Production AI Blueprint · Enablement for mid-market operators
Most mid-market operators have people experimenting with AI and nobody who owns it. The Production AI Blueprint is a fixed-fee engagement that sorts out the data, the governance, the controls, and who runs it — then sequences the two or three use cases actually worth doing first.
30+ years across energy, hospitality & travel, financial services, manufacturing, retail, and healthcare · TOGAF® 9 Certified · CTOx® Functional Technology® Framework
The gap we fill
Strategy firms sell an AI readiness deck and leave. Tool vendors ship a pilot with no governance behind it, and it dies the first time finance or legal looks at it. What almost nobody sells is the middle — systems that reach production and are built to stay there.
Bad pricing data, broken integrations, and inventory that doesn't match across channels. The symptoms show up in conversion, not in a server log — which is why nobody catches them.
Everyone has an AI strategy. Very few have agents running in production against real data with governance around them. The distance between those two is where budgets disappear.
One contractor holds the credentials. One legacy platform holds the business. No one has mapped what happens if either disappears — and the board is starting to ask.
The product
Every stalled AI effort fails on one of four things. The Blueprint assesses all four at once and sequences the work against them.
Where it actually lives, how clean it is, and what has to be true before a model can be trusted with it. Most “AI problems” are data problems wearing a costume.
Who decides what gets built, how use cases get prioritized and funded, which vendors and models are allowed, and what happens when someone buys a tool on a credit card.
Where a human has to sign off, what gets logged, and how you prove after the fact what the system did and why. This is the part that lets a CFO say yes.
Who runs it on Monday morning. What to hire, what to borrow, what to leave with the vendor, and how your team learns to stop depending on me.
Verticals
A three-week blueprint only works if the person writing it doesn't need six months of onboarding. These are the sectors where I've run the systems, not just read about them.
Channel and PMS ecosystems, dynamic pricing, distribution integrity, guest data platforms.
Downstream operations, refining and logistics analytics, application portfolio rationalization.
Packaging, paper, and industrial manufacturers — enterprise architecture and application portfolio rationalization across plants and acquired businesses.
Pricing platforms, MLOps, real-time analytics, and governance-heavy delivery environments.
Retail data models, customer and loyalty data, omnichannel integration, M&A systems merges.
Enterprise architecture governance, data platform strategy, and modernization under compliance.
Selected work
A private-club and vacation-rental operator was running a legacy platform with no in-house technology leadership. Pricing data had degraded to the point that it was actively suppressing conversion, and nobody owned the vendor stack.
Built a modern data lakehouse to restore pricing and data integrity, then designed and deployed pricing, data-quality, and conversion agents on AWS Bedrock — running in production, not in a pilot.
Channel and PMS integrations cleaned up across three platforms, the vendor portfolio rationalized, and key-person and access-custody concentrations de-risked.
How it works
Three steps, each one worth buying on its own and each the obvious next step from the last. Nobody is asked to sign a monthly agreement before there is anything to run.
Three weeks focused on a single function, or five weeks enterprise-wide. Data readiness, governance model, control framework, operating model, and a sequenced twelve-month roadmap with a cost envelope. The fee is credited against a Sprint booked within 60 days.
One use case off the roadmap and into production in 90 days — with the controls, the audit trail, and an internal owner trained to run it. I architect and oversee; your team or your vendor builds.
Ongoing, and only if the roadmap needs an owner. I chair the governance forum, sequence the work, oversee vendors, and coach the person who will eventually do this without me.
Insights
Short, sourced pieces on the decisions mid-market operators are actually facing. Every claim is cited — and where a widely repeated statistic doesn't survive scrutiny, I say so.
AI is being paid for out of existing IT budgets, not net-new money. That changes what a rationalization program is for.
Deploying AI onto a weak data foundation doesn't produce a smaller benefit. It can produce a negative one.
Google tested 117 objective metrics against engineer-reported debt. None of them predicted it. What to measure instead.
Start with a 30-minute call. If there's a fit, the Blueprint gives you a sequenced roadmap in three weeks — not a discovery phase that runs all quarter.