GigEfx Laboratories is seeking to develop a low fidelity minimum viable product (MVP) for Doekon, an AI-enabled patient diagnostic application. This innovative mobile solution aims to revolutionize healthcare delivery by facilitating in-home treatment and connecting patients with medical specialist based on the app's recommendations. The project involves creating ancillary technical documentation to support the development and future iterations of the application. The goal is to provide a foundational prototype that demonstrates the core functionalities of Doekon, such as patient diagnostics and doctor-patient connectivity, while ensuring that the technical documentation is comprehensive and user-friendly. This project will allow learners to apply their knowledge of mobile application development, AI integration, and technical writing, providing a practical experience in the healthcare technology sector.

The project deliverables include a low fidelity MVP of the Doekon application, showcasing its basic diagnostic and connectivity features. Additionally, the team will produce comprehensive technical documentation that outlines the application's architecture, user interface design, and AI integration processes. The documentation should be clear and detailed, serving as a guide for future development and iterations. This will ensure that the application can be easily understood and further developed by other teams or professionals.