Separating Signal from Noise
Healthcare generates more data than ever. Yet 97% goes unused. The signal is buried in noise.
Other fields solved this decades ago. Quantitative finance finds structure in market noise. Physics detects rare events among billions of collisions. But healthcare still lacks a general-purpose way to measure biological change.
Built upon a decade of research at the University of Oxford, our platform brings together expertise from quantitative finance, particle physics, applied mathematics, and neuroscience to address a single problem: measuring biological change precisely, interpretably, and early.
Designed to work across diseases, data types, and scales, our platform provides the quantitative layer behind your breakthroughs.
Measure signal amidst noise.
Single or multimodal inputs are transformed into structured descriptors of variability, physiological patterns and meaningful change.
Translate measurement into insight.
Interpretable outputs power analytics in drug development, public health and clinical research—accessible through secure APIs and a compliant analytics dashboard.
Draw on the data you already generate.
We harness datasets from trials, studies, consumer devices and health systems—past or present; single or multimodal; disease-agnostic; scalable.