AI & Data Practice

Human in the loop.
AI in the human loop.

The loop is your business. We integrate AI inside it, equipping your experts to make high-value decisions faster.

THE FIRST QUESTIONS WE HELP YOU ANSWER
DATA FOUNDATION
6 SOURCES · SCANNED
DATA READINESS · WEIGHTED
62/ 100below the build bar
ERP
OK
MES
OK
PI
GAP
CMMS
OK
LIMS
GAP
CRM
GAP
READINESS GAPS3 BLOCKING
Customer master — 3 systems disagreeOPEN
CRM, ERP, billing hold different IDs · uniqueness
Downtime events — no lineageOPEN
PI historian · no traceable source · accuracy
Asset register — 12% of fields emptyOPEN
CMMS · completeness gap on critical assets
RECOMMENDED FIX
Consolidate the customer master to one authoritative record before the model — three lists reconcile to one, and the features stop contradicting each other.
closes the loop
WHAT WE WORK IN
AI & Machine LearningGenerative AI & AgentsData EngineeringData Lakes & WarehousesAnalytics & BIAutomationSystems IntegrationIT/OT ConvergenceSaaSApplication DevelopmentCloud & MLOpsAPIs & MicroservicesAI & Machine LearningGenerative AI & AgentsData EngineeringData Lakes & WarehousesAnalytics & BIAutomationSystems IntegrationIT/OT ConvergenceSaaSApplication DevelopmentCloud & MLOpsAPIs & Microservices
WE'VE DONE THIS IN
ManufacturingLogisticsUtilitiesIndustrialBankingInvestment BankingFintechHi-TechSoftwareRetailManufacturingLogisticsUtilitiesIndustrialBankingInvestment BankingFintechHi-TechSoftwareRetail
01 / What Has To Go Right

Four things decide whether AI pays.

A strong model is a small part of a working program. The rest is ordinary operating work — it's where we spend most of our time, and we take responsibility for all four as one job.

01
A value case finance backs

Forty ideas become the three worth funding — each tied to a number the CFO recognizes and a person who wants the result.

02
Data the work can stand on

Definitions agree, systems reconcile, and the integration work is scoped before the build starts, so month four holds no surprises.

03
Adoption built in

The output lands inside the tools your team already opens every morning, and the workflow changes with it — so the work becomes part of the job.

04
A capability you keep

Your people run more of each delivery, until the next use case gets built without calling anyone.

02 / What You're Building

You're building two things at the same time.

The program is what your board sees paying off. The office is what makes the next win cheaper than the last. We build them together from day one — the wins fund the capability, and the capability keeps the wins coming.

THE PROGRAM

The work that pays.

The demand forecast, the service copilot, the fraud model — live in production, used every day, with value finance has signed.

THE OFFICE

The team that keeps delivering.

The people, the platform, and the governance that turn the first win into a steady pipeline — and, in time, run it all themselves.

03 / The 24-Month Rhythm

How a capability comes together.

01
MONTHS 1–3
Discovery & Strategy

We learn the business, take an honest look at the data, design the office, and agree on what to build first.

02
MONTHS 2–9
Foundations

Just enough platform to serve the first use cases. We go after the ugliest data problem right away, because it always takes longer than anyone expects.

03
MONTHS 3–9
Lighthouse Delivery

Quick wins and a flagship or two go live, get used, and produce a value number finance actually agrees with.

04
MONTHS 9–24+
Scale & Sustain

Proven work rolls out across the business, and the office starts paying for itself. By now it runs without us.

04 / The Operating Model

A strong center, with people out where the work happens.

The center holds the platform, the standards, the governance, and the specialists who are hard to find. Everyone else embeds in the business units, close enough to the day-to-day to make the work land. And every delivery team has someone who genuinely knows the business — we don't bend on that one.

See the full operating model
DATA & PLATFORM

Architecture, pipelines, and the master data everything else depends on.

DATA SCIENCE & ML

The scarce specialists, kept central so their work carries further.

PLATFORM & MLOPS

Getting models into production and watching them once they're there.

GOVERNANCE

Responsible AI, model risk, and the value tracking that keeps funding flowing.

05 / Deciding What To Do

A mix that pays early and keeps paying.

We start with the decision that needs to improve, not the tool. Every candidate gets scored on how much it's worth and how feasible it really is — and feasibility includes the question everyone underrates, which is whether anyone will actually use it. Then we pick a deliberate mix.

Quick Wins

Doable, decent payoff. We ship a few early to build momentum and earn the right to ask for more.

Lighthouses

Big payoff, harder to pull off. One to three of these are what the whole office is really for.

Big Bets

High value but heavily regulated or data-hard. Worth doing later, once the foundations can carry them.

Fill-ins

Easy but modest. We pick these up whenever there's spare capacity to do them well.

“A brilliant model that nobody uses creates nothing. A decent one that everybody uses can be worth a fortune.”

SOMETHING WE SAY A LOT

06 / From The Practice

Things we've written down.

07 / Experience

Building a strong American Industry.

That's the mission behind the practice. Our team has spent careers doing this work inside some of the largest operations in the country.

MotorolaDuke EnergyBPVerizonUPSShutterflyChewyMotorolaDuke EnergyBPVerizonUPSShutterflyChewy

PLUS ENTERPRISE EXPERIENCE ACROSS FORTUNE 500 INDUSTRIAL, FINANCIAL SERVICES, AND TECHNOLOGY COMPANIES.

Let's talk about where value is hiding in your business.

A discovery call is the easiest place to start. No pitch deck — just an honest conversation about what you're trying to do.

Book a discovery call