Work with me

Building systems that can recognize when they’re wrong

I’m a technologist, founder, and independent researcher working across healthcare, human–AI interaction, and institutional accountability. I built and led healthcare products at Doximity, Transcarent, and CancerCompass, and co-founded Andwise. That work led me to a broader question: why can institutions become more efficient, capable, and successful without becoming more answerable to the people who depend on them?

See case studies See current work →
Portrait of Kanav Jain

Healthcare systems  · Human–AI interaction  · Institutional accountability

Value Measure Source
300,000+ calls on an average workday Doximity Dialer, which I originated as founding product lead. Doximity’s report for October–December 2025.
9 years after I left, still in daily use

Selected case studies

Doximity

2013–17

The patient sees the office number, not the doctor’s cell

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Doximity Dialer “Call from” selector set to OFFICE, with a tooltip explaining the recipient sees this number as caller ID
The identity decision in the product’s own words: the clinician picks which number the patient sees, with the office line preselected.
CancerCompass / CTCA

2019–21

Plain-language next steps for 30 million annual visitors

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Transcarent

2021–22

Four care programs, one system, and an owner for every case

Read full case study →
See all case studies → Work with me →

What connects my work

Doximity Dialer lets a clinician call from a personal phone while the patient sees the office number, and it is still in daily use. I now study how institutions respond when the tools they rely on make a mistake. Can the people affected challenge the decision and get it corrected?

Research →

What I’m building

For sale

NextConsensus

Estimates how likely a guideline, label, or coverage decision is to change by a set date.

NextConsensus share card for FF-011: “Will FDA approve ivonescimab for EGFR-mutated non-small cell lung cancer after EGFR TKI therapy by Nov 14?” with a PDUFA goal date of 14 November 2026 and a registered probability of 15%
Enlarge image
Registered 2026-09-26 at 15%, compared with a 70% estimate for similar FDA approvals by their deadline. The comparison is an estimate, not a count of past decisions. Unresolved at the 2026-11-04 registry snapshot.

Experimental

Ambit

Maps what an agent setup can already do, what one more step would unlock, and which of those tools actually work.

Try the capability map

A terminal running “ambit approve” on an agent’s proposal: approved by Jordan, applicable true, with the note that the approval artifact is signed and expires
Enlarge image
The agent drafted this change through Ambit’s tools using Model Context Protocol (MCP), which connects agents to tools. Those tools let it propose a change; approval and application require a person in a terminal. The approval records that person’s declared name, is tamper-evident, and expires after 24 hours.

  • Live

    Refract Replays source revisions to catch a change before the citations that rely on it go stale.

Current work: code and checks →

Writing and standards

  1. 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 →

  2. Proposed AI standards

    I wrote the Ethotechnics framework, an open set of proposed standards for recording approval, challenges, and corrections. ethotechnics.org

What I want to test next

Whether a record can carry a real dispute end to end: an agent acts, a person challenges the action, and the correction reaches every decision that depended on it.

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, join new companies as a founding product and technology partner, and work with researchers and institutions on how they recognize and correct failure. If you have a product that works and a review standing between it and its users, or a record of decisions you want tested, I’d like to hear from you. kanav@kanav.net

Revised