Commercial · in active development; the public site shows how a program works
NextConsensus
Tracks when medical evidence moves ahead of guidelines.
AI product leader and hands-on builder · Chicago · Open to relocation
I turn new AI capabilities into products that hospitals and other cautious institutions will deploy
- calls on an average workday
- 300,000+
- health systems using it
- 250+
- since I left, still running
- 9 years
Doximity Dialer, which I originated as founding product lead. Doximity’s own figures, February 2026.
14 years as a product leader and hands-on builder, making products in clinical care, oncology and AI, after training in biomedical engineering and molecular-biology research. See where I’d fit →
Current work
The two products deal with one problem: records that go out of date while people still rely on them, like a guideline that no longer matches the evidence.
Experimental · open source, with a live demo and a roadmap that says what is not built
Ambit
Distinguishes the tools an agent can reach from the actions it is authorized to take.
- Refract Records when a source changed and what changed. Live · open source, with a daily observation bot in production and a 16,146-edit public test set
- Fast Harm, Slow Repair A draft test of how far an AI mistake spreads, and whether the fix reaches everyone it affected. Draft · 1 of 12 development cases built; no model results yet
Where I come in
I come in before there’s a roadmap, build an unproven idea far enough to see whether it holds, and then decide what to scale, what to cut, and who should own it.
I originated Doximity Dialer, led R&D at CancerCompass, and co-founded Andwise. Andwise showed in year one that physicians wanted it; I did not work out who would pay until year two, and by then every path that could fund growth made someone other than the physician the paying customer. I chose to wind down the company in 2024. Since then I have built NextConsensus, Ambit, and Refract, putting new AI capabilities into production alongside cross-functional teams.
Selected work
Decided by approval
The patient sees the office, not the cell phone
Physicians calling from a personal phone had to expose their number or hide it behind “Unknown Caller,” making patients less likely to answer. As founding product lead, I originated the identity layer that let the call come from their own phone while the patient saw the office number — so it got answered, and the cell stayed private.
Read case study →
Decided by accountability
Four specialty programs on one routing architecture
Four specialty-care programs launched on one shared architecture.
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Decided by who pays
Reading the contract before the physician signed it
1,200+ physician users, then a deliberate wind-down when the fundable paths changed who the product would serve.
Read case study →Revised