The part nobody demos
Most AI projects in manufacturing do not fail on the AI. They fail because the data was in nine places, three formats, and one person's head. We do the unglamorous part first, because everything you want to build sits on top of it.
Not a data warehouse project. Weeks, on the systems you already run.
The gap
There is a difference, and it changes what the fix looks like.
The ERP has part of it. Scheduling is a spreadsheet. Quoting is a file on the estimator's PC. Quality is on paper. Every one of them is right about something and none of them agree.
Silo inefficiencies eat 20 to 30% of revenue
One person knows that customer 4402 always ships early, that the code in that field means something different since 2019, and which numbers to trust. None of that is written down anywhere.
Knowledge that walks out at retirement
A human can look at four screens and reconcile them. No tool can, which is why every AI demo you have seen assumed a clean table that does not exist in your building.
Every tool you try hits the same wall
What we do
Four steps, in weeks, on the systems you already run.
Every system, spreadsheet, shared folder, and local file that holds something the business depends on. Including the ones nobody mentions in the first meeting.
In practice
You get a map of where your data hides and where it dies. Several customers have told us this map alone was worth the engagement, because it showed them which processes were actually broken.
We read from the ERP through its supported interface, pick up the spreadsheets where they already land, and bring it together. No migration, no new system of record.
In practice
Nobody changes how they work on day one. Asking everyone to change their process before the value shows up is the fastest way to have something nobody feeds.
The reason three departments have three backlog figures is three definitions, not three tools. We settle that in writing, with your people, before building on top of it.
In practice
This is also where the knowledge in somebody's head gets captured. Which codes mean what, which records to trust, what the exceptions are. It becomes documentation instead of a retirement risk.
A one-time cleanup rots in a month. Whatever we build refreshes on a schedule you set, so the data stays trustworthy without anyone maintaining it.
In practice
This is the difference between a data project and a data foundation. One is a report somebody made once. The other is something you can keep building on for years.
Not sure which of these matters most for your company? That is what the first call is for.
Under the hood
Everything you actually want is downstream of it.
Week 1
you get the map of where your data hides and where it dies
2 to 4 weeks
to connected data plus something visible built on it
Every project after
is cheaper, because the hard part is done once
Systems
We build this on any system we can read. These are the ones we work in most.
Questions
Almost never, at your size. Warehouse projects are long, expensive, and usually solve a problem larger companies have. What most manufacturers actually need is their existing systems connected and their definitions agreed, which is weeks rather than quarters. If you genuinely need a warehouse we will tell you, but we start by assuming you do not.
It changes the sequence, not the answer. Where data is actually wrong rather than just spread out, we find that in week one and you get a clear picture of what is broken and what it would take. Often the fix is a process change rather than software, and we will say so.
No, and please do not. We ingest them where they already land, on purpose. Those spreadsheets exist because the ERP could not do something, and the knowledge in them is real. Over time some of them stop being necessary, but that should happen on its own rather than by decree.
You can try, and it is where most manufacturing AI pilots die. An assistant is only as good as what it can reach. If the honest answer is that your data needs a month of work first, we would rather tell you that than sell you a demo that impresses the room and gets abandoned by spring.
Connected, current data running in your own accounts, a written definition of what each number means, a map of where everything lives, and something visible built on top of it so people can see it working. All documented, all yours.
Let's talk
Thirty minutes. You walk us through the systems, the spreadsheets, and the files nobody talks about. We tell you honestly what shape it is in and what it would take to make it usable.
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