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Accountable systems · escalation · recovery

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Healthcare and AI teams ship systems that stay accountable under pressure.

Kanav Jain

Product leadership for high-stakes AI systems where failure, delay, and override actually matter.

I design and ship healthcare and AI systems with explicit decision ownership, escalation clocks, and repair paths that still work when the system is wrong.

  • Translate model failure modes into patient risk with named owners and operating controls.
  • Set override paths with timers, human authority, and audit trails.
  • Ship evals and guardrails that hold up in real care settings, even during incidents.
Why this approach

I turn safety commitments into daily operations: risk-tied evals, named owners, and recovery workflows that survive real incidents.

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Quick start

Portrait of Kanav Jain
Clinician-in-the-loop review A clinician and model co-review moment showing human judgment staying in control.
Human oversight Clinician-in-the-loop review
Safety case stack A layered safety case: intent, policy, evals, guardrails, escalation, audit logging, and the learning loop.
Safety case Safety case stack

Scroll map

Start with the signal that matters.

Pick the thread you need first, then go deeper.

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Start with the essentials

Jump straight to key proof, practice, and writing.

Quick start

Patient reach

100M+ patient–clinician connections across clinical workflows

Audit-ready

Policy checks, approvals, and overrides leave a clean trail

Incident learning

Postmortems feed new evals and guardrails with clear owners

Proof points

Signals from the field

Results and outcomes behind the work.

Proof 100M+ patient–clinician connections enabled (to date) See the work →
  • Clinical safety cases Model behavior tied to patient risk, not just benchmarks
  • Operational trust Incidents, overrides, and audits handled with clear owners and bounded timelines

Patient reach

100M+ patient–clinician connections across clinical workflows

Audit-ready

Policy checks, approvals, and overrides leave a clean trail

Incident learning

Postmortems feed new evals and guardrails with clear owners

The Proof

Portfolio

A quick scan of the teams and outcomes I have led.

Product leadership

Doximity

Scaled clinical communication with safety rails and clinician-led overrides during failure.

  • On-call clinician workflows that reduced routing friction
  • Trust and delivery metrics with audit-friendly logs
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Platform strategy

Transcarent

Consumer-directed health experiences with support handoffs that hold during failure moments.

  • Care navigation systems with accountable handoffs
  • Experience design for payers with measurable outcomes
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Founder

Andwise

Financial immunization for doctors with guardrails and override options that hold under stress.

  • Debt and savings products with clear decision rules
  • Clinical finance tooling built for trust
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Choose a starting point

Pick the thread that fits your role.

Common triggers

When teams reach out

Signals that it is time for help.

Methodology

How I Think

The research practice behind my product decisions.

I ground my work in Ethotechnics—applied research on decision quality, response, and recovery. In plain terms: define who can intervene under stress, how fast issues must resolve, and build the controls that make that enforceable.

The principles below define how I evaluate risk, design guardrails, and support teams.

  • Reversibility by default
  • Binding decisions and decision rights
  • Clinical risk evidence, not safety theater
See the full framework →
  • Auditability through instrumentation and logs clinicians trust
  • Escalation authority that can actually intervene

I evaluate systems by their failure modes: how quickly issues are detected, who can intervene, what patient risk is created, and whether the organization learns fast enough to prevent repeats.

Clinical risk ladder A severity-by-autonomy matrix that maps control strength to patient harm potential.
Risk tiering Clinical risk ladder
Eval coverage map Failure modes linked to evals and mitigations so safety plans trace cleanly from risk to control.
Failure modes → controls Eval coverage map
Decision rights map A compact map showing which roles can ship, override, halt, and audit the system.
Decision rights Decision rights map
Ethotechnics bridge diagram A minimalist bridge arch connecting two dots, representing steady decision pathways.

Ethotechnics

Safety cases for AI that touches reality

Enter the Bridge →

Full-Stack Context

Full-Stack Context.

Three lenses that connect my engineering roots to product and systems leadership.

The Engineer

Focus: The Code

I started in bioengineering, which taught me to treat constraints as design inputs and to turn ambiguity into measurable systems.

The Founder

Focus: The Product

I build tools that survive contact with operations—backed by ownership, instrumentation, and accountability.

The Theorist

Focus: The System

I study how institutions allocate time, delay, and decision authority—and turn that into decision rights, eval plans, and escalation maps teams can run.

Writing

Latest writing

Essays, notes, and audits on building trustworthy systems.

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Updated Feb 2026 · 282 total essays

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Latest essays

Contact

Ready to make this system operationally safe?

Start with a quick scope call or review the engagement paths first.

Next step

Scope the safest next move.

Bring the decision you’re stuck on—AI safety, clinical workflow, or governance—and I’ll map the smallest binding shift that unlocks momentum.

Email Kanav See how I work