Commercially offered · public forecast registry and published review methodology
NextConsensus
Estimates how likely a guideline, label, or coverage decision is to change by a set date.
I’ve taken healthcare products from demo through hospital review into daily use
Now I build AI products the way I built clinical software: identifying unexamined operational assumptions and building systems that eliminate recurring workarounds, from office-number calling at Doximity to runtime agent controls today.
Systems designer and independent researcher · Chicago
- calls on an average workday
- 300,000+
- later, in daily use
- 9 years
Doximity Dialer, which I originated as founding product lead. Doximity’s report for October–December 2025.
Selected case studies
The patient sees the office number, not the doctor’s cell
- The situation Physicians called patients from personal phones, giving the number away for good or showing “Unknown Caller.”
- My choice I proved caller ID over a weekend and launched on a vendor that did not require proof of number control.
- What followed Hospital authorization followed adoption, and the route was unchanged when I left.
Scaling oncology navigation for 30 million annual visitors
- The situation A family facing a new cancer diagnosis needed the next step and a number to call. The site gave them encyclopedia entries.
- My choice I relaunched around plain-language care pathways and nursing triage, with product and nursing reviewing real questions together.
- What followed Chat conversions rose 267% and bounce rate fell 25% across 30 million annual visitors.
Four care programs, one system, and an owner for every case
- The situation High-complexity cases in surgery, oncology, and behavioral health were stalling in exception queues.
- My choice I built one shared routing system instead of four custom ones, accepting higher upfront coordination to enable rapid expansion across specialties.
- What followed Four programs launched on shared infrastructure, and routing delays stopped being the primary bottleneck.
What connects my work
I design software and study how the systems we build affect what people can do, what they come to depend on, and how much influence they have over how those systems work. At Doximity, Dialer let a clinician call from a personal phone while the patient saw the office number. Can a tool expand what people can do and their ability to shape how it works at the same time?
Research →What I’m building
Experimental · open source, with a live demo and a published roadmap
Ambit
Maps what an agent setup can already do, what one more step would unlock, and which of those tools actually work.
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Live · open source, with a scheduled observation bot and a 15,926-event public test set
Refract Replays source revisions to catch a change before the citations that rely on it go stale.
Writing and standards
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Research and essays
From a first-author ACS Symposium Series chapter on RNA thermodynamics to 230+ essays at The Crumple Zone on how institutions distribute burden, absorb failure, and decide who can exist inside them. Selected writing →
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Proposed AI standards
I wrote Ethotechnics’ framework for recording approval, challenges, and corrections. ethotechnics.org
What I want to test next
Whether an auditable record can trace a dispute end to end: from an agent action through human challenge to downstream correction.
Staff Fix the Errors Your Dashboard Doesn’t Show An automation can report 94% straight-through processing while staff fix mismatched codes in shadow spreadsheets.
I take advisory and fractional product leadership roles for healthcare and AI ventures, partner with commercial co-founders on new builds, and research how institutions correct their failures. If you are building something that needs to survive review, or run a system where people are covering for its defects, I would like to hear from you. kanav@kanav.net
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