Sleep.CoDoc is an AI-powered sleep analysis platform that helps users understand the underlying causes of poor sleep rather than just tracking hours. By combining phone and smartwatch signals—including sound, movement, heart rate, and oxygen—the platform identifies patterns pointing to conditions like sleep apnea, insomnia, and restless legs. The service provides personalized action plans and pathways to clinical care, with validation against gold-standard PSG studies in progress.
- Artificial Intelligence
- Digital Health
- Healthcare Technology
- Software Only
- Wellness & Fitness Technology
Funding
Funding not disclosed
Founders
Product
Problem
Most sleep apps only count hours slept, providing a score without explaining what is behind consistently poor sleep. Persistently poor sleep is linked to serious long-term health risks including heart disease, dementia, type 2 diabetes, depression, frailty, and reduced healthspan, yet few consumer products help users understand the root cause.
Solution
Sleep.CoDoc is an AI-powered sleep analysis platform that helps users understand why they sleep poorly and what to do about it. The platform uses data already captured by a user's phone and smartwatch—including sound, movement, heart rate, and oxygen levels—and applies a proprietary AI model designed to read phone and wearable signals together. It surfaces patterns pointing to five common sleep issues: insomnia, sleep apnea, parasomnias, restless legs, and limb movement. Users receive a personalized sleep profile, actionable steps, and guidance toward specialist care when warranted. The platform tracks changes over time, including sleep age, sleep score, heart-health flags, and healthspan trends, enabling early intervention and prevention-minded care.
Target Audience
Primary users are individuals at home who want to understand the cause of their poor sleep and act early, as well as clinics and specialists who benefit from better-prepared patients and clearer information to support assessments.
Features
- Proprietary AI model that fuses phone and wearable sensor data (sound, movement, heart rate, oxygen) to identify likely causes of poor sleep
- Detection signals for five common sleep issues: insomnia, sleep apnea, parasomnias, restless legs, and limb movement
- Longitudinal sleep profile tracking with metrics including sleep age, sleep score, heart-health flags, and healthspan trends
- Personalized action plans and clear pathways to specialist consultation when warranted
- Privacy-by-design architecture: GDPR-aligned, encrypted, and no data selling
- Active validation benchmarking against gold-standard polysomnography (PSG) sleep studies
- Developed in collaboration with practicing sleep clinicians