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Advisory and fractional product leadership for healthcare and AI ventures, and founding partnerships alongside a commercial co-founder or committed sponsor who leads distribution and demand. I take a capability that works in a demo through what decides whether it gets used: hospital IT approval, clinical sign-off, and the support queue after launch.

Direct email kanav@kanav.net
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Availability

Status
Taking advisory, fractional, and founding product partnerships
Based in
Chicago, IL
Work authorization
U.S. and Australian citizen — no sponsorship needed in either country

Engagements

Fractional product leadership
Part-time head of product for a venture-backed healthtech startup, hands-on with onboarding, clinical workflow, and the go-to-market plan.
Strategic advisory
Ongoing guidance for founders on whether clinicians will use the product, what hospital and payer review will require, and how to record AI decisions that people can challenge. Also available as a four-week diagnostic sprint.
Founding product & technology partner
I lead product and technical architecture and build the early versions myself, alongside a commercial partner who leads distribution and demand.
Clinical AI safety review
Whether a healthcare AI system can be stopped, overridden, and reversed, for health plans, healthcare AI companies, and investors. Four formats: a one-hour safeguards review, a two-week readiness sprint on one workflow, an investor diligence memo in five business days, or a two-to-three-week evaluation against FDA and EU AI Act expectations.
Commissioned research and evidence review
A bounded study for an organization that wants its own repair work counted: what the workaround costs, who can refuse it, and what evidence would show the cost while reported performance still looks good.
Independent R&D
Building NextConsensus (guideline, label, and coverage forecasts) and Ambit (agent authorization).

Where each engagement fits

The engagements above are what you buy. These are the situations they fit, with the work that shows each one.

Frontier labs and agent platforms

I build the runtime systems around capable models: tool verification, capability mapping, and reversible execution. In Ambit, an agent can propose a change over MCP but has no tool to apply it; a person approves it under a declared name.

See Ambit and Fast Harm → Inquire about this →

Zero-to-one technical products

I pressure-test the premise before locking in the build, create the first version myself, test it with the people who must approve and use it, and stay through launch and the support queue after it.

See NextConsensus → Inquire about this →

When to bring me in

  • Before the product category has a name, when nobody can point at a competitor to explain what you are building.
  • When hospital IT, security, and clinical review have to be built into the product instead of worked around.
  • When an AI agent is about to act on its own and nobody has decided what it is allowed to do.
  • When a working prototype has to become a business, or an early build needs a fundamental rethink.

Tell me which of these is closest, and what you are trying to get through.

Email kanav@kanav.net

Revised