I am a healthcare technology operator and advisor working at the intersection of AI value creation, regulated product commercialization, and operating model design.
I help healthcare CEOs, boards, investors, and operating partners determine where the value in AI is real, what has to change for it to reach the P&L, and which decisions leadership must make to get there.
That work is grounded in nearly two decades building and scaling regulated healthcare products from inside the companies responsible for delivering them.
I have led product, engineering, regulatory, quality, privacy, security, and compliance functions, and brought more than 30 regulated products to market across AI-enabled devices, diagnostics, clinical trials, connected health, and cell and gene therapy.
I have also been on both sides of enterprise scrutiny: the vendor trying to clear the review, and the executive whose signature authorized the technology’s use.
Building regulated healthcare technology
Shipped across AI, diagnostics, wearables, and clinical trials
Product, Engineering, Regulatory & Quality, Testing & Validation Services, Security, Privacy accountability
Value attributed by a client to one accelerated launch
The hardest healthcare technology problems rarely belong to one department.
A product decision changes the regulatory claim. The claim changes the evidence requirement. The evidence changes the buyer. The buyer changes the workflow, reimbursement path, integration burden, and economics.
Each function may be doing its job correctly while the company as a whole makes the wrong decision.
That is the work I have spent my career doing: seeing the complete system, identifying the assumption that will not survive contact with the market, and creating a practical path through it.
Sometimes the answer is to invest.
Sometimes it is to change the operating model, narrow the market, remove human review, build missing evidence, or redesign the commercial motion.
Sometimes the answer is to stop.
My role is not to defend the AI story a company already wants to tell. It is to determine which parts of the story are real enough to fund, operate, sell, and stand behind.
Four companies, one pattern: the technical work was the smaller half of the decision.
Korio’s COO, who had previously been my CEO at Endpoint Clinical, recruited me to help build the regulated clinical-trial technology company from the ground up.
One recurring client process took six weeks before delivery could begin. AI agents brought the initial documentation cycle down to a day and a half. The important decision came afterward: reducing what humans still had to review, so the technology created capacity rather than merely producing faster drafts.
I helped build the product-development and testing systems behind one of the first commercially approved CAR-T therapies in the United States.
Risk-based testing and automation reduced a regulated release cycle from roughly four months to three weeks. The customer attributed $81 million in value to the earlier launch.
I worked across regulatory strategy, product development, market entry, privacy, and enterprise adoption for an FDA-regulated cardiac platform, including opening pathways into the NHS and the U.S. Department of Veterans Affairs, and supporting the integration of regulated cardiac technology into the Apple Watch.
I carried compliance, privacy, and information-security accountability through rapid growth and a Fortune 500 acquisition. I have rebuilt these functions from the ground up, defended MHRA scrutiny, remediated enterprise controls, and worked through the reviews that determine whether a promising product ever reaches production.
The model is rarely the entire problem.
Value is usually trapped in the workflow, review burden, evidence, decision rights, commercial assumptions, or operating structure surrounding it.
Through my personal advisory practice, I work with healthcare CEOs, boards, operating partners, and deal teams.
The work includes evaluating AI value-creation plans, pressure-testing investment assumptions, identifying operational leverage, defining decision rights, and determining what should be funded, fixed, deferred, or stopped.
Engagements range from pre-investment diligence and fixed-scope operating blueprints to fractional executive responsibility for a defined set of AI decisions.
Explore AI value creationThrough Vahana Labs, I work with healthtech, medtech, diagnostics, SaMD, and digital-therapeutics companies entering or expanding in the United States.
The central question is sequencing: which market can buy, what evidence it requires, what claims the company can make, how payment works, and what must happen first.
This work helps teams avoid spending a year pursuing the wrong customer, regulatory pathway, pilot, or data strategy.
Visit Vahana LabsI write Operating in HealthTech, where I examine how healthcare products survive the distance between technical possibility and enterprise reality.
I am the co-author, with Kimberly Bloomston, of Built to Survive: Building Trusted AI Products and Organizations — on the infrastructure, decisions, and operating disciplines required to build AI products that buyers can adopt and organizations can responsibly support.
I teach and advise healthcare leaders, founders, and emerging companies through:
Where healthcare scale should create leverage, and which interventions are worth the capital.
The advisory work →The useful starting point is usually not “What can we do with AI?” It is a specific decision the organization has been unable to make.
Tell me the decision in front of you. I will tell you candidly whether it is one I can help you make.
Book a call →