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AI product leader, engineer, and researcher · Chicago

I bring new AI capabilities through hospital review into products still in use after I leave

14 years in healthcare technology, most of them leading and building products in clinical care, oncology, and AI. My background is in biomedical engineering and molecular biology research. Work with me →

See current work View résumé → Healthcare case studies →
Portrait of Kanav Jain
calls on an average workday
300,000+
hospitals and 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.

Current work

Both products deal with a decision others act on, and whether it still holds: a guideline, label, or coverage decision, or the permission a person has given an AI agent.

Commercial · in active development; the public site shows how a program works

NextConsensus

An illustrative NextConsensus claim record: at revision 4 the word “contested” is struck from “clinical benefit remains contested,” above the claim’s emerged, contested, and authority dates
Illustrative record. At revision 4 an editor deletes “contested,” and a disputed claim reads as settled. NextConsensus gives teams dated records like this one.

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

Experimental · open source, with a live demo

Ambit

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
The agent drafted this change over MCP, which has no tool to approve or apply it. A person approves it in a terminal under a declared name, and the approval is a tamper-evident record that expires after 24 hours.

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 scheduled observation bot and a 15,926-event public test set

See how I built Ambit, Refract, and Stims →

Selected work

Doximity

Decided by approval 2013–17

The patient sees the office, not the cell phone

Adoption may come before official approval only while the risk stays with the person choosing. When the risk is clinical, approval comes first.

Dialer still carries more than 300,000 calls on an average workday across 250+ hospitals and health systems, 9 years after I left.

Read full case study →
CancerCompass / CTCA

Decided by attention 2019–21

Scaling oncology navigation for 30 million annual visitors

A frightened person is not short of information. The scarce resource is attention and trust, so the product’s job is the next step and a person to call.

Chat conversions up 267% and bounce rate down 25% across 30 million annual visitors after the rebuild I led.

Read full case study →
Transcarent

Decided by accountability 2021–22

Four specialty programs on one routing architecture

One system can carry many programs once every decision point has a named owner.

Routing delays stopped being the primary bottleneck, and the gap between the best and worst service lines narrowed.

Read full case study →
See all case studies →

Writing and standards

The question under the essays and the standards: would a system still look like it works if we stopped counting the people covering for it?

  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 Ethotechnics’ framework for recording approval, challenges, and corrections.

Revised