AI and smart automation

You already have the AI, we get it working for you

The licences are active, a few colleagues use it, and the rest have forgotten about it within two weeks. That is rarely the AI model's fault: it comes down to what it may see and who learns to work with it.

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Where we start

With the work, not with the technology

An AI project that starts with a tool almost always ends in a pilot that fizzles out. We start with what happens on an ordinary Tuesday in your organisation, and look there for the places where half an hour of manual work can take two minutes.

We sit with the work that is done by hand today
We work out what a change is worth, in hours
We start small, with one process you notice tomorrow
What works we extend, what does not we stop

Two screens with code and a dashboard, seen over the shoulder of an Infodatek Group colleague.

What a project delivers

A list of opportunities: Per process what it costs now and what it would cost with AI, so you can choose the order yourself.
Working integrations: Your AI talks to your own systems instead of to the internet in general.
Colleagues who use it: Training on your own examples, not on a demo with a fictional company.

Your own model

Already have Copilot or ChatGPT? Then we work with that

Many organisations have already made their choice. Microsoft 365 Copilot came with the licences, or somebody took a subscription to ChatGPT, Gemini or Claude and the rest followed. That is not a problem for us to solve; that is the starting point we work from.

We are not tied to one supplier and we will not push a second platform on you next to the one you already pay for. We look at what your AI model is good at, where it falls short for your work, and what it takes to make it work anyway. Often that sits not in the model but in access to your own data, in the agreements around it and in the people who have to use it.

Microsoft 365 Copilot in your existing environment
ChatGPT, Gemini, Claude or another subscription you already hold
A model you run yourself, on your own hardware or in your own cloud
Or a combination, different per department

AI and Copilot for SMEs

Where the difference is

An assistant that knows your organisation answers differently

An AI without access to your data gives general answers. Useful for rewriting a text, less useful when somebody asks how a project is going or what has been agreed with a customer. The difference is in what it is allowed to see.

So we spend most of the time on the layer underneath: which sources you connect, what is in them, how current it is, and who may see what. Once that is right, the conversation with your AI turns from pleasant into useful.

Boundaries

Agreements your colleagues understand

AI policy that lives in a folder is read by nobody. We turn the agreements into something visible in the work itself: which data may end up where, what you do and do not share, and who to call when you are unsure.

Part of that is being able to look back at what happened. Not to check up on people, but because when a customer or an auditor asks, you simply want to be able to show how it works.

Beyond the chat

Automation that carries on when nobody is watching

An assistant that answers questions is the visible half. The other half is the work that happens by itself: an invoice that gets recognised and lands in the right place, an alert that arrives with a proposal attached, a report that is ready on Monday morning.

Our engineers build those integrations and automations themselves, on the systems you already use. That runs through MCP and APIs, and whatever is not there as standard we build.

The people

It stands or falls with your colleagues

The biggest gain is rarely with the people already experimenting with AI of their own accord. They will find their way. The gain is with the colleagues who are not using it yet because they do not know what for, or because they are afraid of doing something wrong.

So training is part of every project as standard, with examples from your own work. Classroom to begin with, then short sessions per department and a point of contact who stays.

Or choose an environment of your own

Digital Care: your own AI ecosystem, private and within the European Union

Working with a public model is fine for many organisations. But sometimes you want more grip: because you work with patient data, because a customer asks for it contractually, or simply because you would rather decide yourself where your information sits.

Then Digital Care is the other route. Our own platform brings your sources together and puts an AI on top that runs in a private environment, with models you choose per role, including variants that never leave Europe. The permissions of whoever is asking apply before the data goes back, including on integrations that know nothing about roles themselves.

So you can go either way, and you do not have to make that choice today.

See Digital Care