The real-time fairness layer for clinical AI
Sit underneath every AI-assisted care decision. Audit in minutes via HL7 FHIR R4. Catch bias at the bedside before it becomes a patient outcome.
Algorithmic bias is a patient safety emergency.
The Alice & Amara Story
Two seven-year-old girls: same pain score, same chief complaint, same emergency department, same shift. The AI-assisted triage tool assigned them different acuity levels. One waited 90 minutes longer for the imaging order that would have revealed appendicitis. The difference was not clinical. It was demographic. And the tool that scored them was never checked. Clinical AI is making triage and care decisions in 89% of hospitals right now, yet the algorithms clinicians trust daily systematically undertriage vulnerable populations.
The Governance Gap
Across hospital networks running predictive algorithms, nobody owns algorithmic fairness. No committee has the authority to pause a biased tool. Nobody can see the disparity patterns hidden in the data, and nobody measures the demographic impact of these tools on patient outcomes. Without real-time visibility into how AI performs across different populations, hospitals cannot govern the systems actively shaping patient care.
The 3-Layer Governance Framework
Governance-First Entry
Assess your baseline without requiring IT integration. Our 15-minute Ethical AI Maturity Assessment (EAMA) reveals institutional governance gaps and maps them to concrete mitigation strategies.
Sidecar Retrospective Wedge
Audit your existing tools on historical data securely. We analyze your de-identified model logs in 30 days to expose demographic performance variations before deploying at the bedside.
Real-Time HAIQ Platform
Embed accountability into the clinical workflow. The Data Diversity & Fairness Auditor (DDFA) integrates directly via HL7 FHIR R4 to assess AI recommendations in minutes.
Purpose-Built for Vendors & Hospital Networks
Healthcare AI Vendors
Build trust and pass hospital procurement ethics reviews.
- ✔ Validate algorithms against our proprietary Composite Fairness Index (CFI).
- ✔ Earn the Synod Certified Fairness (SCF) mark to differentiate your software.
- ✔ Generate automated audit documentation for ACA Section 1557 and EU AI Act compliance.
Hospital Networks & Systems
Protect patient safety and satisfy regulatory oversight.
- ✔ Detect demographic performance variations across installed AI data and models.
- ✔ Automate compliance reporting for hospital AI steering committees and risk managers.
- ✔ Prevent adverse events and capture cost avoidance in readmissions.
Stay in the Know: Latest Publications & Events
AC:Health - Healthcare Innovation Program
Participant in AC:Health - Healthcare Innovation Program. AC:Health supports founders building AI, data, and software-enabled solutions that improve healthcare delivery, patient outcomes, and system efficiency.
Learn More →DaRMoD - Vector Institute for Artificial Intelligence
Participant in Darmod. Vector’s Data Readiness, Model Development, and Model Deployment (DaRMoD) program guides startups and small businesses from an AI idea to prototype in four months.
Learn More →CTO Mohan Attending CAIS & Launching Research Pilot
Our CTO Mohan will be attending CAIS on July 17 to launch our new Connected Minds research pilot, bridging clinical data and ethical AI validation.
Learn More →Real-Time Bias Detection EHR: The Missing Layer in Clinical AI
August 20, 2026 • By Constantine Rhaich'al
Explore how embedding real-time bias detection directly into EHR workflows via HL7 FHIR R4 protects patient safety and ensures equitable clinical AI outcomes.
Build the governance layer for your clinical AI.
Connect with our team to audit your AI tools and ensure equitable, safe care for every patient population.
Schedule a 30-Minute Call →