Preemptive puts a monitoring layer underneath primary care. A member holds a finger over the phone camera, the app reads blood-flow patterns from the image, and thousands of those readings build a personal baseline. Algorithms watch for meaningful deviations from it, a dedicated nurse clinician reviews what gets flagged, and early interventions such as a medication adjustment are coordinated from there. Wearables feed in alongside.
Putting a nurse between the signal and the member is the design decision that makes this usable. Continuous physiological monitoring generates constant small deviations, almost all of them noise, and a system that surfaces them directly produces either alert fatigue or unnecessary anxiety within a fortnight. A clinician deciding which deviations are worth a phone call is what converts a data stream into care.
PreemptiveAI Inc. of Seattle sells to individual members, families monitoring aging parents, clinicians, payors and pharmaceutical companies, and publishes no pricing at all. A personal baseline needs weeks of consistent daily readings before deviations mean anything, camera-based blood-flow measurement is sensitive to lighting, skin tone and how the finger is held, and continuous health monitoring raises data questions that a privacy policy answers only on paper.
