الصحة· HEALTHCARE · CLINICAL DECISION SUPPORT
Yaqazaيقظة
Predictive risk, ahead of the code blue.
AI-driven risk stratification for sepsis, deterioration, and length of stay — surfacing early warning signs from vitals and labs before they become an emergency, calibrated on Saudi inpatient cohorts.
اليقظة تسبق الأزمة
“Vigilance precedes the crisis.”
What Yaqaza does
Sepsis early-warning scoring
Continuous NEWS2/qSOFA-informed scoring recalculated every 15 minutes from vitals, labs, and nursing notes.
Deterioration alerts
A ward-wide risk heatmap flags patients trending toward rapid response before bedside signs appear.
Length-of-stay forecasting
Bed-day predictions per patient and per ward, refreshed daily, feeding capacity planning directly.
Saudi-cohort calibration
Models are trained and recalibrated on de-identified Saudi inpatient data, not imported thresholds.
Rapid-response routing
Confirmed high-risk alerts route directly to the covering physician and rapid-response team, timestamped.
FHIR-native ingestion
Connects to HIS/EMR vitals, labs, and nursing flowsheets over HL7 FHIR R4 without a custom interface build.
See Yaqaza in action
An early UX walkthrough of the product, designed bilingually from day one.
Ward risk dashboard
Patient watchlist
Alert workflow
Patient case file
How it works
Ingest
Vitals, labs, and flowsheet data stream in continuously over FHIR R4 from the ward EMR.
Score
Risk models recompute sepsis, deterioration, and LOS scores in near real time.
Alert
Patients crossing risk thresholds surface on the ward dashboard and route to the covering clinician.
Respond
The care team acts, and the outcome feeds back into model calibration.
A quick look at the product
A short, silent UX walkthrough of Yaqaza.
Catch deterioration before the code blue
We're selecting design-partner hospitals for the first clinical AI pilot cohort. Book a briefing to review model fit against your case mix.
Request a Pilot