AI as practical operational infrastructure.

Artificial intelligence works within existing business processes: it classifies information, recommends actions, automates tasks and measures results. It needs to be part of the company’s infrastructure rather than an isolated experiment.

Governance, data privacy and human oversight belong in the project from the start.

Start with a business decision that is currently late, poor or expensive because information is delayed, incomplete or hard to find. If nobody can name that decision, the project still lacks an objective.

What it produces

An assessment of the available data: where it is, who updates it and how complete it is. This often changes the scope of an AI project more than a technical benchmark does. A model cannot make up for data that nobody maintains.

Each use case is then assessed against its expected benefit and the cost of running it in production. The project also defines privacy and governance rules, the points where a person must be able to intervene, correct or stop the system, and the indicators used to measure whether it helps.

Human oversight is necessary to catch an error before it becomes a decision.

Who does what

The business decides which decisions it is willing to automate and which it is not. It retains responsibility for that choice. MA.VI assesses use cases, defines governance and identifies where human oversight is needed.

Technical suppliers build the system. MA.VI checks that it remains measurable and that the rules agreed at the start are still applied six months later.