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.

Solution Briefs

  • thumbnail: Qeexo AutoML: Automating Machine Learning for Embedded Devices
    Qeexo AutoML: Automating Machine Learning for Embedded Devices

    Leveraging sensor data, Qeexo AutoML is an automated, end-to-end machine learning platform that creates machine learning models for embedded devices.

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  • thumbnail: Qeexo Model Converter: Compress Tree-Based Models Without Sacrificing Performance
    Qeexo Model Converter: Compress Tree-Based Models Without Sacrificing Performance

    Qeexo Model Converter is an API service that optimizes existing tree-based machine learning models to run on Arm Cortex-M0+ to Cortex-M4 platforms.

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Insights

  • Automate tinyML Development & Deployment with Qeexo AutoML Arm Tech Talk
    Automate tinyML Development & Deployment with Qeexo AutoML

    What's the smallest machine learning model you've built? Qeexo's is so small, it can even run on an Arm Cortex-M0+!

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  • Automatically Build tinyML Solutions on Embedded Devices Arm Tech Talk
    Automatically Build tinyML Solutions on Embedded Devices

    See how easy it is to automate "tinyML" machine learning development for sensor modules with Arm Cortex-M0+ to Cortex-M4 microprocessors!

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  • Qeexo AutoML on Arm Cortex-M0+: Bringing TinyML to the tiniest Arm MCUs Arm Tech Talk
    Qeexo AutoML on Arm Cortex-M0+: Bringing TinyML to the tiniest Arm MCUs

    Qeexo will provide a demonstration using the Qeexo AutoML platform to build an activity recognition solution for the M0+-powered Arduino Nano 33 IOT. Qeexo AutoML is a no-code end-to-end framework for easily developing tinyML solutions.

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  • Build Custom Keyword Detection Models for Arm Virtual Hardware with Qeexo AutoML Arm Tech Talk
    Build Custom Keyword Detection Models for Arm Virtual Hardware with Qeexo AutoML

    The Qeexo AutoML platform has recently been enabled to integrate seamlessly with the Arm Virtual Hardware platform for the Arm Cortex-M55 processor and enhanced to better support keyword detection problems.

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  • Fast Development of Noise Detection ML Models Arm Tech Talk
    Fast Development of Noise Detection ML Models

    Qeexo AutoML has recently enhanced its Arm Virtual Hardware integration to take advantage of the Arm u55 neural network accelerator. In this tech talk we will demonstrate training the model, and integrating the library to the Arm Keil IDE.

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