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Accountable systems · escalation · recovery

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Helping healthcare and AI teams turn high-stakes ideas into reliable products.

Kanav Jain

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

I partner with healthcare and AI teams to ship products that stay dependable in real operations.

  • Turn ambiguous bets into clear product roadmaps, milestones, and tradeoffs.
  • Design care and communication workflows that work for clinicians, patients, and operators.
  • Set up ownership, escalation, and review loops that still function when conditions are messy.
Why this approach

I blend product strategy, clinical workflow insight, and operating discipline so teams can move quickly without creating hidden risk.

Email Kanav View work →

Start here by intent

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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Start with what you need

Go directly to outcomes, methodology, or essays.

Start here by intent

Patient reach

100M+ patient–clinician connections across clinical workflows

Audit-ready

Policy checks, approvals, and overrides remain easy to trace

Incident learning

Postmortems feed new evals and guardrails

Proof points

Results from real-world delivery

A quick read on what shipped and what changed.

Proof Doximity Dialer: 100M+ patient–clinician connections enabled (to date) See the work →
  • Clinical + product depth From workflow strategy to shipped care experiences
  • Scale and adoption Products that teams and members actually use
  • Operational trust Incidents, overrides, and audits with clear ownership

Patient reach

100M+ patient–clinician connections across clinical workflows

Audit-ready

Policy checks, approvals, and overrides remain easy to trace

Incident learning

Postmortems feed new evals and guardrails

The Proof

Selected work

Representative engagements and outcomes.

Product leadership

Doximity Dialer

Built and scaled Doximity Dialer with safety rails and clinician-led overrides during failure.

  • HIPAA-conscious caller ID workflow that reduced routing friction
  • 100M+ patient–clinician connections with audit-friendly delivery 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 →

Co-founder and CEO

Andwise

Built physician financial wellness products combining personalized guidance, expert support, and operational guardrails.

  • Scaled advisor and clinician inputs into practical decision support
  • Built trust-forward experiences for complex financial decisions
View case study →

Research and advisory

The Crumple Zone

Documenting practical playbooks for AI governance, civic systems, and high-trust operations.

  • Burden modeling and refusal playbooks for real-world teams
  • Governance templates used across healthcare, AI, and public-interest work
Explore Ethotechnics →

Common triggers

When teams reach out

Situations where an outside operator can unblock progress quickly.

Approach

How I work

A clear framework for safer product decisions.

I use a practical operating model 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, and whether teams learn quickly 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.

Operating framework

How to design safer, accountable AI in real operations

Read the full framework →

Cross-functional context

How I work across teams

Engineering, product, and operations 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 translate complex policy and organizational dynamics into clear decision rights, review plans, and escalation paths teams can actually use.

Writing

Latest writing

Essays, notes, and audits on building trustworthy systems.

Explore writing →

Updated Feb 2026 · 282 total essays

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Latest essays

Contact

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