Machine learning at the NanoEdge

Try it for free today!

NanoEdge AI Studio removes traditional AI barriers. It is designed for companies that either do not have expert resources in machine learning or that wish to provide their data scientists with a complementary tool for embedded environments.

NanoEdge™ AI Studio will let you easily create a machine learning static library to embed in your main program running on any ARM© Cortex© M microcontroller. When embedded in microcontrollers, it gives them the ability to locally “learn” and “understand” sensor patterns, by themselves, without the need for a data scientist or creation of a pre-trained neural network.

NanoEdge AI Studio Quick Technical Facts

  • Runs autonomously on the developer’s workstation under Windows or Linux. Thus, no data is transmitted outside the customer’s environment.
  • Will automatically test, optimize and calculate the best algorithmic combination among more than 500 million possible combinations, after the developer has described the targeted environment.
  • Provides the selected algorithm as a C library that is easily embeddable in the microcontroller.
  • Generates libraries that require only 4K to 16K of RAM, making them the most optimized AI algorithms in the industry.
  • Enables the execution of unsupervised learning, inference and prediction on the device edge, opening new classes of small, low-power, low-cost devices to AI for the first time.

The Promise of the Edge

The promise of the Edge is to be able to process data on the periphery of the network, far from the data centers. Cartesiam innovates and pushes intelligence to the edge, directly into your objects or devices. To achieve this feat, mathematicians designed and developed NanoEdge AI™ a set of Machine Learning algorithms to understand and exploit the data in microcontrollers, directly where the data is generated.

Contact Richardson RFPD with questions or to schedule a demo

NanoEdge AI Studio
in four easy steps

a. Choose your microcontroller type
b. (ARM® Cortex® M0 to M7)
c. Choose the maximum amount of RAM that you wish to allocate to your library
d. Choose the sensor type used to collect data

NanoEdge Ai Studio uses both regular and abnormal datasets to test several machine learning model’s performance against your data, Along with a multitude of different (hyper) parameters and signal processing algorithms.
With NanoEdge AI Emulator, you can emulate the behavior of your custom NanoEdge AI Library directly on your PC, as if the library was running on your microcontroller.
Choose your compilation flags and download your final static library ready to learn and infer in your microcontroller.

Packages & prices

Fully functional NanoEdge AI Studio (Windows 10 and Ubuntu versions)

Solo

Entry

For embedded developers who want to assess technology and rapidly build a prototype

• Full access to all supported library
• Full access to library selection
• Rapid testing using emulator

Unlimited number of prototypes on selected partners demo boards

FREE

Pro

For enterprises who want to build a ready to run solution for production purpose

All entry capabilities plus:

• Full technology support and use case validation
• Automatic access to all new algorithms and technical improvement
• Flexible options for individual developers or teams

Unlimited number of prototypes on any
arm Cortex M

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Corp

For enterprises who want to deploy a family of devices

All pro capabilities plus:

• Unlimited number of developers
• Unlimited number of projects
• Unlimited number of devices deployed
• Multi year dedicated R&D support

PLEASE CONTACT US

Additional Resources

Frequently Asked Questions: Artificial Intelligence and Machine Learning with Cartesiam

Cartesiam Use Case: Aging and normal wear of machinery

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Cartesiam Storefront

On the Richardson RFPD website.

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