RiayaCare is the first AI-native health informatics platform purpose-built for the GCC. Our machine learning models predict patient outcomes 30-90 days in advance, prevent adverse events before they occur, and transform reactive healthcare into proactive, personalized care.

AI Alert: 12 High-Risk Patients Identified
Preventive Care Recommended
Traditional health information systems tell you what happened yesterday. RiayaCare's AI tells you what will happen tomorrow—and what you should do about it today.
RiayaCare's AI platform combines six specialized machine learning engines, each trained on millions of GCC healthcare records to deliver predictive intelligence across every aspect of care delivery and operations.
Analyzes 200+ patient data points in real-time to predict risk of readmission, sepsis, falls, and adverse events 30-90 days in advance with 92% accuracy.
85% of predicted adverse events prevented
Automatically extracts insights from unstructured clinical notes in Arabic and English. Identifies hidden patterns and generates structured data from free text.
90% reduction in manual chart review time
Predicts bed occupancy, ED volume, surgical demand, and staffing needs 7-30 days in advance. Optimizes resource allocation and prevents capacity crises.
40% reduction in capacity bottlenecks
Segments populations by risk level, identifies high-cost patients, predicts chronic disease progression, and recommends personalized preventive care strategies.
30% reduction in preventable hospitalizations
Provides real-time, context-aware clinical recommendations based on patient-specific data, latest evidence, and GCC clinical guidelines.
45% reduction in medical errors
Continuously monitors all systems and patient data for unusual patterns that indicate emerging problems—from patient deterioration to system failures.
75% faster problem detection
See how leading healthcare organizations in the GCC are using RiayaCare's AI to save lives, reduce costs, and transform care delivery.
Dubai Health Authority reduced heart failure readmission rate from 24% to 9%, saving AED 15.3M in the first year through AI-powered early intervention.

Cleveland Clinic Abu Dhabi's AI detected sepsis 18 hours earlier than traditional methods with 94% accuracy and only 5% false positive rate.

King Faisal Specialist Hospital performed 1,200 additional surgeries annually with existing capacity through AI-powered scheduling optimization.

Trusted by Leading Healthcare Organizations Across the GCC
Ministry of Health UAE
Saudi Health Council
Dubai Health Authority
SEHA
Cleveland Clinic Abu Dhabi
King Faisal Specialist Hospital