SpectraCann Ltd.

Published purpose

This project aims to transform a novel form of spectroscopy data analysis by implementing AI and machine learning (ML) technologies to achieve substantial improvements in accuracy and efficiency. A scalable, secure, and efficient target architecture and foundational model will be selected and documented to support the integration of AI capabilities. The final phase of this project will involve the seamless integration of ML models into the device hardware, ensuring synchronized communication between software, hardware, and algorithm components. Rigorous internal verification will optimize performance metrics, while algorithms will be validated and tested through controlled lab experiments and field trials.