Qeexo AutoML is our fully automated platform that allows customers to rapidly build machine learning solutions for highly constrained environments using sensor data.
Supports Arm® Cortex™-M0-to-M4 class MCUs and other constrained environments
Click-through UI with no coding required
Performs sensor fusion and is sensor agnostic
Visualize collected or uploaded data to understand patterns and potential problems
Automatically generates and weights features from your data to achieve the best performance
View detailed metrics of a wide range of machine learning models to select one that best fits your needs
Provides model performance summaries, visualizations, and recommendations for improvements
Translates models into C code to compile and deploy to target (embedded) hardware
Qeexo AutoML automates many of the most tedious and time-consuming processes within the machine learning model development lifecycle, significantly reducing the time and resources needed to build models while eliminating room for error.
Machine learning models built with Qeexo AutoML are highly optimized and have an incredibly small memory footprint. Models are designed to run locally on embedded devices – ideal for ultra low-power, low-latency applications on MCUs and other highly constrained platforms.
Collecting sensor data and rapidly iterating through machine learning models onsite allow each “endpoint” or “edge” device to run its own unique AI model to augment its functionality and performance in consumer, industrial, and automotive applications.