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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 help healthcare and AI teams ship systems that stay safe when pressure is high.

  • Map model failures to patient risk with clear ownership.
  • Design override paths with authority and audit trails.
  • Ship guardrails and incident workflows that hold up in care operations.
Why this approach

My work turns safety goals into operating defaults: clear ownership, risk-linked checks, and response paths people can actually use.

Email Kanav View work →

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

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Quick start

Patient reach

100M+ patient–clinician connections across clinical workflows

Audit-ready

Policy checks, approvals, and overrides leave clean trails

Incident learning

Postmortems feed new evals and guardrails

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
  • Operational trust Incidents, overrides, and audits with clear owners

Patient reach

100M+ patient–clinician connections across clinical workflows

Audit-ready

Policy checks, approvals, and overrides leave clean trails

Incident learning

Postmortems feed new evals and guardrails

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

A practical framework for safer product decisions.

I ground my work in Ethotechnics, an applied practice for decision quality, incident response, and recovery. In practice: define who can intervene, how quickly issues must resolve, and what controls make that enforceable.

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

  • Prefer reversible decisions when risk is high
  • Bind decision rights to named owners
  • Use clinical-risk evidence, not safety theater
See the full framework →
  • Keep logs and instrumentation audit-ready
  • Give escalation owners real authority to intervene

I evaluate systems by failure behavior: detection speed, intervention rights, patient risk created, and whether teams learn 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 →

The Proof

Selected work

Representative engagements and outcomes.

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
View case study →

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
View case study →

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
View case study →

Full-Stack Context

How I work across layers

Engineering, product, and governance perspectives used together.

The Engineer

Code + constraints

My bioengineering training taught me to treat constraints as design inputs and turn ambiguity into measurable systems.

The Founder

Product + operations

I build tools that survive real operations, backed by ownership, instrumentation, and accountability.

The Theorist

System + governance

I study how institutions allocate authority and delay, then 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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Ready to improve system safety?

Start with a scope call or review 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