Qeexo Named May “Partner of the Month” by Renesas for its AutoML Support

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Qeexo’s end-to-end system solution will enable customers to create highly optimized machine learning solutions

Combining Qeexo’s easy to implement AutoML platform with our flexible RA Family of MCUs will drive machine learning applications to the intelligent edge, providing customers with a sensor module reference design that is suitable for a multitude of smart IoT applications.

Qeexo, a company that has developed an automated machine learning platform that accelerates the deployment of smart IoT devices by enabling machine learning and data science at the edge/endpoint device, today announced that Renesas Electronics Corporation has chosen Qeexo as “Partner of the Month” for May 2020, as part of its Renesas RA Partner Ecosystem.

This honor reinforces Qeexo’s methodology that pairing the Qeexo AutoML platform with a flexible MCU hardware platform is a strong value proposition for edge/endpoint processing. Qeexo’s end-to-end system solution will enable customers to create highly optimized machine learning solutions for applications such as: predictive maintenance for industrial machine anomaly detection; gesture and context awareness algorithms for consumer/wearable use cases like fitness trackers and elderly care products; and integrating safety measures in smart appliances.

Qeexo and Renesas collaborated on a machine learning reference design featuring a multi-sensor module that showcases different AI machine learning use cases using the Qeexo AutoML platform and Renesas microcontrollers (MCUs), as well as other Renesas devices. The machine learning reference design is ideally suited for consumer, industrial, and automotive applications as it integrates many of the commonly used sensors in these applications such as accelerometer, gyroscope, humidity, light, microphone, and environmental/gas.

“It’s an honor to be chosen by Renesas as ‘Partner of the Month,’” said Sang Won Lee, CEO of Qeexo. “Renesas has been an important partner to Qeexo, both in terms of product development and market fit. We look forward to continuing to work with them to ensure that our technology is being deployed within the segments that can benefit the most from Qeexo’s speed to market, such as the Industry 4.0 initiative.”

“Renesas is excited to work with Qeexo and demonstrate the variety of opportunities that machine learning opens up for IoT devices,” said Kaushal Vora, Director of Strategic Partnerships & Global Ecosystem at Renesas. “Combining Qeexo’s easy to implement AutoML platform with our flexible RA Family of MCUs will drive machine learning applications to the intelligent edge, providing customers with a sensor module reference design that is suitable for a multitude of smart IoT applications.”

Qeexo will demo how to automatically develop machine learning applications with Qeexo AutoML on Renesas’ multi-sensor module reference design during its webinar, hosted by Arm and scheduled for May 20th, 2020. The hands-on tutorial will explore how to easily overcome implementation challenges of embedded machine learning. To sign up for the Arm webinar, please use the link: https://www.brighttalk.com/webcast/17792/406117.

About Qeexo
Qeexo is the first company to automate end-to-end machine learning for embedded Edge devices (Cortex M0-M4 class). Our one-click, fully-automated, Qeexo AutoML platform allows customers to leverage sensor data to rapidly build machine learning solutions for highly constrained environments with applications in mobile, IoT, wearables, automotive, and more.

Delivering high performance, solutions built with Qeexo AutoML are optimized to have ultra-low latency, ultra-low power consumption, and an incredibly small memory footprint.

As billions of sensors collect data on every device imaginable, Qeexo can equip them with machine learning to discover knowledge, make predictions, and generate actionable insights.

Spun out of Carnegie Mellon University, Qeexo is venture-backed and headquartered in Mountain View, CA, with offices in Pittsburgh, Shanghai, and Beijing. To learn more, visit http://automl.qeexo.com.

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Lisa Langsdorf
GoodEye Public Relations
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