of Machine Learning
at the Edge
Qeexo develops machine learning solutions that generate actionable insights from sensor data.START FREE TRIAL
First automated ML platform for an Arm Cortex-M0/M0+
Supporting a wide range of machine learning algorithms, Qeexo AutoML is designed for lightweight, Cortex-M0-to-M4-class processors, yielding ultra-low power consumption and latency.
Automatically Build Machine Learning
Solutions with Sensor Data
Why Qeexo AutoML?
The Cortex-M0 and Cortex-M0+ processors pack high performance with very low power consumption, and the added support of the Qeexo AutoML platform enables application developers to easily add intelligence to small devices such as wearables, making a world of one trillion intelligent devices a closer reality.
Combined with Arduino Nano 33 IoT, users [of Qeexo AutoML] can quickly create smart IoT sensors that can perform analytics at the edge, minimize communication, and maximize battery life.
By automating the development of ML solutions for advanced industrial IoT applications such as condition monitoring and predictive maintenance, Qeexo AutoML eases the usability of our products.
The Qeexo AutoML platform is a great tool to enable ML-based features without [too much engineering] effort.
The UI is clean, intuitive, and provides end-to-end model deployment support. We no longer have to fumble with various tools for collecting data, building models, and deploying solutions.
FEATURED PRESS Qeexo AutoML Enables Machine Learning on Arm Cortex-M0 and Cortex-M0+
First company to build an automated ML platform for the Arm Cortex-M0 and Cortex-M0+ processor MOUNTAIN VIEW, Calif. (PRWEB) September 09, 2020 Qeexo, developer of an automated machine learning (ML) platform that accelerates the deployment of tinyML at the edge, today announces that its Qeexo AutoML platform now supports machine learning on Arm® Cortex®-M0 and […]Qeexo, Co. 09 September 2020
PRESS LETU Machine Learning Contest Video
Click HERE to view the video Full URL to video source: https://www.kltv.com/video/2020/11/06/machine-learning-contest/KLTV 12 November 2020
PRESS Can a piece of drywall be smart? Bringing machine learning to everyday objects with TinyML
So-called smart devices like Amazon Echo and Google Nest made early headway into our homes. But will devices as small as a vibration sensor soon outsmart an Echo? Here's a look under the hood of "TinyML."Diginomica 11 November 2020
PRESS LeTourneau University students design artificial intelligence projects for contest
Since mid-September, 10 teams of LeTourneau University engineering students have been working on projects involving artificial intelligence to enter into a contest. Winners of that contest were announced Friday in the lobby of the Glaske Engineering...Longview News-Journal 09 November 2020
Register for a free evaluation or other SaaS options.
Interested in leveraging sensor data from your devices? We're happy to help!
Submit your information and we will get in touch with you.