An extensive offer to meet the needs of any Edge AI project

STMicroelectronics offers several tiny ML solutions to embed AI on microcontrollers, microprocessors, and smart sensors. Our extensive offer allows you to find the right tool for your project, regardless of your level of expertise in machine learning.

With NanoEdge AI Studio, you can easily generate ML libraries for your embedded devices, with millions of pre-built models available. This means you do not need to collect and document large and complex data sets. Your model can also be self-trained on your device.
If you already have AI knowledge, STM32Cube.AI helps you to port and optimize trained artificial neural networks on STM32 microcontrollers.
For developers who work with OpenSTLinux, we have developed a complete framework allowing you to easily integrate AI models.

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STMicroelectronics Edge AI solutions

Nanoedge AI Studio

Automated Machine Learning tool for STM32 MCU

NanoEdge AI Studio is a user-friendly desktop tool to design and generation of standard ML libraries optimized for STM32. There are four types of libraries: anomaly detection, feature classification (1-class and n-class), and extrapolation of temporal and multivariate signals.


The AI model optimizer for STM32 MCU

STM32Cube.AI is a free tool that helps you optimize the performance and memory of trained AI models in your STM32 project. It supports all major AI framework formats such as TensorFlow™ Lite, Keras and many others via the ONNX standard.

AI for Linux

A complete AI framework for OpenSTLinux on STM32 MPU

For those working on STM32 MPUs, X-LINUX-AI is a collection of libraries and runtimes that simplify the integration of trained AI models in your OpenSTLinux-based projects.

STM32 hardware

A wide range of ICs and boards for Edge AI

We offer a wide range of microcontrollers, microprocessors and smart sensors to develop Edge AI applications with an optimized power consumption, footprint and cost