ST EDGE AI SUITE

Your stepping stone to enabling edge AI on MCUs, MPUs, and smart sensors.

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10+

Free software and tools.

Be inspired.

50+

Case studies.

Find support.

20+

Resources and documents.

Dive into the edge AI world

Find out more about the products and tools that enable edge AI in your embedded project.

Explore our edge AI lab

Discover inspiring application examples leveraging the power of edge AI and STM32 microcontrollers and microprocessors.

Generate optimized ML libraries

Find and configure the best edge AI library in a few steps, based on minimal amount of data.

Program and evaluate MEMS sensors

Analyze data, develop embedded AI features, evaluate embedded libraries, and design algorithms without any coding.

Benchmark AI neural network models

Use online AI benchmarking services. Test your models on ST devices remotely.

Demo: classify motor faults

Learn how we added machine learning features to an industrial machine based on vibration data.

Online event

Discover the STM32N6 MCU at the STM32 Summit

Follow the keynote for the product unveiling and gain useful insights on the MCU during the tech dives.

Patrick Aidoune

General Purpose MCU Division General Manager, STMicroelectronics

All the tools available in the ST Edge AI Suite

X-LINUX-AI

HAND POSTURE TOF

HIGH SPEED DATALOG

MEMS STUDIO

NANOEDGE AI STUDIO

ST EDGE AI CORE

ST EDGE AI DEVELOPER CLOUD

MODEL ZOO

STELLAR STUDIO

STM32CUBE.AI

ST AIoT CRAFT

By bringing solutions to engineers and data scientists at every stage of their development, the ST Edge AI Suite accelerates edge AI adoption.

FAQ

Quickly find clear, concise answers to the most common questions.

Frequently asked questions on how to deploy edge AI in embedded projects.

Edge AI refers to the enabling technology that runs AI algorithms and models directly on devices such as microcontrollers, microprocessors, and sensors embedded in industrial and automotive applications. Deploying AI at the edge enables real-time data processing directly at the source of data collection, offering faster response times, enhanced data security, and greater bandwidth efficiency. Read more about the advantages it offers here.

  • For all ST devices: the ST Edge AI Core CLI version and the ST Edge AI Developer Cloud allow users to optimize and evaluate AI model performance on any ST hardware.
  • For STM32 MCUs: STM32Cube.AI (X-CUBE-AI) enables neural network optimization. NanoEdge AI Studio is an AutoML tool.
  • For STM32 MPUs: developers can use AI for OpenSTLinux (X-LINUX-AI) and the STM32MP2 offline compiler for Linux AI frameworks.
  • For Stellar MCUs: StellarStudioAI is a software package for neural network optimization and deployment.
  • For MEMS sensors with a machine learning core: the online tool ST AIoT Craft and the desktop tool MEMS Studio can be used for data analysis, algorithm design, and model optimization. The MLC model zoo provides pre-optimized models.
  •  For MEMS sensors with an ISPU: the MEMS Studio enables data analysis and model optimization. The ISPU model zoo provides pre-optimized models."

The ST Edge AI Suite facilitates the deployment of AI models by allowing users to easily find the right tool for their project:

  • Data logging: capturing the sensor data necessary for AI model training.
  • Auto ML: automatically generating optimized machine learning algorithms.
  • Model optimization: optimizing AI models and generating associated code for target devices.
  • Validation and testing: ensuring model performance meets deployment criteria.
  • Online benchmarking: testing model performance on ST hardware using the cloud.

Embedded developers can also benefit from:

  • The model zoo: simplifying the deployment of AI models on supported devices.
  • Documentation for more guidance through the deployment process.

The tools featured in the ST Edge AI Suite are free of charge, including for commercial use, which contributes to reducing the costs of running AI on embedded devices.

The ST Edge AI Suite is a set of tools for integrating AI features in embedded systems. It supports STM32 microcontrollers and microprocessors, Stellar automotive microcontrollers, and MEMS smart sensors, and includes resources for data handling and AI model optimization and deployment. Users will also find educational insights and real-world case studies to simplify their design journey.

The ST Edge AI Suite is compatible with a wide range of sensors as shown in the breakdown:

  • Time series sensors: accelerometers, gyroscopes, magnetometers, temperature sensors, ToF ranging sensors and other sensors that output data over time. 
  • Audio sensors: microphones are the primary sensors for capturing audio data. 
  • Vision sensors: cameras (RGB, B&W, IR), Time of Light sensors, radar, lidar, and more.

The ST Edge AI Suite is optimized for ST sensors, including MEMS devices with an MLC and the ISPU. It supports any sensor as long as the data provided is compatible with the tool requirements.

The tools in the ST Edge AI Suite can support different types of data:

  • High Speed Datalog:
    • Time Series Data
  • NanoEdge AI Studio:
    • Time Series Data
  • STM32Cube.AI (X-CUBE-AI):
    • Time Series Data
    • Audio Data
    • Vision Data
  • MEMS Studio:
    • Time Series Data (from the MEMS sensor)
  • StellarStudioAI:
    • Time Series Data
    • Audio Data
  • AI for OpenSTLinux (X-LINUX-AI):
    • Time Series Data
    • Audio Data
    • Vision Data
  • ST AIoT Craft:
    • Time Series Data (from the MEMS sensor)