From ERP exports to a governed warehouse
the manufacturer runs itself.
The client is a mid-size manufacturer. Production, quality, and scheduling data lived in the ERP and in exports of the ERP. We built the governed warehouse and the reporting on top of it, on the client's own servers, for one fixed price quoted before the work began, and handed it to the client's team to run.
The situation
Like most plants its size, the ERP held the production and inventory record, and almost everything the leadership team looked at was a manual export of it: a spreadsheet pulled on Monday, out of date by Tuesday, and calculated slightly differently by whoever pulled it.
The team did not have a reporting problem so much as a connection problem. The numbers existed. They were not in one place, not defined the same way twice, and not available without a capable person spending hours a week producing them. The owners wanted that fixed in a way their own staff could run, and wanted to do it without handing an outside firm the keys to their systems.
What we built
We started with the layer most vendors skip. Before a single dashboard, we built a governed warehouse that pulls from the ERP and the quality and safety system automatically, every night, and checks what arrived before anyone sees it. A load that fails a check stops there rather than landing in a report.
On top of that sits one set of definitions. On-time delivery, scrap, job cost: each is defined once, in the warehouse, and every dashboard reads the same definition. When two people pull the same number, they get the same number.
Then the dashboards, generated from the model rather than clicked together, so a change to a definition flows through every report at once. And documentation and training, so the client's team maintains the pipeline and builds its own reports without calling us.
How it stays inside the client's environment
Everything runs on the client's servers. The client provisions whatever access Solomon uses and can revoke it at any time. Nothing in the design requires the client's data to leave its environment, and nothing requires Solomon's involvement to keep running.
We mention this because it is the question every manufacturer asks first, and it should be. The right answer is a design the client controls, not a promise.
How it landed
The project was quoted as one fixed price before any work began and delivered in stages, so the client could see progress and test as it went. The client's team tested each dashboard against the numbers they already knew, the definitions held, and the reporting went live on the client's own servers with the client's own staff running it.
The Monday spreadsheet is gone. The loads run every night, the checks catch what used to be caught by hand, and the leadership team reads one set of numbers.
The follow-on phase is already scoped: letting people ask questions of the same governed data in plain language. Because the definitions already live in the warehouse, that phase builds on what exists rather than starting over.
What a manufacturer can take from this
If your plant runs on ERP exports, the first project is not an AI project. It is the staging layer and the metric definitions. Once those exist, the dashboards are quick and the AI use cases stop being hypothetical. Our AI Readiness Assessment is the three-week version of the question this client asked us first: what would it take for the numbers to be trusted?