Qeexo AutoML selected as a 2021 CES Innovation Awards Honoree!
Qeexo AutoML shortlisted for the 2020 AIconics Awards!
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 BLOG Introducing Qeexo Model Converter
Our latest API service for fitting your existing ML models onto an embedded target as small as a Cortex-M0+! Qeexo AutoML offers end-to-end machine learning with no coding required. While this SaaS product presents a wholistic user experience, we understand that machine learning (ML) practitioners working in the tinyML space may want to use their preexisting models that they’ve already spent a lot of time and efforts to finetune. To these folks working on tinyML applications, fitting the models onto embedded hardware with constrained resources is the final step before they can test their models on the embedded Edge device. However, this step requires a specialized set […]Gilbert Tsang, Director of Product Management 29 April 2021
PRESS Building effective IoT applications with tinyML and automated machine learning
IoT enables continuous monitoring of environments and machines using tiny sensors. Advances in sensor technologies, microcontrollers, and communication protocols made mass production of IoT platforms, with many connectivity options, possible at...Embedded 27 January 2021
PRESS The insideBIGDATA IMPACT 50 List for Q1 2021
The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine...insideBIGDATA 05 January 2021
PRESS Big Data Industry Predictions for 2021
2020 has been year for the ages, with so many domestic and global challenges. But the big data industry has significant inertia moving into 2021.InsideBigData 29 December 2020
Automate tinyML Development & Deployment with Qeexo AutoML
- March 9, 2021 8:00 am PST, 4:00 pm GMT, 10:00 am CST
- Tina Shyuan, Director of Product Marketing at Qeexo
Join Tina for a hands-on workshop of how to automatically build multiple ML models with Qeexo AutoML on the ST SensorTile.box!
Truly Smart Interactivity with Sensors and ML at the Edge
- April 15, 2021 9:10 am PST, 4:10 pm GMT, 10:10 am CST
- Chris Harrison, CTO
Come listen to our CTO, Chris Harrison, speak about enabling smart sensors at the Edge with machine learning at MEMS & Sensors Technical Congress (MSTC).
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