AI Services for Wisconsin Businesses
AI consulting built around your own people and your own data. We find where AI pays, build it beside your team one working piece at a time, and hand it over so your team runs it, for businesses across Wisconsin and nationwide. Take one, take two, or take all three.
A working AI system your team runs.
Custom AI development, one workflow at a time. Most things called an AI agent should not be one. An agent decides what to do next, and that is useful when the path varies from case to case: every claim is a little different, every invoice arrives in a different format. When the path is the same every time, a plain automation runs faster, costs a fraction as much, and does not surprise you. We start every build by asking which one you actually need.
- How long
- Weeks for one workflow, built beside the people who do the work, with a working version they try before the end.
- Fee
- Quoted before we start and paid in working pieces: each step is proven on your own data before the next is invoiced, and you can stop after any step. Most builds run $25K to $150K+ depending on scope.
- What you keep
- A system your team runs without us: the code in your own accounts, the rules it learned written down, and a handover scoped as work, with documentation, monitoring, and time with your team.
In production A Wisconsin manufacturer runs our invoice tool, built beside its billing team, and every billing rule it learns is written down.
Not sure whether to build or buy? We wrote down six questions, with our verdict on each, and a table for accounts payable. Read it in our Field Notes.
Three weeks, fixed fee. Where AI pays first, with a quote.
An AI opportunity assessment of your business, not a readiness score of your organization. We sit with the people doing the work, score every candidate workflow, and come back with one named project and the reasons for the order.
- How long
- Three weeks. Short on purpose: an assessment that takes a quarter costs more than the first project it recommends.
- Fee
- $10K to $25K, fixed, agreed before we start.
- What you keep
- The scored map, the list of ideas not to build yet, and a build plan with a quote, whether or not you build with us.
Delivered A Wisconsin credit union's leaders used our map to pick where to start, and put compliance risk ahead of hours saved.
What you get, in four pieces
- A scored opportunity map. Every opportunity we found, written up in plain language with the workflow it touches, the time or cost at stake, the data it needs, and a score on six dimensions. Ranked against each other, not just listed.
- A first-build recommendation. One project named, with the reasoning shown. What it does, what it would take, roughly what it costs, and what has to be true for it to work. Specific enough to hand to any developer, including one who is not us.
- The honest no-list. The ideas that came up and should not be built yet, and the reason each one fails: data is not there, the risk is wrong, the change load falls on a team already at capacity. Knowing what to skip saves more money than knowing what to start.
- Materials for the board. The version you show your board or your executive team. Same findings, written to be read by people who were not in the interviews and do not want the technical detail.
Your outside AI partner, keeping the AI work moving.
AI strategy, advisory, and adoption, side by side with your team. Your people keep the business running while we keep the AI work moving: hands-on sessions on their real tasks, not demo data, so they learn by doing, adoption keeps its momentum, and the know-how of your long-tenured people gets written down before it walks out the door.
- How long
- Month to month, for as long as it keeps paying. It starts with hands-on workshops on your team's real tasks.
- Fee
- A set monthly amount per team, agreed up front. Anything we build for you along the way is quoted separately, piece by piece.
- What you keep
- A team that uses AI on its own work, the know-how of your long-tenured people written down, and an outside partner who knows your business.
Live A national catalog retailer's marketing team builds with us week by week; one brand lead scheduled two months of content in four hours.
What the first weeks look like
We start with the tasks your team already does and pick the two or three where AI gives back the most time. The first workshops run on those tasks, with your people at the keyboard. After that it is a rhythm: a short weekly session with the person who owns each item, something built for them to try, and another round on what they found. You stop when it stops paying. AI training for Wisconsin teams →
Not sure which fits? Most clients still start with the audit, and the first 30 minutes with Mike are free.
Book a Free CallHow a full engagement runs, start to finish
Each of the three offers also works on its own. This is the path when you take the audit and the build together, from the first look to the finished build.
- 1Sit with the work. We interview the people doing the job and the leader who can decide, on the operational side and the customer-facing or regulated side.
- 2Score and test on your data. Every candidate is scored on the six criteria below. Where something looks promising and cheap to check, we check it against your real data rather than guessing.
- 3Agree the first build. We walk your leadership team through the map together, argue about the ranking in the room, and leave with an agreed first project, scoped and quoted.
- →Decision gate. Build with us, build it yourselves, take it elsewhere, or stop. No commitment past the audit itself.
- 4Build. One workflow, weeks not quarters, with a check-in with your leader every week and a working version your team tries before the end.
The six criteria, in three pairs
The score is what makes the ranking arguable instead of a matter of taste. If you disagree with a number, you can point at which one and say why. Tap a criterion for the question behind it.
