Vignette-based methodologies are frequently used to examine judgments and decision-making processes, including clinical decisions made by health professionals. One of the most difficult tasks is to ease the creation of such vignettes (i.e., the definition of features, design variations, strengths, etc.) as well as to support the gathering of clinical judgments from professionals (e.g., assigning diagnoses, and selecting treatments). In this demonstration paper, we present FaST, a tool supporting the whole pipeline management of vignette-based factorial surveys. We consider this tool relevant for the community since it can work as an enabler for generating statistical data that can feed AI-based algorithms to generate insights for clinicians.