AI & automation · AI where your data already is

Use AI without replacing a single system.

We connect AI to your existing systems – ERP, CRM and DMS stay.

What happens here

AI where your data already is.

Your systems are connected, not replaced.

The red seal

People give the final approval.

First a measurable pilot at a binding price after the first consultation. We scale up when the numbers add up.

Does this sound familiar?

AI projects rarely fail because of the AI.

They fail because of data silos: ERP, CRM and filing do not know each other. Skip that, and you automate your data problems.

What is included

Integration services

  • Data flow map: where it breaks
  • Integrations between your systems
  • AI functions on your real data
  • MCP: one standard instead of many one-off integrations
  • Data quality: fix duplicates
  • Hybrid: Sensitive data stays in-house
Your landscape, briefly sketched

What do you use? We show the connections most worth making.

A rule-based sketch, locally in your browser. We draw the real map in the consultation.

How it works

To AI in your systems in three steps.

Step 1Map out

Map the data flows, name the silos.

Step 2Connect

The most worthwhile data routes first, with logging.

Step 3Dock on AI

One use case first, measured, then more.

The technical view

Data first, then AI.

One standard instead of five building sites

Via the Model Context Protocol (MCP) AI accesses your systems in a controlled way. Connected once, with no tie to any one AI provider.

The data flow map first

Contradictory data produces contradictory results. Often connecting two systems is enough – and if so, we tell you.

Sensitive data stays here

Non-critical data runs through cloud AI; HR and contract data through your own or EU infrastructure. We draw the line beforehand, and document it.

Common questions

AI integration – what managing directors ask us.

Do we have to replace our systems?

No – that is the core of the offer: AI and automation dock on to your existing setup. At most, what demonstrably holds you back gets replaced – and that would then be a deliberate, calculated decision, not a precondition.

What if our legacy system has no API?

Then we check the alternatives: automated export/import, a database connection, in an emergency robot-assisted operation. Sometimes the answer is also: we leave this one system out. What works and what does not we say before the quote.

What about our data quality?

We look at that first – AI only makes bad data bad faster. Duplicates, gaps and contradictions are named and fixed before AI works on them. Often this cleansing is the most valuable part of the project.

Does sensitive data stay in-house?

Yes, via a hybrid setup: sensitive material runs through components on your own or EU infrastructure, non-critical material through cloud AI. We define the boundary together and in writing – before the first data exchange.

What is MCP, and do we need it?

An open standard through which AI assistants access several systems in a controlled way – instead of building an extra integration for each system. Most will need it only with their second AI use case; planned cleanly it saves real money from then on.

How do we begin?

With the data flow map and one prioritised connection – not with everything at once. The mini configurator above gives a first idea; the real map we draw in the free consultation.

Let’s talk

Free consultation at a fixed appointment – or a non-binding price range first.

Free consultation Request a quote