Clinical AI governance and implementation for health AI companies
I help health AI, telehealth, digital care and clinical software teams design, evaluate and govern AI systems that are clinically safer, regulator-ready and usable in real-world care.
My work sits at the intersection of clinical medicine, AI evaluation, product implementation, digital health operations and health regulation.
Who I help
I work with teams building or scaling:
- AI doctors
- Clinical copilots
- Symptom checkers and triage tools
- Preventative health and longevity platforms
- Telehealth and digital care systems
- Clinical content and decision-support products
- Health AI tools requiring clinical safety review, governance or evaluation
What I help with
Health AI products do not usually fail because the demo looks bad. They fail because the clinical edge cases, escalation pathways, scope boundaries, governance model or real-world implementation have not been properly designed.
I help teams find and fix those risks before they become patient safety, regulatory, reputational or commercial problems.
Services
Clinical AI safety audits
A structured review of your AI product, model outputs, clinical content, escalation logic, user-facing claims and safety boundaries.
This may include:
- Review of model responses or clinical content
- Identification of unsafe or misleading outputs
- Red-flag and escalation pathway review
- Clinical scope boundary review
- Human oversight and workflow review
- Risk-prioritised remediation plan
Best for teams that already have a product, prototype or clinical workflow and want a focused external review.
AI doctor and clinical copilot evals
Design and review of evaluation systems for AI doctors, clinical copilots, symptom engines and health AI products.
This may include:
- Benchmark case design
- Synthetic patient cases
- Training and test case libraries
- Clinical reasoning rubrics
- Red-flag safety criteria
- Longitudinal and preventative health evals
- Failure-mode taxonomies
- Regression testing for model or prompt changes
Best for teams that need to know whether their AI system is clinically reliable across realistic patient scenarios, not just polished demo cases.
Clinical governance frameworks
Design of practical governance systems for health AI products and digital care workflows.
This may include:
- Clinical accountability models
- Human-in-the-loop review pathways
- Escalation and handover logic
- Audit trail requirements
- Clinical risk registers
- Safety review workflows
- Clinical policy architecture
- Incident and feedback loops
Best for teams preparing to scale, raise capital, enter regulated markets or work with clinical partners.
Regulatory and product translation
Practical translation of health AI, SaMD, clinical decision support and digital health governance requirements into product and operational decisions.
This may include:
- Product risk classification support
- Review of clinical claims and user-facing language
- SaMD and CDSS boundary analysis
- TGA, FDA and EU-style regulatory risk mapping
- Documentation gaps and governance requirements
- Founder or executive briefing memos
This is not a substitute for formal legal advice. It is designed to help teams understand how clinical, regulatory and product risks interact before they commit to a build or launch pathway.
Fractional clinical AI leadership
Ongoing advisory support for teams that need senior clinical, product, safety or governance input without hiring a full-time clinical AI lead.
This may include:
- Weekly or fortnightly advisory sessions
- Clinical product review
- AI output review
- Governance and policy design
- Safety eval oversight
- Founder and executive support
- Clinical implementation strategy
- Support preparing for investors, partners or regulators
Best for early-stage or scaling teams that need senior clinical AI judgement embedded into the product cycle.
Example problems I can help solve
- “We are building an AI doctor and need to know whether the answers are clinically safe.”
- “We need benchmark cases and rubrics for clinical AI evaluation.”
- “We are not sure whether our product is crossing into clinical decision support or SaMD territory.”
- “Our AI gives good general answers but misses escalation, red flags or safety-netting.”
- “We need a clinical governance framework before launching or scaling.”
- “We need someone who understands medicine, AI, product and regulation in the same conversation.”
- “We need an external review before showing this to investors, clinicians or partners.”
- “We need clinical safety criteria that are specific enough to train and test against.”
Relevant experience
I am a physician, digital health founder, former medical director and clinical AI evaluator with experience across telehealth, clinical governance, AI doctor evaluation, regulated clinical software and health technology implementation.
My background includes:
- Medical training and clinical practice
- Digital health founding and product implementation
- Clinical governance and policy development
- Telehealth system design
- Regulated clinical software and SaMD experience
- AI doctor evaluation and clinical safety benchmarking
- Health law and regulatory research
- Clinical content and safety review for AI health products
I am especially interested in the layer between promising AI capability and safe clinical deployment: the evals, governance, escalation pathways, product constraints and human oversight required to make health AI usable in real care.
How I work
I prefer defined, practical work with clear outputs.
Typical engagements include:
- A focused clinical AI safety audit
- A fixed-scope eval or benchmark design project
- A governance framework build
- A due diligence or risk review memo
- Ongoing fractional advisory support
I do not offer generic AI commentary. My work is focused on clinical safety, governance, evaluation, implementation and product risk in healthcare settings.
All advisory work is subject to confidentiality, conflict checks and appropriate boundaries around current roles and client information.
Work with me
If you are building a health AI, telehealth, digital care or clinical software product and need senior clinical AI input, I can help you review the risks, sharpen the governance model and design safer systems before scale.