The EXEL AI machine learning development kit provides and all-in-one platform for exploring and building with AI/ML technology.


The kit is optimized for education in classroom and home settings, providing a guided system for learning AI/ML and putting the technology into practice.


Hands-on AI/ML Kit

Easy-to-use and accessible platform, designed for education and training, to provide hands-on experience in AI/ML and deep learning using Coral USB module and TensorFlow Lite.

One-Stop Platform for ML

Framework for users to easily create, test, and deploy machine learning, computer vision models, in one easy-to-use application.

Future AI Expansions

Modular software design optimized to add future sensors and integrate various mobility solutions, including robotics and other AI/ML applications that evolve with real-world needs.


Building on the TensorFlow Lite framework and Edge TPU processing capabilities, the EXEL AI kit utilizes the Coral USB Accelerator from Google for increasing ML inferencing speed and accuracy.
Coral from Google is a platform for bringing AI/ML to the edge with on-device ML inferencing acceleration. It uses Edge TPU technology designed by Google that is optimized for TensorFlow Lite machine learning models. The Coral USB Accelerator module that is an integral part of the EXEL AI Kit has the Edge TPU inside with the USB 3 interface speed with the Raspberry Pi host, and it provides 4 TOPS ML computational acceleration performance. The EXEL AI Kit design selected TensorFlow Lite as the framework for it's low resource requirements, especially suitable for low-power, low-memory, and mobile platform applications, yet very powerful for high-speed AI vision applications such as object detection and object classification.  To make the EXEL AI Kit suitable for our customers, especially those in the educational field, we leverage the resources from the Coral platform, and provide accessibility of online tutorials, including python examples and pre-compiled models, which have been easy to integrate with the Raspberry Pi host.  We are proud to use the TensorFlow ecosystem in promoting AI/ML and increasing AI/ML accessibility, and we want to help continue optimizing the educational experience for our users, by increasing adoption and promoting more innovations.
More information on Coral can be found at coral.ai


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