Open-source plugin streamlines edge AI deployment
Analog Devices and Antmicro have released AutoML for Embedded, a tool that simplifies AI deployment on edge devices. Part of Antmicro’s hardware-agnostic, open-source Kenning framework, it automates model selection and optimization for resource-constrained systems. The tool helps users deploy models more easily without deep expertise in AI or embedded development.
AutoML for Embedded is a Visual Studio Code plugin designed to integrate seamlessly into existing development workflows. It works with CodeFusion Studio and supports direct deployment to ADI’s MAX78002 AI accelerator MCU and MAX32690 ultra-low power MCU. The tool also enables rapid prototyping and testing through Renode-based simulation and Zephyr RTOS workflows. Its support for general-purpose, open-source tools allows flexible model optimization without locking developers into a specific platform.
With step-by-step tutorials, reproducible pipelines, and example datasets, users can move from raw data to edge AI deployment quickly without needing data science expertise. AutoML for Embedded is available now on the Visual Studio Code Marketplace and GitHub. Additional resources are available on the ADI developer portal.
AutoML for Embedded product page
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