About ClearForge
We build production AI. And stay until it sticks.
The same senior team diagnoses the workflow, engineers the system, ships it to production — and runs the adoption until your people work in it every week.
The Founder
James Penz
Before ClearForge, James spent over a decade in management consulting and enterprise technology — at Bain & Company, EY, and Capgemini — advising mid-market and Fortune 500 companies on operations, AI strategy, and large-scale delivery.
Across those years he kept watching the same failure: companies spend millions on AI strategy that never survives contact with the people who have to use it. The gap was never insight. It was execution — and adoption. So he built the firm he could not find in the market: senior enough to scope the problem honestly, technical enough to ship working systems, and stubborn enough to stay through The Adoption Mile™ until the team runs it without us.
Based in Southeast Michigan. Serving clients nationally.
Bain & Company
Strategy & AI practice
EY
Enterprise delivery
Capgemini
Technology at scale
The Operating Belief
Shipping is half the job. Adoption is the other half.
Most AI firms sell a roadmap and leave. Some build something and create a dependency you cannot operate without. We do neither. Every ClearForge engagement ends with a working system in production, a named operator on your team, and a weekly adoption rhythm we run together until usage holds.
70%
Weekly-active usage — the adoption bar we build to by day 90
1 owner
Named on your team before we write a line of code
100%
You own everything we build — code, docs, runbooks
Principles
What we believe shapes every engagement.
Strategy must end in execution
Every engagement produces a working system, not a report. If we cannot build it, we do not recommend it.
Senior-led, end to end
The person who scopes your engagement is the person who delivers it — and can make tradeoffs in the room.
Adoption is the deliverable
A system nobody uses is a write-off. We put a named operator, a weekly cadence, and a visible scoreboard on every launch.
Build capability, not dependency
Everything we build transfers. We train your people, document the systems, and make ourselves replaceable. That is the goal.
Honest Answer
Why not just buy a platform?
Platforms require a data science team
DataRobot and Dataiku can help if you already have a team to build, validate, and maintain models. Most mid-market companies do not.
Platforms solve the tool problem, not the business problem
Buying a platform is like buying a CNC machine without a machinist. The tool is only as good as the people operating it and the process around it.
We build AND run the adoption
We deploy production AI, train your team, and stay on a weekly cadence until usage holds. When we leave, the system works and your people own it. No ongoing license dependency.
One conversation to find out.
Bring one stuck workflow. We will be honest about whether it is worth building — and if so, exactly how.