In the Mittelstand the data has long been there: in the ERP, in the CRM, in machine controls, in Excel lists on network drives. What is missing is access, reliable, consolidated, in the quality that analysis and AI need. That is exactly what we build: the data foundation on which the first use case stands in weeks, not years.
No platform for the platform's sake. Every step pays into a concrete analysis or a concrete AI use case.
ERP, CRM, machines, Excel: we connect the sources into a platform that is current every day, without replacing your systems.
Duplicates, gaps, contradictory master data: we make them visible, settle responsibilities and keep the quality permanently, not once.
Analyses, forecasts, AI models: whoever needs access gets it, department, management, agent. Traceable, with permissions that fit your obligations.
Data rarely looks the way you would wish. This is how a grown customer list becomes a stock that analysis and AI can work with.
What happens here: Duplicates merged, formats unified, missing fields completed from other systems, and every record with source and owner.
| customer | city | revenue | owner |
|---|---|---|---|
| Miller Ltd | munich | 12.500,00 | — |
| MILLER LTD. | Munich | 12500 | K.S. |
| Acme Corp | ?? | n/a | — |
| acme corp | Berlin | 8.900 € | — |
| Hill & Sons | BERLIN | 15 200 | Sales |
01
At the end you haveThe data map of your company, with quality, gaps and the first use case that pays off.
Which systems hold which data, who maintains it, where does the flow break? Within a few weeks a map of your data emerges, honest, including the spots where it gets stuck.
02
At the end there runsThe platform with daily current, verified data, on your infrastructure or in the cloud of your choice.
Platform, data flows, permissions and rules. As lean as the first use case needs, as solid that the next ones build on it without starting over.
03
At the end there worksThe first use case in daily business, on data everyone in the company trusts.
Analysis, forecast or AI agent: the first use case goes into operation on the new foundation, with department, metric and clear operational responsibility.
Management, sales and production look at the same numbers, with source, date and owner. Discussions revolve around decisions, not around data states.
Models and agents access the same platform as your reports. The next use case needs no new data basis, only a good idea.
We start with what is there, not with what is missing.
That is exactly what the platform is for. We connect the existing sources, ERP, CRM, machines, spreadsheets, instead of replacing them. Your systems keep running, the data flows together.
No. We clean where the first use case needs it, and automate the rules so that the quality stays. The rest follows step by step, driven by real need, not by a mega project.
Both are possible. We decide together based on data protection, cost and what your IT already operates today. Many mid-sized companies run hybrid: sensitive data in-house, computing load where it is cheap.
Your team, with clear responsibilities per data area and quality rules that check automatically. We build so that you do not depend on us permanently, and stay at your side in operation on request.
Whoever uses AI must be able to document data origin, quality and decisions. A platform with source, date and owner per record delivers exactly that, as a by-product, not as an additional project.