Who RegOS Is Built For
Clinical AI governance isn't one problem — it's three, experienced by three distinct groups. RegOS was designed from the ground up to serve each of them.
Three segments served by RegOS
The people responsible for deciding what gets approved
Regulatory sandbox operators, FDA reviewers, and national health AI oversight bodies are being asked to evaluate an unprecedented volume of clinical AI submissions — without standardized tools to do it consistently or defensibly.
- Consistent, structured evaluation pipeline for every AI submission
- Tamper-evident decision records that withstand legal and regulatory scrutiny
- Reproducible scoring methodology aligned to FDA SaMD and EU MDR
- Full audit trail from intake data to final decision, dependency-traced
- Autonomous AI mode for models without real-time human oversight
Every AI submission arrives in a different format, with different evidence, evaluated through a different process. Decisions are hard to defend, harder to compare, and impossible to audit systematically.
RegOS provides a single structured intake, a consistent multi-domain validation engine, and a sealed evidence package for every evaluation. Every decision traces back to the same rulebook version.
Reproducible, defensible evaluations at scale. Regulators move from reactive review to systematic governance — with a complete audit trail that supports appeals, resubmissions, and public accountability.
The institutions responsible for what runs in their clinical environment
Hospitals and integrated health networks are procuring AI from dozens of vendors — each promising clinical-grade performance, few able to prove it. CMIOs and CISOs need a structured way to evaluate, approve, and monitor every model in their environment.
- Pre-procurement evaluation of third-party AI against your risk standards
- Auditable model registry with post-market monitoring conditions
- Fairness and bias validation across your specific patient demographics
- Governance documentation for boards, legal counsel, and compliance teams
- Integration-ready evidence packages for procurement and IT governance
Vendor AI models arrive with impressive publications but inconsistent evidence. Clinical and IT leaders have no standardized way to evaluate them — and no ongoing mechanism to verify they stay safe post-deployment.
RegOS creates a consistent evaluation gate for every model — before procurement and during operation. Post-market conditions are tracked within the platform, not left to spreadsheets and emails.
A governed AI model registry with documented approval rationale for every tool in the clinical environment. Boards and compliance teams have the paper trail. Clinicians have tools they can trust.
The innovators who need a clear path from development to approval
Clinical AI developers and medical device companies need to know — early and definitively — whether their model is ready for regulatory submission. Discovering gaps at the FDA review stage is expensive. Discovering them with RegOS is not.
- Pre-submission evaluation against FDA SaMD and EU MDR requirements
- Structured gap analysis with remediation guidance before filing
- Evidence package generation aligned to SaMD documentation standards
- Autonomous AI model pathway with MD Comparison Evaluation
- Repeatable evaluation framework as the model evolves post-clearance
Clinical AI developers spend months navigating fragmented regulatory guidance, assembling documentation without a clear standard, and discovering gaps only when regulators push back — burning time and capital at the worst possible moment.
RegOS runs a structured pre-submission evaluation against the actual regulatory frameworks — producing a scored gap analysis and a structured evidence package aligned to submission requirements, before you file.
Faster time to clearance. Fewer surprises. A complete, submission-ready evidence package that demonstrates the rigor regulators expect — and a repeatable process as the model evolves post-approval.