Mid-Market AI Blueprint
A 6–12 week engagement. $25,000. A prioritized AI roadmap built around the work you actually do.
You don’t have the budget of an enterprise. You don’t have a Chief AI Officer or a team of developers running parallel experiments. What you have is a business to run, a team that’s curious about AI, and a growing sense that you’re either going to figure this out on your terms — or watch a competitor figure it out first.
The Mid-Market AI Blueprint is a fixed-fee engagement that gets you to a clear, prioritized plan in six to twelve weeks. We assess a handful of the business processes you already know are bottlenecks, examine the data estate that everything else depends on, and hand you back a roadmap with short-term wins you can act on immediately and a longer-term path that keeps you moving.
If you’re asking yourself any of these questions, this engagement is for you
“We know AI is important, but where do we even start?”
“We’ve had a couple of false starts with AI. What did we miss?”
“We’re using AI in pockets, but is any of it actually delivering value?”
“Our data is a mess. Can AI even work here yet?”
“There are a hundred AI tools and vendors pitching us. Which ones matter for our business?”
If two or three of those sound like a Tuesday morning conversation in your office, keep reading.
What’s actually happening with AI in mid-market businesses
We’ve been in the room with a lot of organizations over the past year. Here’s what it usually looks like.
Adoption is uneven and unmanaged.
Some of your people are power users — drafting, summarizing, building little agents on the side. Others have never opened Copilot. There’s no shared baseline, no shared vocabulary, and no coordinated push. It isn’t really “adoption.” It’s a handful of motivated individuals making it work in spite of the org chart.
IT turned the tools on. Nobody told the business what to do with them.
Licenses are paid for. Copilot is enabled. And most employees still don’t know what they should be using it for in their actual job. Enablement sessions help for a week, then everyone goes back to their inbox.
There’s no cohesive movement.
One department is building a chatbot. Another is doing a data cleanup project. Marketing is generating content. Finance is dabbling in forecasts. Each piece may be fine on its own, but nothing rolls up to a strategy, and nothing compounds.
The “where to start” problem is real.
You see what enterprises are doing on LinkedIn — chief AI officers, agent platforms, governance councils — and it’s intimidating because the playbook isn’t built for you. You can’t dive in headfirst. You can’t run twenty parallel pilots. You need to put a couple of feet in the water, prove value, and earn the next investment.
You feel the pressure to move the needle.
Boards are asking. Customers are asking. Younger employees are asking. Doing nothing is no longer a neutral choice.
This is the gap the Mid-Market AI Blueprint is built to close.
How the Blueprint addresses what you’re up against
The “where do I start” paralysis. You don’t need a five-year transformation plan. You need a short, ranked list of moves that pay off fast. We give you that list, with the rationale behind it.
False starts and pilot fatigue. Most failed AI pilots fail for one of two reasons: the process wasn’t the right fit, or the data underneath couldn’t support it. We pressure-test both before you spend on implementation.
Disjointed adoption. A roadmap gives leadership, IT, and the business teams something to align around. It replaces “everyone’s doing their own thing” with a shared sequence of bets.
Unknown data readiness. You can’t run AI on a data estate held together with spreadsheets and tribal knowledge. We tell you exactly where you stand and what to fix first.
What we actually do in the engagement
The Blueprint runs in three parallel tracks, then converges into a single roadmap.
1. AI in Action: The Art of the Possible
Working sessions with your leadership and operating teams to demystify what current AI can and can’t do, and to align on what “valuable” looks like for your business. This is not a vendor demo reel. It’s a calibration exercise so the rest of the engagement targets outcomes you actually care about.
2. Business Process Review (3–5 key processes)
You already know where the bottlenecks are. Where the work piles up. Where the same person re-keys the same information into the same three systems every week. We sit with the people doing that work, document the real flow (not the org chart version), and identify where AI — or intelligent automation, or sometimes just a better-designed step — can take time, errors, or cost out of the process. Each opportunity is sized and scored on ROI and effort so the priorities are obvious.
3. AI-Ready Data Estate Assessment
In the age of AI, your data is the new gold. The catch: most data estates were built for human reporting, not for AI consumption. We evaluate your sources, integrations, BI/reporting layer, governance, and quality against what AI tools actually need to be useful. You leave knowing what’s ready, what’s blocking you, and what to fix first.
Convergence: The Roadmap
The three tracks become one prioritized plan that sequences data fixes alongside process pilots so the two reinforce each other instead of competing for budget.
What you walk away with
- A prioritized AI opportunity backlog, scored by ROI, effort, and data readiness — so the next decision is obvious.
- Short-term wins you can start within weeks of the engagement closing.
- A longer-term path for how to keep moving as your data estate matures and your team’s capability grows.
- A clear-eyed view of your data estate — what’s AI-ready, what isn’t, and what to do about it.
