Multimodal ophthalmology AI for structured clinical decision support
RetinEye AId synthesizes retinal imaging with clinical patient data to support more structured diabetic retinopathy risk identification. All outputs serve as decision-support tools for independent clinician review.
Patient ID
DR-2026-04821
Report Date
29 Apr 2026
Fundus - Left Eye
Risk Indicator
Moderate - Review
DR Stage
Data Sources
Vascular Biomarkers
CRAE
148.2
CRVE
215.7
AVR
0.69
Decision-support output only. Requires independent clinician review.
Patient ID
DR-2026-04821
Report Date
29 Apr 2026
Fundus - Left Eye
Risk Indicator
Moderate - Review
DR Stage
Data Sources
Vascular Biomarkers
CRAE
148.2
CRVE
215.7
AVR
0.69
Decision-support output only. Requires independent clinician review.
Product Overview
What is RetinEye AId?
A comprehensive clinical AI platform that transforms retinal imaging data and electronic health records into actionable clinical insights, streamlining the ophthalmic assessment workflow.
Multi-Modal Input
Upload fundus images, OCT scans, and clinical records in a single session. The system accepts multiple imaging formats and automatically identifies modality type for streamlined processing.
AI-Assisted Analysis
Multiple specialized analysis pipelines run in parallel, covering disease classification, vascular biomarker extraction, volume analysis, and integrated risk assessment, to support comprehensive clinical review.
Clinical Decision Support
Structured outputs include confidence-scored classifications, automated triage prioritization, follow-up recommendations, and standardized reports, all designed for independent clinician review.
Intuitive Interface
A guided clinical workflow
A streamlined 3-step process collects retinal images, patient information, and clinical parameters before launching parallel AI analysis.
Retinal Image Upload
Right Eye (OD)
JPG, PNG, DICOM, TIFF, VOL
Left Eye (OS)
JPG, PNG, DICOM, TIFF, VOL
Patient Information
Smart modality detectionPatient Name
Modality
Date of Birth
Gender
Clinical & EHR Data
26 clinical parametersDemographics
Diabetes
Lab Values
Vitals
Complications
Medication
All data transmitted securely via HTTPS encryption.
Analysis Output
Comprehensive AI results
Every analysis produces structured results across multiple dimensions: disease classification, vascular biomarkers, segmentation overlays, and integrated risk scoring.
Moderate DR detected in right eye. Clinician review recommended.
Right Eye (OD)
Quality 92%Classification
Stage 2 - Moderate NPDR
57.8% confidence
Detected Findings
Left Eye (OS)
Quality 88%Classification
Stage 0 - No DR
84.1% confidence
Detected Findings
Vascular Biomarkers
Optic Disc
Vessel Caliber
Vessel Structure
Integrated Risk Assessment
Ensemble assessment combining imaging analysis with clinical parameters from 26 EHR data points.
Reliability: 82%
Decision-support output only. All findings require independent clinician review and clinical judgment. Not a substitute for professional medical diagnosis.
Clinical Value
Intelligence that supports clinical review
All outputs are decision-support tools requiring independent clinician judgment.
Diabetic Retinopathy Screening
5 DR StagesFive-stage ICDR classification with confidence-scored predictions and quality-aware processing for structured DR assessment.
Retinal Disease Detection
7 Disease ClassesMulti-class retinal disease classification from OCT scans, covering major conditions with multi-scan consensus analysis.
Vascular Biomarker Analysis
50+ BiomarkersComprehensive vascular health measurements including vessel caliber, density, structural complexity, and optic disc analysis.
Integrated Risk Assessment
Multi-ValidatedEnsemble risk scoring combining imaging analysis with clinical parameters from electronic health records for comprehensive evaluation.
Multimodal Data Fusion
Combined AnalysisGo beyond single-source image classification by synthesizing retinal imaging with electronic health records and clinical context.
Automated Triage & Reporting
Instant TriageAI-supported triage prioritization with follow-up recommendations and standardized PDF reports for consistent clinical documentation.
Workflow Impact
How RetinEye AId transforms ophthalmic assessment
From fragmented manual workflows to structured, AI-supported clinical intelligence.
