<![CDATA[Diabetes Mellitus (DM) remains a significant public health challenge in Indonesia, with rising prevalence and limited access to personalized nutritional care. The Nutrition Care Centre (NCC) at Jember State Polytechnic offers diet consultation and education services but faces constraints in human resources and client reach, with only 23% of visitation targets met since 2021. To address this gap, this study aims to develop VANESA, a virtual assistant powered by artificial intelligence (AI) and QR code technology to provide accessible, efficient, and contextual education and consultation services for DM patients. The system integrates rule-based and AI-based chatbot functionalities to deliver natural language responses regarding DM management, including dietary guidance, physical activity, and basic treatment advice. It also facilitates telehealth consultations, automated registration via QR code, and seamless integration with the existing Electronic Medical Record (EMR) system. Developed using the Waterfall model of SDLC, VANESA is designed to enhance service accessibility, reduce operational costs, and support continuous monitoring of patient nutritional status. Expected outcomes include a web-based admin system, an AI-driven Q&A chatbot, telehealth features, QR-based registration, and an analytics dashboard. This innovation not only supports the Teaching Factory NCC but also serves as a scalable model for digital health interventions in resource-limited settings. Thus, VANESA is a digital health solution that has a direct and applicable impact, is able to increase service efficiency, expand the reach of nutritional interventions, and can be replicated and scaled sustainably in various health facilities, especially in areas with limited resources.]]>
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