- Alignment across leadership, IT, and the business on where AI delivers real value, and just as importantly, where it won’t.
- Confidence to spend. When you do invest in implementation, you’ll know why, where, and what return to expect.
How it works — the engagement at a glance
| Phase | What happens | Typical duration |
| Kickoff & alignment | Confirm scope, identify the 3–5 processes, schedule stakeholder sessions | Week 1 |
| Art of the Possible | Education and calibration sessions with leadership and process owners | Weeks 1–3 |
| Process discovery | Working sessions with the teams doing the work; opportunity identification | Weeks 2–6 |
| Data estate assessment | Source, integration, BI, governance, and quality review | Weeks 2–8 |
| Roadmap synthesis | Prioritization, sequencing, ROI scoring, written deliverable | Weeks 6–10 |
| Executive readout | Roadmap presentation, Q&A, decision on next phase | Weeks 10–12 |
Total engagement: 6–12 weeks. Fixed fee: $25,000.
What we ask of you: access to a small set of process owners, an executive sponsor, and your existing data and BI documentation. That’s it.
How this is different from what else is on the market
You’re going to see other “AI strategy” packages. Some come from the giant consultancies — long, heavy, expensive, and built for organizations five times your size. Some come from product partners pushing a single vendor’s stack with a discount attached. Both have their place. Neither is built for the way mid-market businesses actually buy and operate.
Versus enterprise consultancies: Faster, fixed price, no thousand-page deliverable. You get a working plan, not a binder.
Versus single-use-case discovery offerings: We look at three to five processes and your full data estate in parallel. One use case in isolation rarely tells you whether the next ten will work.
Versus DIY: You can absolutely run this internally — if you have the time, the AI fluency, the process discipline, and the data expertise on staff. Most mid-market teams don’t, and the cost of a wrong first bet usually exceeds the cost of this engagement.
Why Weidenhammer
We’ve spent 48 years building software, modernizing data, and standing up the Microsoft stack — Business Central, M365, Azure, Power Platform, Fabric, Copilot — for mid-market businesses. We’re big enough to bring real depth, and we’re not the 800-pound gorilla that treats you like account #4,328. Your engagement is run by people whose names you’ll know, who will actually be in the room, and who care whether the roadmap gets used after we hand it over.
We also live in your reality. We work with mid-market organizations every day. We know what a $25,000 decision feels like in your business, and we build the engagement to earn that investment back many times over in the first wave of work that follows.
Optional add-ons
Some clients extend the Blueprint with one or both of the following:
Cloud & Infrastructure AI Readiness Spark Assessment ($10,000–$15,000). A focused review of your cloud, security, and governance posture so you can safely activate Copilot and downstream AI tooling. Deliverable: a Cloud & Infrastructure AI Readiness Roadmap.
Virtual Chief AI Officer (vCAIO) ($2,500–$5,000 per week). Ongoing strategic consulting after the Blueprint — adoption oversight, governance and policy support, vendor evaluation, and progress accountability. For organizations that want a senior AI voice without hiring one full-time.
Frequently Asked Questions
How long does the Mid-Market AI Blueprint take?
Six to twelve weeks, depending on scheduling and the complexity of the processes and data sources we review. Most engagements land between eight and ten.
How much does it cost?
$25,000, fixed fee. No hourly billing surprises. Optional add-ons (cloud readiness, vCAIO) are priced separately and called out above.
How many processes do you assess?
Three to five core business processes — typically the ones you already know are bottlenecks. We’ve seen clients want as many as ten; we’ll tell you honestly which ones belong in this engagement and which are better tackled later.
Do we need to have our data in good shape before we start?
No. Part of what you get is a clear-eyed read on the state of your data estate and what to fix first. If your data were already AI-ready, you probably wouldn’t need this.
Will this lock us into a specific AI vendor or platform?
No. We work primarily across the Microsoft stack because that’s where most of our mid-market clients already live, but the roadmap is built around your processes and your data — not around selling you a particular tool.
What happens after the Blueprint?
You decide. Some clients take the roadmap and execute internally. Some bring us back for the first wave of implementation. Some engage our vCAIO service to keep momentum. The deliverable is yours either way.
Who should be involved on our side?
An executive sponsor, three to five process owners, and someone from IT or data who can speak to your current systems. Total time commitment is usually 15–25 hours across the engagement, spread over the 6–12 weeks.
Is this a fit if we’ve already started with AI?
Often, yes — especially if you’ve had false starts or stalled pilots. The Blueprint is just as useful for resetting direction as it is for starting from zero.
Ready to put a stake in the ground?
You don’t have to commit to a multi-year AI program to start moving. You have to commit to six to twelve weeks of focused work and $25,000 to know exactly where to put your next dollar.