Canadian Copacking Group Inc is seeking to enhance its food safety monitoring processes by developing a mobile-friendly user interface that facilitates both structured and free-text data input. The project aims to integrate a Large Language Model (LLM) engine to interpret and organize unstructured observations, thereby enabling real-time risk scoring, compliance monitoring, and predictive alerts. This initiative will ensure alignment with food safety guidelines and improve operational efficiency. The project will be piloted in 10 facilities within three months of the prototype's completion, with the goal of launching the final version to at least 1,000 facilities within 12 months. This project provides an opportunity for learners to apply their knowledge of mobile development, data integration, and compliance standards in a real-world setting.

The project deliverables include a functional mobile-friendly user interface that supports structured and free-text data input. Additionally, the integration of an LLM engine for data interpretation and organization is required. The final deliverable will be a prototype capable of real-time risk scoring, compliance monitoring, and predictive alerts, ready for pilot testing in 10 facilities. The project will culminate in a comprehensive report detailing the development process, testing outcomes, and recommendations for scaling to 1,000 facilities.