What I Do

When you need traction

Growth Strategy

You've got a product, a goal, or a market opening up, and no clear path from here to revenue. Finding that path is the job. I start in the data (what's happening) and then in real conversations with your customers (why it's happening), because a spreadsheet has never once told anyone the whole truth. From there come the calls that decide whether an idea catches on or gets ignored: how to position it, where to compete, what to build first, and in what order.

I've made those calls at the scale of getting a single product to market, and at the scale of a customer base that grew 328% in a year.

You walk away withA clear plan for how to position it and roll it out, grounded in your data and your customers' own words, sharp enough to start building on Monday.

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When the business has to go digital

Digital Channel Development

Your revenue still runs on phone calls and good relationships, and everyone quietly knows that ceiling is real. I take businesses online for the first time, and I don't stop at the storefront: sign-up, credit and payments, insurance paperwork, and the behind-the-scenes connections that make a real sale possible. Then the part most launches skip: watch where customers get stuck, clear the way, improve it, until the experience is genuinely good.

That's how I built the online rental business at a Nasdaq-listed construction technology company: from a January 2024 launch to $12M+ a year across 400+ branches within two years, through the company going public, with customer accounts up 328% and driving 80% of online orders.

You walk away withA working online business, the systems behind it, and a customer list you actually own.

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When AI has to deliver

Applied AI

You know AI should be doing real work in your business, and so far everything you've been shown is a demo with great lighting. I drive machine learning that launches and keeps working, same discipline as everything else: fix the process first, point AI at what's left, then keep improving it against real use until it holds up when real people lean on it.

At the same company: an image-recognition system (built on Amazon Rekognition, trained on 1 to 2 million photos) that grew an online catalog from 5,000 items to 100,000, and a model that read live data off the machines to flag one about to break down before it did.

The future I build toward: AI makes it affordable to create software shaped to how a business actually works, instead of bending the business to fit some off-the-shelf product. I've written about why →

You walk away withA real, working system measured in results, not a demo that dies in a slide deck.

How an applied AI engagement works →

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