Beds under coverage
8,400+
Clinical AI, hospital operations, and population-health platforms aligned to the Health Sector Transformation Program. We build alongside MoH, CCHI, NUPCO, and the cluster operators — designed so the clinician spends less time documenting and more time with patients.
Six pressures we hear from CMOs, cluster CEOs, and CIOs on every first call.
The Health Sector Transformation Program is reshaping public healthcare into independent clusters. The IT, data, and revenue-cycle stack inherited from the Ministry was never designed for this operating model.
Saudi clinicians spend 38–52% of their day on documentation. Ambient scribing, structured-note generation, and order-entry copilots are the highest-ROI AI investment a hospital can make.
Tertiary EDs run at 110%+ of design capacity. Predictive triage, bed-management, and discharge-planning AI move the throughput needle in a way new buildings cannot.
Radiology and pathology volumes outpace specialist supply. Computer-vision triage for chest X-ray, CT, mammography, and dermatology is now standard of care, not a research project.
Patient-health data is the most sensitive class under PDPL. Models trained on Saudi cohorts, governed under NDMO classification, and audited per MoH protocols — not models trained on Boston EHRs and rebadged.
Diabetes, cardiovascular, and obesity prevalence in Saudi cohorts demand population-level analytics, not just episodic care. Risk-stratification has to feed primary care, not radiology dashboards.
Six disciplines, sector-tuned around the clinical workflow and the cluster operating model.
Risk-strat, sepsis prediction, deterioration alerts, and length-of-stay forecasting — trained on Saudi cohorts, audited per MoH.
Arabic-and-English ambient documentation that drafts the structured note, the order set, and the discharge summary while the clinician talks.
Triage-grade CV for chest X-ray, CT head, mammography, and dermatology. Worklist re-prioritization with a written radiologist sign-off loop.
In-Kingdom landing zones for cluster operators. EMR-adjacent data lakes, FHIR ingestion, and PDPL-aligned access controls.
Medical-device security, segmentation, and a SOC posture tuned for ransomware-targeted hospital networks. CCHI- and MoH-aligned controls.
Risk-stratification platforms that feed primary care, with diabetes / CV / obesity cohorts modeled against Saudi-specific outcomes.
Two engagements that anchor our healthcare practice. Names redacted under MNDA — the cluster CEOs know the work.
Ambient documentation that listens to the clinical encounter in mixed Arabic-English code-switching, drafts a structured note in seconds, and posts it to the EMR with order-entry suggestions. Built on a Saudi clinical-language corpus we trained ourselves; clinician retains the pen at every step.
An ED operations platform with live arrival forecasting, acuity-aware triage decision support, and discharge-readiness scoring. Bed-management is no longer a whiteboard exercise — it is a 15-minute-horizon model the charge nurse trusts.
Authorities, EMR vendors, and the partners we integrate with at the cluster level.
Yes — and we say so explicitly. Models trained on Boston or London EHRs perform poorly on Saudi clinical reality. Our clinical AI is fine-tuned on Saudi-cohort data with explicit cohort sign-off from the partner cluster.
In-Kingdom, at every step. Sovereign cloud or on-prem depending on the cluster's posture. Cross-border PHI movement is not part of our delivery model.
FHIR-first. Read-side via FHIR R4, write-side through whatever interface engine the cluster has standardized on. We do not displace the EMR — we operate alongside it.
Anything that influences a clinical decision is documented to MoH, CCHI, and CBAHI standards. Where appropriate, we follow IEC 62304 software-lifecycle and submit through the SFDA medical-device pathway.
97% acceptance on the ambient scribe in our flagship cluster — measured weekly. Adoption is the only metric that matters. We design for the clinician first, the dashboard second.
Yes. Our flagship deployments cover 8 hospitals, 8,400+ beds, and 3,200+ active clinicians under a single platform. The architecture is cluster-native, not single-site.
Sixty-minute working session with our Healthcare lead and a clinical informaticist. Bring the workflow that hurts — documentation, ED throughput, imaging backlog — and we'll come back with a one-page roadmap.