This I-Corps project is based on the development of a digital software platform for healthcare research. Researchers currently face obstacles that limit innovation including high costs, fragmented tools, and technological complexity when conducting real-world studies. This technology addresses the inefficiencies and technical barriers that hinder traditional clinical studies by providing an integrated, intuitive system that automates data collection, participant engagement, and real-time analysis. The solution is designed to enable research teams to deploy advanced digital health studies without writing a set of instructions (computer code) or building custom infrastructure. In addition, the solution includes wearable sensor technology, behavior-triggered surveys, and artificial intelligence (AI) analytics to support dynamic, adaptive clinical research. The technology may enhance study accuracy, efficiency, and participant adherence, which may lead to faster and more effective healthcare solutions. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a digital research software platform that integrates multimodal data collection, intelligent intervention delivery, and real-time analytics. The technology is a no-code, closed-loop system that utilizes context-aware mobile health technologies, wearable device streams, and advanced machine learning models to facilitate predi