Transform Insurance
Underwriting with
Real-Time AI
Health Data
Capture clinically accurate health insights in seconds and make smarter, data-driven risk decisions — at scale.
Self-Reported Data
Applicants routinely misreport health conditions, creating inaccurate risk profiles.
Slow & Manual Processes
Traditional underwriting takes days or weeks, slowing time-to-policy.
High Fraud Risk
Without biometric verification, fraud goes undetected at scale.
Generic Risk Pricing
One-size-fits-all premiums lead to mispriced risk and lost profitability.
The Problem with Traditional Underwriting
Legacy underwriting relies on outdated, inaccurate inputs — questionnaires, manual reviews, and physical examinations — creating a slow, fraud-prone, and imprecise process that leaves both insurers and applicants underserved.
Introducing Cura-X AI
A real-time AI-powered platform that delivers clinically accurate health data instantly for smarter, faster, and fraud-resistant underwriting decisions.
From Facial Scan to Risk Decision
in Seconds
30-Second Facial Scan
The applicant undergoes a non-invasive, contactless facial scan via any standard camera — no equipment, no labs.
AI Processes Billions of Data Points
Our deep learning engine analyzes micro-signals in facial video — blood flow, pigmentation, motion patterns.
Extracts Key Health Metrics
BP, glucose, SpO2, HRV, stress index, BMI, respiratory rate, and more — clinically validated outputs.
Generates Risk Score Instantly
A comprehensive risk score and premium recommendation is delivered within seconds, ready for underwriter review.
Everything Underwriters Need
From Guesswork
to Precision
Move from assumptions to real-time, verified health data. Cura-X replaces guesswork with clinical-grade intelligence, enabling underwriters to make decisions they can stand behind.
Built for Underwriting Excellence
Powering Smarter Risk
Across the Industry
Reimagine Risk Assessment
with AI
Start using real-time health intelligence to make smarter, faster, and more profitable underwriting decisions.
