A reasoning substrate engineered against the healthcare record.
Veronara's AI architecture is not a set of models attached to a clinical system. It is a reasoning substrate engineered into the architecture of HealthOS — observing the same data model, governed by the same identity layer, auditable through the same trail as every other action in the system.
Last reviewed:
Unified data model
Identity-governed access
Versioned & audited
CAB-reviewed
Advisory output
Closed-loop outcomes
Region-resident
Observable traces
Unified data model.
Models observe structured clinical, operational, financial, and patient data produced by HealthOS itself. No retrofit ETL. No brittle integration against external EHR extracts.
Identity-governed access.
Every model's read and write scope is governed by the same role-based identity layer that governs clinician access. A model cannot see what a clinician cannot.
Versioning.
Every production model carries a semver, a deployment date, a training data snapshot reference, and an evaluation record. Published to the model change log.
Clinical Advisory Board review.
Models with clinical effect are reviewed by the Clinical Advisory Board before production release. Review documentation is public.
Advisory output.
All model output in care-affecting contexts is advisory. The system reasons; the clinician decides. Every override is recorded with reason.
Closed-loop outcome capture.
Decisions and observed outcomes are captured into the record. Models update against outcome data under supervised retraining — not silent drift.
Residency.
Training and inference run in the deployment region. No cross-border transfer of clinical data for model operations.
Observability.
Every inference carries a reasoning trace. Clinicians and institutional operators can inspect why the system surfaced what it did.
Frequently asked
Common questions about this layer.
What is Veronara's AI architecture?
Veronara's AI architecture is the Clinical Reasoning Layer — a reasoning substrate that observes clinical signals across the longitudinal record and returns advisory output into the clinician's workflow. It is a property of HealthOS, not a chatbot bolted to a portal.
What models does Veronara use?
Veronara uses a combination of foundation models, institutionally fine-tuned models, and rule-based reasoning components, depending on the workflow. Each model is named, versioned, governed under the Advisory Principle, and reviewable by the Clinical Advisory Board.
Where does the data go for AI processing?
Inside the institution's data residency boundary. Region-resident architecture keeps clinical data, model inference, and audit logs within the institution's region. Sovereign deployments support dedicated and air-gapped configurations.
Is the AI used for diagnostic decisions?
AI in HealthOS issues advisories — not decisions. The clinician is the decision-maker; the model is the advisor. The Advisory Principle is non-negotiable in every clinical workflow.
How is model performance evaluated?
Each predictive system has a published evaluation document specifying performance thresholds, demographic stability, and failure modes. Performance is monitored continuously against the published criteria; drift triggers institutional review. Methodology is at /research/methodology/predictive-evaluation.
Intelligence is a property of the substrate, not a feature bolted to it. The architecture exists so that the Advisory Principle can hold.
Signed by the Veronara Intelligence Office · Last reviewed · Propose a correction to corrections@veronara.com.
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