Turn AI Regulation Into
Real-World Deployment.
Precoh RegOS transforms fragmented regulatory requirements into structured, executable, and auditable workflows—so clinical AI can be evaluated, approved, and scaled with confidence.
Replace ad hoc validation with reproducible pipelines designed for regulators, health systems, and AI innovators.
Clinical AI is ready. Regulatory infrastructure isn't.
Healthcare AI development has outpaced the governance systems designed to validate and approve it. The result: capable models stuck in review limbo, ad hoc compliance processes, and regulators without structured tools to make defensible decisions.
See How RegOS Solves Thisof healthcare AI models never reach clinical deployment
wasted annually on AI initiatives that fail to deliver value
of health systems lack a formal AI governance policy
of deployed models have no active drift monitoring
Advisory expertise meets regulatory execution.
Precoh brings together two complementary capabilities — expert consulting that builds clinical AI readiness, and the RegOS platform that executes it. Together, they replace ad hoc AI reviews with structured, reproducible pipelines.
Advisory builds the readiness. RegOS ensures every model is evaluated, approved, and scaled safely — without stalling innovation or overloading clinicians and compliance teams.
RegOS: Regulatory infrastructure, not just a checklist
Most 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 operationalizes FDA SaMD, EU MDR, and IMDRF frameworks so your team can focus on outcomes, not paperwork.
Three stages. One defensible record.
Every clinical AI model moves through the same structured pipeline — from structured intake through a sealed evidence package ready for regulatory submission.
Evaluate & Validate
Structured intake captures model identity, risk classification, and documentation. Five domain engines — Data Governance, Clinical Validation, Fairness & Bias, Technical Standards, and Post-Market Governance — run sequentially with real-time results.
Score & Decide
Domain scores are weighted by clinical risk profile and aggregated into a composite score. The decision engine applies the SaMD framework to issue a defensible verdict: Approved, Conditional, or Not Approved — with full reasoning exposed.
Package & Deploy
Every evaluation step is assembled into a sealed, tamper-evident evidence package. Decision traces link each verdict back to its inputs. The result: a complete, submission-ready record that holds up to regulatory scrutiny.
Built for the people who bear accountability
RegOS serves three distinct constituencies — each with different roles in the clinical AI ecosystem, and different needs from a regulatory execution platform.
Regulators & Sandbox Operators
Run consistent, reproducible evaluations across every AI submission. Replace inconsistent ad hoc review with a structured pipeline that produces defensible decisions and a complete audit trail.
See their use caseHealth Systems
Evaluate third-party AI models before procurement. Maintain an auditable record of every model in your clinical environment, with post-market monitoring conditions tracked and enforced by the platform.
See their use caseAI & MedTech Companies
Run pre-submission evaluations before regulatory filing. Identify gaps early, generate structured documentation, and arrive at FDA or EU MDR submission with a complete, defensible evidence record.
See their use case