Qeexo’s New Embedded Machine Learning Platform Supports AI on Edge Devices

December 6, 2018 Laura Dolan

Mountain View, CA. Qeexo is launching its Machine Learning Platform for embedded products and applications. Its lightweight, general-purpose design can execute local inferencing on an embedded edge device in real-time and sans cloud reliability. The solution already operates over 170 million smartphones and tablets globally with Qeexo’s FingerSense and EarSense products.

Qeexo-powered sensors are conducive for industrial settings, as they can monitor and analyze processes, equipment, and products of interest in factories, helping machines run more smoothly. For automotive, Qeexo Embedded Machine Learning sensors can transmit real-time road and automobile conditions for immediate response or predictive maintenance of the car itself.

Qeexo’s Machine Learning Platform features include:

  • Millisecond-Latency
  • Ultra-low Power Consumption, Memory, and Processing Requirement
  • Sensor Data

“Qeexo Embedded Machine Learning can help any company make sense of the constant streams of data their products and equipment are already gathering or could be gathering,” said Sang Won Lee, CEO of Qeexo. “As silicon chips continue to become more powerful and less expensive, we believe that the trend is for machine learning to move towards the edge.”

To learn more, visit www.qeexo.com.

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