Precoh RegOS
The regulatory execution operating system for clinical AI. Every model evaluated through structured intake, multi-domain validation, risk scoring, and a defensible decision record — end to end.
What Is RegOS
Regulatory infrastructure, not just a checklist
Most healthcare organizations assess clinical AI through ad hoc reviews and static documentation. Precoh RegOS replaces that with a structured, reproducible operating system — one that captures every input, runs every check, and generates tamper-evident records that hold up to regulatory scrutiny.
RegOS is built for SaMD developers seeking FDA clearance, health systems deploying third-party AI models, and compliance teams managing post-market monitoring obligations. It operationalizes the frameworks — FDA SaMD, EU MDR, IMDRF — so your team can focus on outcomes, not paperwork.
See it in actionThe Evaluation Pipeline
Five stages. One defensible record.
RegOS walks every clinical AI model through a structured five-step workflow. Each stage produces structured, timestamped artifacts that feed the next — no gaps, no ambiguity.
AI Intake
Structured submission form captures model identity, risk classification, clinical use scope, developer information, and mandatory documentation (IRB, de-identification, bias assessment). All fields are validated on submission.
Structured Validation
Five domain engines run in sequence — Data Governance, Clinical Validation, Fairness & Bias, Technical Standards, and Post-Market Governance. Autonomous AI models trigger a mandatory sixth domain: MD Comparison Evaluation.
Risk Scoring
Domain scores are weighted by clinical risk profile — Clinical Validation (30%), Data Governance (25%), Fairness (20%), Technical (15%), Governance (10%) — and aggregated into a composite score that maps to approval thresholds.
Regulatory Decision
The decision engine applies the SaMD framework (DECI-SAMED-2026) to issue one of three outcomes: Approved, Conditional Approval with remediation requirements, or Not Approved with gap analysis. Every decision is reproducible and defensible.
Evidence Package & Audit Trail
Every evaluation step — inputs, checks, scores, decisions — is assembled into a sealed, tamper-evident evidence package. The audit trail links each decision back to its inputs with full dependency tracing and a reproducibility guarantee.
Platform Capabilities
Built for every stage of clinical AI governance
Scenario Prefills
Pre-loaded clinical scenarios — radiology AI, sepsis predictors, pathology classifiers, diabetes risk models, and autonomous AI — let teams evaluate representative model archetypes instantly.
Real-Time Validation
Domain validation engines run sequentially with live progress tracking. Each check resolves to a structured pass/warn/fail result tied directly to the model's documentation inputs and risk class.
Autonomous AI Mode
Models operating autonomously — making decisions without real-time human review — automatically trigger a mandatory sixth validation domain: MD Comparison Evaluation, testing DDx overlap and primary diagnosis match rates against board-certified physicians.
Weighted Risk Scoring
Composite scores are calculated using a risk-weighted methodology (WACI algorithm) tied to the model's risk class. Scores map to transparent approval thresholds — no black-box verdicts.
Decision Traceability
The Decision Trace panel exposes every input, dependency, and rulebook version behind each verdict. Evaluators, regulators, and auditors can follow the reasoning chain from raw intake to final decision without ambiguity.
Evidence Packages
Every completed evaluation generates a sealed evidence package — intake record, validation report, risk scores, and decision record — stored as structured JSON artifacts with tamper-evident hashing for regulatory submission.
Who It's For
Designed for the people who bear accountability
SaMD Developers
Run pre-submission evaluations against FDA SaMD and EU MDR frameworks before regulatory filing. Identify gaps, generate structured documentation, and arrive at submission with a complete evidence record.
Health Systems
Evaluate third-party AI models before procurement and deployment. Maintain an auditable record of every model in your clinical environment, with post-market monitoring conditions tracked and enforced.
Compliance Teams
Replace ad hoc AI review processes with a reproducible, documented methodology. RegOS provides the paper trail that boards, legal counsel, and regulators require — without the manual overhead.
Interactive Demo
Run a live evaluation now
The RegOS interactive demo walks you through a complete five-step evaluation of a clinical AI model — from structured intake to sealed decision record. Choose from five pre-loaded clinical scenarios or enter your own model details. No login required.
- Five clinical AI scenarios pre-loaded
- Real-time validation across 5–6 domains
- Composite risk score with gauge visualization
- Sealed evidence package & audit trail
- Decision trace with full dependency tracing
Ready to operationalize clinical AI governance?
Precoh RegOS is available for SaMD developers, health systems, and compliance teams. Contact us to discuss production deployment and integration with your existing regulatory workflows.