Digital healthcare doesn't fail because of technology.
It fails because people quit.
Behaver bridges AI reasoning with human willpower to drive lasting health outcomes.
Measuring and logging alone doesn't change behavior. You need to interpret data, understand context, and accompany people through every step.
Show numbers without interpretation. After the 2-week sensor expires, most users stop managing entirely.
Only facilitate logging. Users must interpret data themselves, with no guidance on sustained behavior change.
Cannot accumulate personal data over time. Incapable of understanding individual context for continuous coaching.
We remember data, understand people, and accompany their behavior to the very end.
Integrate CGM, activity, sleep, heart rate, and dietary data from multiple biosensors and lifestyle inputs.
BehaverMap analyzes relationships between health data points and explains the "flow" behind patterns.
BehaverPath suggests up to 2 actionable behaviors through empathetic dialogue, guiding voluntary choices.
Track clinical markers like HbA1c, weight, and sleep quality — building evidence for DTx certification.
A proprietary tech stack that naturally bridges AI inference and human behavior.
Defines relationships between health data points and infers context. Example: nighttime glucose spike → sleep quality → next-day fatigue — all connected and explained.
Generates optimized, actionable suggestions based on analyzed context. Empathetic dialogue drives voluntary user choices — max 2 suggestions at a time.
Accumulates individual health data to build an evolving, hyper-personalized health operating system that sharpens guidance over time.
CGM democratization, plummeting AI costs, and a global shift toward preventive care converge now.
Based on UKPDS (UK Prospective Diabetes Study)
Looking for partners to build the future of healthcare AI together.