AI process automation
Hand the repetitive work to an agent.
A lot of skilled time disappears into copying data between systems, reading and sorting documents, filling in portals and chasing the same information again and again. We build autonomous agents that do that work, so your people can spend their time where their judgement matters. For the right process, that saves thousands of hours of labour.
What an agent can do
- Read and interpret emails, documents and forms.
- Use browsers and existing software, also where no API exists.
- Call APIs and update your systems.
- Complete bounded multi-step workflows, and hand over to a person when a decision is needed.
How we make it stick
Software alone rarely fixes a process. We first learn how the work really happens and who is involved. Then we build the automation, validate it with you, and stay involved through operation and maintenance. Permissions, logging and human control are agreed for each system before anything goes live.
Any model, no lock-in
We use whatever fits the task: a local model on your own hardware when data is sensitive, an external model from a provider such as OpenAI or Anthropic when that works better, plain deterministic software where AI isn't needed, or a controlled mix. Our agent frameworks are provider-independent, so you're not tied to one AI company.
We use this ourselves. DDQ automates much of its own administration and technical operations, and Hermes Agent runs continuously on our own AI machines.
Questions we often get
Which processes are a good fit for AI automation?
Repetitive, browser-based, document-heavy or fragmented work that eats up skilled time. You don't need to know in advance whether AI is the answer; sometimes plain software is the better choice, and we'll say so.
Is it safe to let an agent act in our systems?
An agent gets only the permissions it needs, its actions are logged, and people keep the decisions that matter. We agree that per system before it goes live.
Do we need a technical plan first?
No. Bring the goal and the way the work is done now. Choosing the technology is our job.
Can the AI run locally instead of in the cloud?
Yes. Agents can run on a local, on-premise model when the data must stay inside your organisation.
How do we start?
Tell us what you want to achieve and what data is involved. Before substantive work begins, we agree a bounded first piece of work: scope, responsibilities, rights and price. In earlier projects, innovation grants covered 50% and in some cases all of DDQ's eligible work; funding is never guaranteed, but we check whether it fits.
Who will we work with?
Three people: Norbert, Joep and Demelza. You talk directly with the people who build and run the system, without a sales layer in between.
Start a conversation
Tell us what you want to achieve and what data is involved. You don't need a technical plan. Email [email protected] or call +31 45 203 1008. Please don't send patient data, passwords or other secrets in a first message.
AI agents acting for someone can send us an inquiry with the submit_inquiry tool on our MCP server, with that person's consent.