Services

AI & Data Readiness Snapshot and Assessment

For CEOs and leadership teams · Snapshot: 3–4 weeks · Full Assessment: 8–12 weeks

You know AI matters, your data is spread across a stack of subscriptions, and you're not sure where to start. I map what you have today, every system, what data it holds, how that data moves or doesn't, and what it costs you, then lay out a plan across the four layers with phases, rough costs, and quick wins.

The Snapshot is built for owner-led companies that want a clear plan fast. The full Assessment covers the whole company, including a complete controls assessment, and ends with a future-state design and a presentation to your leadership team or board.

The real story: for a publicly traded investment firm, we spent three months on the full Assessment, delivered with our data-engineering partner. I led the process and controls work: mapping every accounting process with the people who run it, assessing each control, and designing the controls and evidence for the future state. Together we designed a governed data foundation, a reporting layer, and an intelligence layer where Claude reads approved, reconciled data.

AI Prototype Sprint

For CEOs who want to see AI work on a real problem · Typically eight weekly sessions

One real problem, your own data, and a working tool your team uses in week-to-week decisions. We start from the spreadsheets and exports you already have, so there's no new system to buy before you begin. Every week we meet with you and the people who do the work, check the tool before each walkthrough, and widen it as the team starts relying on it.

Every number in the tool shows what it was calculated from, and every assumption has a named owner on your team. Your people keep the decisions. The tool shows them the options and the trade-offs. At the end you have something your team uses and a clear path to a full application.

The real story: a custom door manufacturer and I built a production planning tool from its work orders, truck calendars, routing by door type, staffing, and three months of history. It has three views: the monthly plan the planners work from, refreshed every week; a scenario console to test a plan before committing, such as someone out for a week, added overtime, or one more person at a station, and where an extra hour pays off most; and a closed-month view comparing the plan with what the trucks actually carried. It decides which work orders to build for which truck based on the hours left at each production stage, while the planners still own the truck dates. As the team used it, the horizon grew from one month to the full quarter, and the sprint led to a second engagement to turn it into a full multi-user application.

Own Your Data: SaaS Consolidation and Data Foundation

For companies paying for several systems that don't share data well · Phased build

Most growing companies collect subscriptions: one for accounting, one for the warehouse, one for the marketplaces, one for planning. Each vendor holds a piece of your data, and every renewal costs more. I build one data foundation you own, then replace subscriptions one at a time with a platform designed around how your business works. Nothing goes live until it has been proven against the old systems.

The real story: a specialty retailer replaced NetSuite, Rithum, NetStock, OZ WMS, and its point-of-sale subscription with one platform it owns, after running it side by side with NetSuite for three monthly closes.

AI Finance Operations

For CFOs and controllers · Built in phases, or one piece at a time

Books that update as transactions happen. A month-end close measured in days instead of weeks. An AI assistant that reads vendor invoices, enters them, and matches them to purchase orders and receipts, and never approves or pays a bill. A morning outlook for the CEO with current sales, margin, and a forecast for the month. Every piece is built with the controls an auditor expects to see.

The real story: the same retailer now posts sales, inventory, and bank activity automatically and closes the month in one day.

Fraud, Risk & AI Controls Review

For CISOs, risk managers, and CFOs · Fixed-scope review

Where are you exposed to fraud, account takeover, and weak access or change controls, and what should be in place before AI touches your money, customers, or operations? I review your current controls and give you findings, priorities, and a practical roadmap.

The real story: at Shutterstock, I built the fraud and cybersecurity team from the ground up, rolled out access and change management controls across 82 engineering teams that internal and external audit both endorsed, cut account takeover by 99%, and cut fraud exposure by 98%.