Frisco, Texas
Engagement and accounts
Engagement and account leadership · AI from pilot to production
Enterprise AI does not fail on the model. It fails on adoption.
I have spent 24 years running a small number of very large accounts as businesses I own — the relationship, the P&L, the plan and the risk.
The accounts grew because the delivery held. I build the systems myself, so the technical conversation does not get handed to someone else.
Fortune-10 healthcare
Client partner
Owned end to end
The number
$3M to $27M in three years — and the mechanism is the interesting part.
- Opening position
- $3M · 2016
- Delivery that held. Landing a capability inside one business unit, proving it against a measured baseline, then earning the next one.
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- Brand and geography expansion. The same pattern extended across brands and three geographies rather than re-sold each time.
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- Trusted-advisor renewals. A multiyear plan held at CXO level, so the account was not re-pitched at every cycle.
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- Closing position
- $27M · 2021
Expansion, not new-logo hunting. The delivery organization behind it grew from 10 to 300 across three geographies over the same period. It was recognized with the EPAM CEO Award for Value Creation.
CIO · CTO · CDO · COO
Business-line leadership
The role
What I own in an account.
Executive relationship depth
CIO, CTO, CDO, COO and business-line leadership. A trusted-advisor position held across multiyear cycles, not rebuilt at every renewal.
Delivery and outcomes
Scope, sequencing, quality, and the measured baseline that proves the lift. Accountable for whether a deployment lands, not for whether it ships.
Account growth and P&L
Expansion earned from delivered results: multiyear account plans, margin, forecasting and adjacency across brands and business units.
AI adoption and scale-up
Pilot to production, workflow redesign, readiness and adoption measurement — and the change motion that decides whether a deployment holds.
Technical credibility
Architecture, data foundations, retrieval and evaluation discussed directly with engineering audiences, not routed to a solutions engineer.
Complex environments and governance
Procurement, legal, security and technical evaluation, with SOW and change-order accountability. Data privacy, IP and audit-grade traceability where the answer has to survive scrutiny.
Production, not prototype
Solo, end to end
The differentiator
I lead AI programs, and I build them.
Most people in this seat hand the technical conversation to a solutions engineer. I write the systems, which is why architecture, retrieval and evaluation are a discussion rather than a hand-off — and why I can tell a CTO what will not work before it is scoped.
Regulated-compliance adjudication
Reads obligations against live SEC and FINRA sources, adjudicates exceptions and produces a defensible remediation trail — built for environments where the output has to survive an audit.
Production AI-OCR, at CIO and COO level
Unstructured field documents converted into a clean analytics database for a global industrial distributor. I owned the adoption motion as well as the build: field-user readiness, enablement and measurement.
Audit-grade traceability
Agentic orchestration and multi-step LLM workflows instrumented with evaluation harnesses and Merkle-hashed event logs under agentic CI, so a claim about what the system did can be checked rather than asserted.
I write up what I find in the field. 13 teardowns on where value leaks in enterprise systems, and the working fix.
Clients de-identified
Healthcare and distribution first
The record
Accounts I have owned.
Described by shape rather than by name. I do not publish client names.
Fortune-10 healthcare distributor
Owned the account end to end. B2B commerce, a clinician-facing program addressing physician burnout, in-store experience across a ~1,200-store retail network grounded in ethnographic research, and a rapidly stood-up cold-chain visibility application built with a hyperscaler under national distribution conditions.
$3M → $27M recurring in three yearsGlobal industrial distributor
Production AI-OCR converting unstructured field documents into a clean analytics database. Owned the full adoption motion — field-user readiness, enablement and measurement — engaged at CIO and COO level.
80%+ efficiency gain in field reconciliationSecond Fortune-500 healthcare enterprise
Extended a proven re-platforming pattern into a second enterprise: replaced intensive managed services with an owned, headless architecture.
~$8–10M TCV · managed services replacedTwo national health insurers
Delivery leadership in a heavily regulated, procurement-intensive environment, with security, legal and compliance review carried inside the plan rather than met at the end of it.
~$20M TCV · two enterprisesGlobal apparel group · two brands
Led migration of the content platform off a legacy CMS onto Adobe Experience Manager, then ported the same pattern to a second brand. Authoring, publishing velocity and site performance were the measured outcomes.
Page load ~8s → under 1sNational department-store retailer
Led the partner delivery track on an omnichannel commerce and content platform inside a 200–250-person program, aligning external vendors under matrixed reporting.
44 vendors aligned, launched on scheduleDepartment-store group · bakery-café chain
Executive workshops and design engagements: shaped the target customer experience and built the investment case ahead of budget cycles.
Funded ahead of the cycleGlobal technology manufacturer
Designed and scoped a competitive-intelligence capability monitoring pricing, catalog, inventory and content signals across the market to feed commercial decisions.
Market signals into commercial decisionsFrisco, Texas