EXPERIENCE & CONSULTING

Two Decades of Enterprise Digital.

Now Building AI Systems That Ship.

I've spent my career on the hard edge of digital transformation: global platforms, consolidated tech stacks, teams scaled from a handful of people to hundreds. That background shapes how I build AI products today. The models are the easy part. Getting them to survive contact with a real organization is the work.

From Enterprise Platforms to AI Products

Most of what I know about AI architecture I learned before I built my first production AI system. Two decades of leading digital transformation, marketing technology consolidation, and CRM strategy across global enterprises and venture-backed companies teaches you a particular lesson: technology doesn't fail because the code is wrong. It fails because nobody mapped the constraints, nobody designed for the messy middle, and nobody built the judgment layer that decides what gets automated versus what needs a human in the loop.


That pattern recognition is what I bring to AI now. CleanSmart coordinates five models across hundreds of thousands of records because I've seen what happens when you skip the validation layer. SignalHive works because I've learned, the hard way, where confidence scoring matters and where it's theater. The InsightStack architecture that organizes my product portfolio wasn't designed up front. It emerged from solving the same kinds of problems, at different scales, over and over.

AI can execute. It cannot decide. The enterprises that will win with AI are the ones with the best judgment about where that line sits.

That's the work I do now. Building production systems when the judgment calls are mine to make. Advising teams when they're theirs.

Career Timeline

Where the Judgment Came From

2024–Present
CleanSmartLabs & Bottom Line Strategy Group
Founder / Digital Strategy & Transformation Consultant

AI Products in Production, Consulting at the Executive Layer

The question: What does an AI innovation lab look like when the founder ships the code and the strategy?

Running CleanSmartLabs as a working AI product studio. Shipped CleanSmart (data quality SaaS with semantic matching and anomaly detection), SignalHive (community intelligence at scale), and the ICP Intelligence Engine. In parallel, advise enterprise clients on AI integration, digital product strategy, and technology adoption where the judgment calls matter more than the tooling.

Multiple AI Products Shipped, Not Prototyped Executive Advisory
Jan 2023–May 2024
Novartis
Executive Director, Web Experience & Strategy, International

Global Web Platform, 90 Countries

The question: How do you consolidate 1,200 legacy websites across 90 countries without breaking the local businesses that depend on them?

Led the international web strategy and platform consolidation. Built a unified architecture that gave 90 country markets the customization they needed without forking the core platform. Retired 900 of 1,200 legacy sites and cut operating costs by 52%. Brought legal, regulatory, compliance, medical affairs, and patient services into the process from day one, which prevented the late-stage surprises that usually derail programs of this scale.

90 Countries 52% Cost Reduction 1,200 Sites Assessed
2014–2022
BestReviews, CT3 Education, Formative
VP-level Roles: SEO & Email, Digital Marketing, CRM & Marketing Automation

Growth-Stage Operating Leadership

The question: What does it take to turn a marketing function into a revenue engine at a company that's scaling fast?

A run of VP roles across media, ed-tech, and SaaS. Built the CRM and marketing automation practice at Formative from zero to $3.1M in revenue. At CT3, led the tech ecosystem overhaul that cut operating costs 27% and drove 22% lead growth. At BestReviews, took the email program from nothing to a multi-million-dollar revenue stream across a 500,000-contact database, and grew organic traffic revenue 28% in eight months. Different companies, same throughline: turn the messy parts of a growth-stage tech stack into something that compounds.

3 VP Roles $3.1M Built From Zero 27% Cost Reduction
2002–2014
Razorfish, Beamm, Affinity Answers
SVP/GM, Global Performance Marketing → VP, Brands & Agencies → VP, Product Marketing

Global Agency Leadership and Early-Stage Go-to-Market

The question: What does it look like to build a practice from nothing, at the scale of a global agency and a venture-backed startup?

Twelve years across the agency and startup sides of the business. At Razorfish, built and ran the global performance marketing division, growing it from $24M to $50M and leading a team of 200+ across search, analytics, CRM, and BI. Took the SEO practice from $1M to $13M in two and a half years. On the startup side, led go-to-market for a venture-backed SaaS analytics platform (Pepsi, Xfinity, 41% revenue growth in year one) and a digital payments product that returned 11X to investors. Two different vantage points on the same question: how do you build something that scales?

$24M → $50M 200+ Team 11X Investor Return
HOW WE WORK TOGETHER

Engagement Models

AI Architecture Review

2–4 weeks


I audit your AI stack, identify capability gaps, and deliver an architecture roadmap aligned to your constraints.


Includes:
Stack assessment
Capability gap analysis
Architecture roadmap
Priority recommendations

System Design & Build

1–3 months


I design and build production AI systems end-to-end — from capability selection through deployment and monitoring.


Includes:
Architecture design
Model selection & orchestration
Confidence scoring design
Production deployment

Advisory Retainer

Ongoing


Ongoing access to AI architecture judgment for teams building or scaling AI systems across their organization.


Includes:
Weekly architecture calls
Design review
Team upskilling
Vendor assessment support

Let's Talk About Your AI Architecture

Whether you're starting your first AI initiative or trying to get an existing one to production, I can help you make the judgment calls that matter.