Backed by an engineering PhD, I help MedTech companies create clear, traceable, review-ready documentation for clinical evidence, product claims, and AI use. As an AI governance documentation specialist, I use a minimalist, workflow-based approach tailored to each company’s needs — so teams can stay audit-ready without unnecessary reporting burden.
A medical affairs team lead asked to show how AI governance and quality are being built in clinical, regulatory, or medical writing work, needing audit-friendly AI-use records but wanting a practical system, instead of a giant policy binder.
A RA/QA lead preparing or updating a CER, PER, PMS, PMCF, or technical documentation file — and you need clinical evidence to be organized, summarized, and traceable without slowing the whole team down.
A MedTech founder or project owner preparing for submission, launch, financing, partnership, or acquisition — and realizing that your evidence, claims, and documentation need to look more mature than your team size.
A medical writing team overloaded with CER literature reviews, state-of-the-art summaries, clinical data tables, evidence gaps, or claim-evidence mapping — and needing reliable support that can plug into your workflow.
A software, diagnostics, imaging, or connected-device team working with patient data, clinical outputs, or AI-assisted workflows — and needing lightweight documentation that shows how tools, data, outputs, and human review are controlled.
Most MedTech teams I support already have strong products, serious clinical evidence, capable RA/QA teams, and smart people across clinical, product, and commercial functions. What slows progress is not a lack of expertise, but scattered evidence, unclear ownership, inconsistent claims, and limited documentation around how decisions, AI tools, data, outputs, and human review are controlled.
Without a lightweight documentation structure, the work becomes heavier than it should. CER updates take longer. Literature reviews become harder to defend. Product claims drift away from the evidence. AI use stays informal. Customer or audit questions create last-minute stress. Teams keep doing the right work, but the proof of that work is not always easy to show.
My role is to help turn that complexity into clear, traceable, review-ready documentation — using a minimalist approach tailored to the company’s actual workflow, risk level, and stage of growth.
Evidence and interprecation verification with strong critical reasoning and meticulous attention to detail.
Practical training on evidence verification and critical thinking while using AI to enhance accuracy in writing.
Minimal AI-use inventories, review checklists, audit sheets, prompt/output controls, and human-verification records tailored to workflows.
Deep scientific literacy across clinical, technical, regulatory, and AI-related information
Experience supporting CER literature reviews, evidence summaries, and medical writing workflows
Strong ability to check whether claims, data, references, and source documents actually align
Structured reasoning when evidence is scattered, inconsistent, incomplete, or difficult to interpret
Practical AI governance documentation support without creating unnecessary reporting burden
Minimalist, workflow-based approach tailored to each company’s size, risk level, and documentation needs
“Ri helped us turn informal AI use into clear, review-ready documentation. Instead of creating a heavy policy burden, she mapped how AI tools were being used, what data was involved, who reviewed the outputs, and where records needed to be kept. The result was a practical governance structure our team could actually maintain.”
Ri Xu, PhD provides clinical evidence, CER support, fact-checking, and AI governance documentation for MedTech companies and medical writing teams. Her work helps regulated teams keep evidence, data summaries, AI-assisted workflows, and review records clear, traceable, and defensible in environments where small errors can create regulatory, clinical, or audit risk.
Based in Montreal and working internationally, Ri partners with RA/QA, clinical affairs, medical writing, product, and innovation teams to turn complex clinical, regulatory, and AI-related information into practical documentation. Backed by an engineering PhD, medical writing experience, and AI governance training, she helps teams strengthen accuracy, reduce documentation friction, and use AI critically without compromising evidence standards.