What does “in control” mean?

This document answers one question: what exactly does this term mean?

In control means an organisation stays the owner of its processes, its data and its technology choices. It is not a checkbox for the lawyer, but a foundation: whoever understands and governs their processes makes the entire organisation auditable. Below we explain the term through three pillars and the three questions behind them.

Three pillars of control

Being “in control” rests on three pillars. Together they keep you the owner:

Process control

I understand my AI

I know what it does, I can change it and I can audit it.

Data control

I decide what is shared

I decide which data leaves my organisation — and which does not.

Vendor control

I can switch

A different AI provider tomorrow, without rebuilding my entire business process.

Going deeper: three questions

“Local”, “vendor lock-in” and “in control” are often used interchangeably, while they are three different things. Behind each pillar sits one clear question.

Question 1 · Process control
Where does the process run? (Local)

This is about where the software runs. With MMC, the workflow runs in the customer’s own environment. That can be:

an own server
the customer’s Azure
the customer’s AWS
a private cloud
or, optionally, our managed environment

The key point is: the customer decides where the process runs. Not MMC. Not OpenAI. Not Anthropic.

Question 2 · Data control
Where does the data go?

This is a different question. You can run a process entirely locally and still send a prompt to an external model. For example:

PDF

↓

Local OCR

↓

Local workflow

↓

Only the summary goes to GPT

↓

Answer comes back

↓

Local storage

The workflow is local. One step uses an external model. That is fine — the question is: which data leaves my organisation? That is what governance is about. MMC keeps that as small as possible: only the relevant paragraph, no personal data, no complete files, anonymised where possible. So not everything local. But: every exchange is a deliberate choice.

Question 3 · Vendor control
Who owns the process? (Lock-in)

This may well be the most important one. Many AI platforms say: “Use our builder.” After a year everything lives there: a hundred workflows, two hundred prompts, a hundred and fifty connectors — all inside that one platform. Want to switch? You can’t. That is lock-in.

MMC does exactly the opposite. The process belongs to the customer — not to MMC, not to OpenAI, not to Anthropic. The workflow is built from ordinary components. You can replace GPT with Claude tomorrow. Or Claude with Gemini. Or run Llama on your own hardware. The process barely changes; only one building block does.

A metaphor

Vendor lock-in is like buying a house, but the builder says: you may live in it, but only we have the key, only we may change the kitchen, and only we know where the pipes run. That doesn’t feel like your house.

MMC says the opposite: this is your house. We help build it, but you get the drawings, the keys and the installations — and any builder can do maintenance later. That is ownership.

So what does “local” really mean?

Not: “data always stays within the walls” — that is not always true. Better: local means your business process, configuration and data storage stay under your control. External AI models may be used, but only when you want them to and only for the data you explicitly decide to share.

Most AI platforms deliver software.
We make sure you stay the owner of your processes, your data and your future.

We don’t deliver software, but a better business process.