Medical Doctor • MBA • PhD in AI & Software Engineering • Author
I work at the intersection of clinical medicine, AI, and business to assess whether health-tech products are real, defensible, and deployable.


I work with healthcare startups, investors, and enterprises to identify the clinical, technical, and regulatory risks that determine whether AI products succeed or fail in the real world.I typically assess:
• Clinical validity and workflow fit
• AI / ML substance and data quality
Regulatory realism and compliance risk
• Architecture, security, and production readiness
• Team and execution risk
My background spans clinical medicine, business strategy, and AI research. I’ve spent over six years building a healthcare startup, giving me firsthand exposure to the technical, regulatory, and operational realities that rarely show up in pitch decks.I have advanced training in medicine, conducted doctoral research in AI, hold an MBA, and have published academic work. I also authored a practical post-mortem on building healthcare companies, focused on the failure modes founders and investors tend to underestimate.In addition to advisory work, I build and research AI systems, including work on observability and long-term memory architectures.

I work on a small number of engagements at any given time.Typical work includes:
• AI health-tech diligence and risk reviews
• Founder and board-level advisory
• Pre-deployment and pre-partnership assessmentsIf you’re preparing for fundraising, diligence, or deployment and would value an independent perspective, you can reach me below.
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I write to clarify how healthcare and AI systems fail in practice — and how founders, investors, and operators can reason about risk before it becomes expensive.
My publications reflect a mix of hands-on startup experience and academic research, focused on real-world deployability rather than theory.