Single-cell technologies have enabled the generation of vast amounts of data from human tissues with unprecedented resolution. While numerous cell atlas efforts have made strides toward describing and cataloging cellular complexity, the full potential of single-cell data in biomarker discovery and clinical applications has yet to be unlocked, in part due to the challenges in analyzing such high-dimensional, complex data. Scailyte has developed a novel approach combining single-cell analysis, integration of clinical data, and a tailor-made supervised machine learning platform, which allows for targeted and sensitive biomarker discovery. Here we highlight several discovery projects across different disease areas, including oncology and cell therapy.