Traditional Workflow
Manual Image Review
Clinicians review fundus and OCT images one by one, with subjective assessment dependent on individual experience.
Paper-Based Records
Patient history scattered across separate files and systems with no unified digital timeline.
Subjective Grading
DR staging relies entirely on clinician experience, leading to inter-observer variability.
No Integrated Risk Scoring
EHR data reviewed separately from imaging, with no quantitative cross-modal risk assessment.
Delayed Triage
Priority assessment happens after the full examination, with potential for missed urgencies.
Inconsistent Reporting
Manual report writing leads to inconsistent formats and varying levels of detail across clinicians.
With RetinEye AId
AI-Assisted Analysis
Upload fundus and OCT images for automated quality checking and multi-pipeline analysis in parallel.
Unified Digital Timeline
Patient visits, images, and clinical notes accessible in one searchable, structured timeline.
Objective Classification
Confidence-scored disease classification across multiple stages and categories, supporting consistent review.
Integrated Risk Assessment
EHR and imaging data synthesized through ensemble risk models, producing quantitative risk scores.
Instant Triage Prioritization
Real-time priority levels with follow-up recommendations generated immediately upon analysis completion.
Standardized Clinical Reports
Automatically generated PDF reports with structured findings, biomarkers, and follow-up recommendations.
How It Works
From patient data to clinical intelligence
A streamlined workflow designed to integrate into existing clinical environments.
Select Patient
Clinical staff select the patient and relevant records are automatically retrieved from your existing EHR system.
Upload Retinal Images
Fundus photographs and OCT scans are uploaded directly from imaging devices or your PACS archive.
AI Analyzes in Under 2 Minutes
Multiple analysis pipelines run in parallel, combining imaging data with clinical context to produce a comprehensive assessment.
Clinician Reviews Structured Report
A triage-prioritized report with annotated findings, risk indicators, and follow-up recommendations is presented for independent clinical review.
Under the Hood
How the analysis works
Multiple specialized analysis pipelines run in parallel, with intelligent orchestration that adapts to available data and gracefully handles partial inputs.
Intelligent Orchestration · Adapts to Available Data · Multiple Pipelines in Parallel
DR Classification
Five-stage diabetic retinopathy assessment from fundus images with confidence scoring
Retinal Disease Detection
Multi-class disease identification from OCT scans covering 7 major conditions
Vascular & Structural Analysis
Comprehensive vascular measurements and structural assessments from retinal imaging
Integrated Risk Assessment
Combined imaging and clinical data synthesis for holistic patient risk evaluation
Triage Priority
4-level urgency classification
Clinical Results
Classification with confidence scores
Biomarkers
50+ quantitative vascular metrics
PDF Report
Standardized clinical documentation
Capabilities
Platform at a glance
Key numbers behind RetinEye AId's comprehensive clinical analysis capabilities.
6
AI Pipelines
50+
Vascular Biomarkers
7
Disease Classes
<2 min
Minutes Per Patient
Supported Input Modalities
Upload
Quality Check
AI Analysis
Triage
Report
Deployment
Starts delivering value from day one
Workflow tools deploy immediately. AI-assisted clinical intelligence follows regulatory clearance.
Clinical Workflow Platform
Replaces fragmented image management and paper-based workflows with a unified digital system built for ophthalmic clinics.
No MDR requirement. Immediate deployment.
AI Clinical Intelligence
Full AI-assisted analysis capabilities currently in regulatory preparation. Available through research collaboration today.
CE marking process underway. Research use available now.
Research Areas
Adjacent research and collaboration areas
These are active research directions, not commercial products. We are open to collaboration.
Eye Disease Progression Tracking
Exploring longitudinal retinal analysis to help clinicians monitor disease trajectory over time. Research-stage only.
Anti-VEGF Treatment Response Prediction
Investigating predictive approaches that may assist clinicians in evaluating treatment response patterns. No clinical claims.
Interested in RetinEye AId for your institution?
Let's discuss how multimodal ophthalmology AI can support your clinical review workflow.