Objective: To present the development of a web application prototype based on Artificial Intelligence (AI) for the early detection of respiratory diseases, in order to explore its applicability in timely diagnostic support. Materials and Methods: It uses the agile Scrumban methodology, which combines the Scrum structure with the flexibility of Kanban, allowing adaptive workflow management. The prototype design included the integration of machine learning models, such as convolutional neural networks (CNNs), applied to simulated and open-access clinical data. Expected results: The prototype incorporates a web interface aimed at healthcare professionals, with functionalities for patient management and preliminary data analysis using AI. Its application is expected to improve the accuracy of initial diagnosis and facilitate integration in resource-limited settings. Conclusions: This advance...