The PerMel-AI project aims to revolutionize the treatment of melanoma, the deadliest form of skin cancer, by leveraging the Human Melanoma Proteome Atlas (HMPA) combined with AI and machine learning technologies. Our consortium, consisting of leading experts from the academy and industry, is dedicated to validating novel drug targets and companion biomarkers to enable personalized melanoma treatments. The HMPA provides an exhaustive pathological, clinical, and molecular characterization of melanoma. This robust dataset, including +1000 tumors, allows us to identify biomarkers and therapeutic targets with unprecedented precision. The project focuses on integrating AI-driven analyses to enhance patient stratification and tailor therapies to the unique genetic and molecular profiles of each patient’s tumor. Our research addresses the critical challenges of melanoma’s complexity and heterogeneity. Despite advances in immunotherapy and targeted treatments, patient responses remain unpredictable, underscoring the need for reliable predictive biomarkers and a deeper understanding of resistance mechanisms. The PerMel-AI project aims to fill this gap by employing AI and digital pathology tools to dissect tumor heterogeneity at a single-cell level, improving diagnostic precision and treatment planning. We address significant unmet medical and societal needs, like the increasing incidence of melanoma among young individuals and disparities in disease presentation. By developing and validating predictive biomarkers and therapeutic targets, we will enhance diagnostic accuracy, refine treatment protocols, and reduce the trial-and-error approach in oncology. The PerMel-AI project will impact on melanoma treatment, promising to improve patient outcomes, extend survival, and set a new standard in oncology. Our approach, combining advanced technologies and multidisciplinary expertise, will transform melanoma management and deliver life-saving innovations to patients worldwide.