Model builder for Axon NPU - Build models with your custom dataset and architecture

Documentation for the Edge AI Lab is available here.

Go to the Edge AI Lab

Build your own

Gesture recognition remote control

For a hands-on example, you can follow our guide to recreate our gesture recognition remote control, using the Nordic Thingy:53.

Read the getting started documentation to learn how to create your own