Neurocast develops software platforms designed to passively monitor brain health through analysis of everyday digital behavior. The company’s approach uses AI to interpret patterns in keystroke dynamics and smartphone interactions as proxies for neurological function. Its system operates non-invasively in the background, enabling continuous data collection without dedicated tests or devices. Neurocast positions its technology within applied neuroscience and digital health monitoring contexts.

The technology analyzes fine-grained behavioral signals such as typing speed, rhythm, error patterns, and interaction timing. Machine learning models are used to identify deviations or trends that may reflect changes in cognitive or neurological state. By relying on routine device usage, the platform enables longitudinal monitoring in real-world conditions. This approach emphasizes ecological validity and low user burden compared to clinic-based assessments.

Neurocast targets applications in brain health tracking, neurological research, and remote monitoring of cognitive change. The platform is intended to complement clinical evaluation rather than provide standalone diagnosis. Its positioning reflects growing interest in passive digital biomarkers as scalable tools for understanding neurological function in daily life.