Anti-Sepsis AI
AI-powered sepsis response platform for hospitals
Identify sepsis risk signals earlier, support timely clinical review, and surface preventable delays so every critical action is accountable.
Designed by Dr. Ahmed Almalaq
Anti-Sepsis AI connects early recognition, sepsis bundle tracking, antimicrobial stewardship, source control, escalation, and quality analytics into one closed-loop response system.
For Clinical Teams
Prioritize high-risk patients, identify missing actions, and coordinate urgent response.
For Quality & IPC
Track bundle compliance, HAI-related sepsis, MDRO signals, delays, and case reviews.
For Business & Leadership
Measure outcomes, bottlenecks, ROI, implementation readiness, and hospital performance.
How it works
- 01Detect
- 02Prioritize
- 03Respond
- 04Escalate
- 05Learn
Competitive Edge
What sets Anti-Sepsis AI apart from legacy systems?
Three pillars that legacy sepsis platforms and other brands don't deliver — built for clinical safety, accountability, and national-scale intelligence.
Guardian Mode
AI-on-AI supervision layer
An independent second model audits every clinical recommendation in real time and blocks unsafe outputs before they reach the clinician.
Outcome Ledger
Transparent, auditable ledger
Every recommendation, decision, and approval is timestamped with a full causal trail — ready for accountability and accreditation.
Federated Cross-Hospital Learning
National learning without patient data transfer
Models improve from every hospital in the Kingdom while patient data stays behind hospital walls — full privacy, collective intelligence.
- Independent supervision layer over AI outputs
- Full transparency & auditable ledger per decision
- Federated cross-hospital learning without data transfer
- Explainability for every recommendation~
- FHIR/HL7 integration with hour-1 bundle workflow~
- National governance layer & live hotspots map
- In-EMR clinical decision support
- Early sepsis alerts
Benchmark reference: legacy sepsis platforms and other brands — based on public documentation and published literature.
Clinical decision support only. Final decisions remain with qualified healthcare professionals.