![Qeexo Qeexo logo](/-/media/global/Why%20Arm/partner/Partner%20Ecosystem/catalog/qeexo/qeexo-logo.png?rev=eaa7c96437754ab9b08c85966dc5652a&revision=eaa7c964-3775-4ab9-b08c-85966dc5652a&h=204&w=571&la=en&hash=3BF918937BEDE9899B104669F287A05A)
Qeexo
Qeexo AutoML leverages sensor data to automatically build optimized machine learning models for embedded devices using 17+ algorithms.
Qeexo Solution Briefs and Insights
About Qeexo
Qeexo is the first company to automate end-to-end machine learning for edge devices (e.g. Cortex-M0+ to Cortex-M4 class MCUs). Its Qeexo AutoML platform provides an intuitive UI that allows users to collect, clean, and visualize sensor data and automatically build machine learning models using different algorithms. Delivering high performance, solutions built with Qeexo AutoML are optimized to have ultra-low latency and power consumption, and an incredibly small memory footprint – so tiny it can run on a Cortex-M0+! Qeexo AutoML enables all of this in a no-code environment, enabling data collection and training of 17 (and counting) different machine learning algorithms, including both neural networks and non-neural-networks, to the same dataset, while generating metrics for each (accuracy, memory size, latency), so that users can pick the model that best fits their unique requirements.
Contacts at Qeexo
![Elias Fallon Qeexo contact: Elias Fallon](/-/media/global/Why%20Arm/partner/Partner%20Ecosystem/catalog/qeexo/representatives/EliasFallon_Qeexo_Profile.png?rev=43a2b3ccb936461192f020b6caab2d68&revision=43a2b3cc-b936-4611-92f0-20b6caab2d68&h=140&w=142&la=en&hash=AFE84DD760B28C6692AB8A0755303607)
Elias Fallon
VP for Machine Learning
![Michael Gamble Qeexo contact: Michael Gamble](/-/media/global/Why%20Arm/partner/Partner%20Ecosystem/catalog/qeexo/representatives/michael_headshot.jpeg?rev=a3d7c91f47c147809c2ce731e2c37589&revision=a3d7c91f-47c1-4780-9c2c-e731e2c37589&h=277&w=320&la=en&hash=24D8C002D424EFD23958E990E2523D69)
Michael Gamble
Director of Product Management