Hours it returns
Staff-time impact
How many hours a week does this give back, and to whom? Hours given back to a role you are struggling to hire for are worth more than hours given back generally.
Measurability
Will you be able to tell whether it worked? If there is no number that moves, the project cannot be defended at renewal time.
Risk it carries
Risk and compliance
What happens when it is wrong? A workflow where a mistake is caught in the next step scores very differently from one where a mistake reaches a customer or a regulator.
Change load
How much has to change for the people who do this work every day? AI projects fail on adoption more often than on technology.
Effort to build
Data readiness
Does the data this needs already exist, in a form a system can read? This is the single most common reason a good idea is not a first project.
Technical feasibility
Can this be built with what exists today, at a cost that makes sense against the hours it saves? Scored by the people who would build it.
A high impact score with a low data-readiness score is not a first project, and the map says so plainly rather than burying it.
The questions your IT team will ask, answered up front
| The question | The answer |
|---|---|
| Where does it run? | In your cloud accounts wherever practical. Your IT team owns the infrastructure, the keys, and the off switch. |
| Does our data train the model? | No. We build on commercial providers under agreements where customer content is not used to train the underlying models. |
| Are we locked into one AI vendor? | No. The model sits behind an interface and can be swapped. That is a deliberate design choice, not a happy accident. |
| Is this a new trust boundary? | Usually not. Most clients already run on the cloud and model providers involved, so the system inherits an approval that already exists rather than asking for a new one. |
| Who supports it at 3am? | Your team owns it, and we scope the handover so that is realistic: documentation, monitoring, and a named person on our side during the transition. |
| Is it just a wrapper? | The model is one component. The work is in reading your documents correctly, connecting to your systems, handling the exceptions, and proving accuracy against your data. |
The teams we build for
The work shows up by team. Industries are where the proof happened.
| Team | What we build | One proof |
|---|---|---|
| Marketing, brand and sales | Campaign production, brand voice held in code, catalog and product copy, outbound with quality control | A campaign studio for a national catalog retailer, live in production |
| Operations | Internal knowledge Q&A, meeting follow-through, process documentation, front desk and phone | A document search and consolidation tool at a Wisconsin manufacturer |
| Finance and accounting | Invoice drafting from job data, vendor invoice reading, close and reconciliation help | An AI invoice tool at a Wisconsin manufacturer, in production |
| Customer and member service | Renewal season, member replies, form-packet pre-flight, prospect meeting prep | An AI audit and build roadmap for a Wisconsin credit union |
Industries where we have worked: manufacturing, catalog retail, credit unions, insurance (a pilot), agricultural lending, and college athletics. Based in Madison, serving Wisconsin, Milwaukee, and clients nationwide.
Common questions
What does an engagement cost?
The 30-minute call is free. The AI audit is a fixed fee of $10K to $25K for three weeks. Builds are quoted from the audit and paid in working pieces, and most run $25K to $150K+ depending on scope. Accelerate is a set monthly amount per team. Every price is agreed before work starts.
Who owns what WiscAI builds?
You do, and your team runs it without us. The code, the documentation, and the accounts it runs in are yours; there is no per-seat license on custom work. The handover is scoped as work, written into the engagement rather than promised at the end.
Does WiscAI build custom AI agents?
Yes, when the work calls for one. An agent decides what to do next, which helps when every case is a little different. When the path is the same every time, a plain automation is faster and cheaper, and we will say so. Either way it is a Build: quoted up front, paid in working pieces, and run by your team.
Do we have to build with WiscAI after the audit?
No. The scored map, the list of ideas not to build yet, and the build plan with its quote are yours whether you build with us, build it yourselves, take it elsewhere, or stop there.
Can we skip the audit and go straight to a build?
Yes, when the workflow is already clear and the data is in hand. We quote the build from a short scoping conversation instead. Most clients still start with the audit, because knowing the order matters more than the first idea.
How is the audit different from an AI readiness assessment?
A readiness assessment scores your organization: data maturity, governance, skills. Useful, and not what this is. The audit scores specific workflows in your business on the hours they return, the risk they carry, and the effort to build, and it ends in one named project with a quote.
How fast do we see something working?
The audit takes three weeks. A build is scoped to one workflow and done in weeks, not quarters, with a working version your team tries before the end. Accuracy is proven on your data before the scope is final.
Who keeps it running afterwards?
Your team, and the handover is scoped so that is realistic: documentation, monitoring, and a named person on our side during the transition. If you want us close by, Accelerate keeps us on as your outside AI partner.
Start with a conversation.
30 minutes with Mike. He'll tell you honestly whether we're the right fit.
Book 30 minutes with Mike