Leadership · Transformation · Product

Building solutions
that simplify complexity.

I build teams, turn product ideas into working prototypes, and secure support to move them forward. I've led the early, messy work of AI adoption, helping teams decide what to build and how to put it to use. I set the vision and take the first step with the team, staying close to the design and the people. Safety, governance, accessibility, and inclusivity shape decisions from the start. I help teams balance competing needs and ask better questions. It gets messy. We get through it. That's part of the job.

Leadership & Direction

Setting priorities, developing designers, and aligning teams around product and business goals. Clear expectations. Direct feedback. Room to grow.

Systems & Operations

Building shared standards that reduce rework, securing executive support, and resolving competing priorities. Decisions need to hold up beyond the meeting.

Design & Delivery

Mapping user journeys, identifying jobs to be done, and designing interactions and prototypes that turn insights into useful products. Staying close to the work and the people.

Guiding Principles

The teams that win the AI era will be the ones who kept people at the center of it.

Most of the industry is racing to lead with the technology. I think that is backwards. The hard part was never the model. It is deciding what should be built, for whom, and where the line is. That is product judgment, and it matters more now, not less.

My job is to hold three things together that teams tend to pull apart: what people actually need, what the system is safe to do, and what the business has to achieve. Keeping those in balance is the whole discipline.

Human benefit

Start from the person and the outcome they need, then bring AI to it. Not the other way around.

Safety & governance

Behavioral boundaries, risk tiers, and escalation paths designed in from the start, not bolted on after launch.

Business outcomes

Every decision ties to adoption, conversion, and cost. Human-centered and commercially sharp are not opposites.

Selected work

Proof, not promises.

A few places where the approach held up under real enterprise pressure.

Cairya zero-to-one AI product
01 — AI Native Product Development

From concept to first client: Conversational AI Product with guardrails.

Led a research-validated pivot that landed the first enterprise client in six months. Set the behavioral boundaries so AI performed with acceptable predictability in demos and pilots.

AI GovernanceAI Adoption0-to-1
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Inovalon Application Portal
02 — Enterprise SaaS

Transforming Product Discovery into a Commercial Growth Opportunity

An executive-sponsored initiative to unify product access, improve customer discovery, and establish a scalable experience across enterprise healthcare applications.

Enterprise SaaSGovernanceAdoption
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Inovalon Design System overview
03 — Design Systems

One design system across four business units

Built Inovalon's first unified design system on top of legacy frameworks across 40+ digital products, with an adoption strategy and C-suite advocacy pushing the change across the organization.

Design SystemsAdoptionHealthcare
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Cairya Provider Portal patient dashboard
04 — Service Design · Clinical AI

Designing safe AI-assisted clinical intake for mental health providers.

Mapped the full psychosocial assessment journey for a clinical AI intake assistant, defining safety escalation tiers, HIPAA-aware interaction boundaries, and a swimlane service design covering what AI can do, what it hands off, and where it must stop.

Service DesignClinical AISafety
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WhatIff.chat — M1, M2, M3 posting action variants
05 — AI Product Design · Mobile UX

Designing a scalable routing action for an AI assistant posting to 20+ channels.

Six variants across two levels of the problem. Verdict reached in a single session with marketing, engineering, and design.

AI Product DesignMobile UXScalable Design
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WhatIff Chat — Design Rubric document header with TOC sidebar and 1–5 adherence scoring
06 — Design Governance · Rubric

A design rubric for an AI-native product team.

19 sections, 1–5 adherence scoring, version-controlled with the codebase. Engineers make design calls without a designer in the loop — and the trade-offs are recorded.

Design GovernanceAccessibilitySystems Thinking
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Asian Development Bank Funding Resource Portal
07 — Enterprise UX

Accelerating global program start dates by improving discoverability of ADB's multi-billion dollar funding portal.

Redesigned the Asian Development Bank's Funding Resource Portal, significantly increasing discoverability of critical resources and accelerating project initiation timelines.

Enterprise UXAdoptionConsulting
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ITCI biotech 300% growth systems
08 — Strategy

Building growth strategy impacting HR & Operations team of a biopharmaceutical company undergoing hypergrowth stage.

Built the process and operational foundations for a biopharmaceutical company during their hyper growth stage (from 80 to 300+ employees by end of 2019) utilizing the full breadth of consulting skills to assess the systems, create an onboarding experience, and define top priorities for the first 90-120 days.

StrategyOnboardingService Design
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L'Oreal ML attrition model
09 — Org Design

Designing a new organizational capability — from attrition model to People Analytics function.

Built L'Oreal USA's first ML-based attrition model, then designed the organizational structure to sustain it. After presenting to the C-suite, the work became the foundation for a new People Analytics function, first in the US, then adopted by global HQ.

Org DesignData ProductExecutive
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Let's build something meaningful.

Designing for people cannot be another buzzword. It's my guiding statement. It helps me keep usefulness, safety and the business case from drifting apart from each other as a product takes shape.

Open to leadership roles, consulting opportunities and fractional roles.

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