Patient monitorLive signal
HRV
48 ms
Heart rate
72 bpm
SpO₂
98%
10:41:3010:42:0010:42:30
01
Signal
Continuous biometrics are captured from the wrist.
The pipeline, from signal to chart.
Personal baseline14 days analyzed
Baseline status
Established
Confidence
96%
02
Baseline
NURL learns each patient's normal.
Deviation detectedHigh priority
0.94
risk score
Reading above typical range · flagged in 840 ms
03
AI flag
Meaningful deviations flagged in real time.
Clinical alertDelivered now
Relapse risk
Patient requires clinical attention
Recipient
Assigned care team
Status
Notification delivered
04
Alert
The care team is notified immediately.
Patient chartEntry recorded
Clinical event
Biometric risk flag
Timestamp
10:42:18 AM
Risk score
0.94
Finding
HRV deviation from baseline
Source
NURL
05
Action
Timestamped and documented in the chart.
Built around how clinical teams decide.
Defend length of stay
Objective biometric trends give utilization review the data to justify continued care.
Justify every clinical decision
Quantifiable, timestamped signal replaces subjective self-report. Defensible documentation for clinical and payer review.
Tailor care to the individual
Patient-specific baselines mean the AI flags what is abnormal for that patient, not a population average.
Continuous data, turned into action.
Earlier intervention
Surfaces deviation before it's clinically observable.
No smartphone required
Works in phone-restricted settings. No paired device needed.
Patient-specific baselines
The model learns each patient's normal, then flags their abnormal.
Risk signal
Explainable wellness risk score. Not a black box.
Seen earlier in the signal
The gap between AI detection and clinical observation, illustrated below.
Built with clinicians.
Private by design.
HIPAA compliant.
Security & Privacy
HIPAA-compliant, encrypted, with SSO, audit logs, and role-based access. Clinical control at every step.
HIPAA-compliant and encrypted end to end, with SSO, audit logs, and role-based access, so clinical teams keep control at every step.
Integration
Integrates with EMR, EHR, and analytics systems. Live in days, not months.
Connects to your EMR, EHR, and analytics systems through robust APIs. Designed to go live in days, not months.
Adherence
A band patients keep wearing. Continuous data is what makes the model work.
Comfortable enough that patients keep it on. Continuous data is what makes the model work.
Supported by
world-class institutions
