Qeexo
Qeexo AutoML is a one-click, fully-automated platform allowing customers to rapidly build machine learning solutions for highly-constrained environments using sensor data. Machine learning engines built with AutoML are lightweight and designed to run locally on Edge devices without having to go to the cloud. Delivering high performance with an incredibly small footprint, AutoML models are ideal for low-power and ultra-low-latency applications in mobile, IoT, wearables, automotive, and more.The company works with leading device OEMs and component manufacturers to power new and exciting user experiences on hundreds of millions of devices worldwide. In industries such as mobile, IoT, and automotive, there are billions of devices where computation and memory are highly constrained. Qeexo’s proprietary, low-latency, low-power models are engineered to have an incredibly small footprint – ideal for making high-accuracy predictions in these environments.
Qeexo
Qeexo AutoML is a one-click, fully-automated platform allowing customers to rapidly build machine learning solutions for highly-constrained environments using sensor data. Machine learning engines built with AutoML are lightweight and designed to run locally on Edge devices without having to go to the cloud. Delivering high performance with an incredibly small footprint, AutoML models are ideal for low-power and ultra-low-latency applications in mobile, IoT, wearables, automotive, and more.The company works with leading device OEMs and component manufacturers to power new and exciting user experiences on hundreds of millions of devices worldwide. In industries such as mobile, IoT, and automotive, there are billions of devices where computation and memory are highly constrained. Qeexo’s proprietary, low-latency, low-power models are engineered to have an incredibly small footprint – ideal for making high-accuracy predictions in these environments.
TL;DR
Headquarters / HQ: Mountain View, California
Core product: Qeexo AutoML — automated platform for building lightweight ML models for constrained edge/sensor devices
Use cases: Mobile, IoT, wearables, automotive
Acquisition: Acquired by TDK Corporation (announced Jan 4, 2023)
Company Overview
Problem Domain
Machine learning for sensor data on constrained edge devices
Founded
2012
Industry
Machine Learning / Edge AI
Funding Track Record
2300000.00 USD
Early round reported by TechCrunch
Profiles list a Series B and other rounds; full details partially redacted on some platforms
7400000.00 USD
Total funding amount with last funding date listed in company snapshot
Investor Signal
“Prior venture investors reported include Sierra Ventures and KTB Network”