Professional Engagement

For Clinicians

Explore how Hayati can support your practice with ethical, transparent AI-assisted wellness screening.

A Tool That Supports, Not Replaces

Hayati is designed to complement clinical expertise, not compete with it. Our pre-diagnostic indicators can help identify patients who may benefit from earlier intervention or additional screening.

We're transparent about our ~75% MVP accuracy target and provide confidence tiers so you can appropriately weight our indicators in your clinical decision-making.

Key Benefits for Clinicians

  • Early indicator identification before symptoms manifest
  • Objective, quantified element measurements
  • Longitudinal tracking for patient monitoring
  • Clear confidence tiers for appropriate weighting
0+
Facial Elements
~0%
MVP Accuracy
0
Confidence Tiers
0
Intensity Scale

Technical Overview

Understanding our methodology helps you integrate Hayati into your practice

Analysis Method

Multi-element facial analysis using computer vision and machine learning. Elements are scored on 1-10 intensity scales and correlated through weighted matrices.

Output Format

Results include individual element scores, aggregated condition indicators, confidence tiers (High/Medium/Low), and plain-language explanations.

Validation Status

Currently in MVP phase with ~75% accuracy target. Ongoing validation studies with clinical partners. Full validation roadmap available upon request.

Limitations

Pre-diagnostic only — not intended for diagnosis or treatment decisions. Accuracy affected by image quality, lighting, and demographic factors.

Integration Options

API

API Access

RESTful API for integration with existing clinical workflows and EHR systems. Secure, authenticated endpoints with comprehensive documentation.

Coming Q2 2026
HL7

FHIR Compatibility

HL7 FHIR-compatible data formats for seamless health record integration. Standardized observation resources for interoperability.

Roadmap item

Research Collaboration

Partner with us to advance ethical healthcare AI

Validation Studies

Partner with us to validate indicators against clinical outcomes in your specialty area.

Data Partnerships

Contribute anonymized data to improve model accuracy and reduce bias across populations.

Advisory Board

Join our clinical advisory board to guide ethical development and appropriate use cases.

Interested in Learning More?

Download our technical brief or get in touch to discuss collaboration opportunities.

Contact Us