RPA and workflow automation for Dutch businesses

Automating administration means handing off the repetitive back-office work: processing invoices, retyping data between systems, routing emails, compiling reports, and generating standard documents. RPA takes over the structured, rule-based steps; agentic AI handles the steps that need interpretation. It connects to the tools you already use, so you do not have to switch. You start with one process that eats a lot of manual hours and expand where it measurably saves time.

Classic RPA is scripted automation: a bot follows a fixed series of steps on an existing UI or API, with no judgment of its own. Strong for stable, rule-based processes like invoice posting or CRM updates. Agentic AI has language understanding and can make decisions based on context, so it fits processes with variation, such as email routing or client onboarding where every case is different. DataDream often builds hybrid: RPA for the structured parts, agentic AI for the steps where judgment is needed. That makes the system both robust and flexible without locking you into a tool that only handles one of the two.

DataDream is tool-agnostic. For every project we evaluate whether UiPath, Microsoft Power Automate, Automation Anywhere, Blue Prism, Workato, n8n or custom Python is the best route. The choice depends on your existing stack, your IT policy, the volume and complexity of the process, and Total Cost of Ownership over three years. For a Microsoft 365 shop Power Automate is often logical. For scale-ups with technical teams n8n or a custom Python pipeline is cheaper and more flexible. For enterprises with high volumes and strict compliance requirements UiPath or Blue Prism may fit. DataDream is not a certified partner with any single vendor because that would colour the advice, and your interest comes first.

A defined bot for one process is a contained engagement, including testing and pilot deployment. A full workflow automation that ties multiple systems together with escalation and monitoring is a larger engagement. Engagements always start with one concrete use case rather than a platform project. A bot in production that works is worth more than a big roadmap delivering something in six months. For a new process the current time cost is measured first, then a first version is built, a limited user group goes live, and only then scale-up follows. The pace stays in your hands.

Process change is the biggest reason RPA projects fail. Classic scripted bots break the moment a UI or field name shifts. DataDream therefore designs with change in mind: bots get their own test set that runs on every deploy, critical steps are caught by agentic AI that can interpret rather than only copy, and documentation is delivered that lets you make small adjustments internally. For large process changes billing is by the hour, so no surprises. There are clients who maintain their bot themselves after six months, and clients who keep DataDream as their extended development team. Both work.

Classic RPA without AI falls outside the AI Act because no artificial intelligence is involved, only scripted rules. Once a bot includes an AI component, for example to classify a document or interpret an email, the AI Act applies. DataDream therefore builds audit trails by default: every decision is recorded with input, output, model version and any human approval. For agents that may fall into a high-risk category, such as recruitment or credit scoring, an extended compliance file is delivered. For lower-risk categories logging plus a usage notice is usually enough. Advice on which category applies is always given upfront.

That is exactly the preferred route. The starting point is one process that is well-defined and where the pain actually sits. Not "we want RPA", but "our accounting team retypes 800 invoices a month and that costs half a working week". Such a use case can be in production within two to three weeks with a limited user group. What it delivers in hours, lead time or error rate gets measured, adjustments made, and scope expanded. A Quickscan upfront helps pick the right use case. Six-month RPA platforms where you have to discover afterwards whether it works are no longer built.

It depends on the process, the volume and the tools you already use. A defined bot for one process sits in a different price band than a full workflow automation with multiple integrations and monitoring. DataDream works with fixed pilot prices or hourly rates for open-ended projects. Yearly RPA license fees are not passed on if the build can use tools you already have or open source. For a fair price quote a 30-minute discovery call is needed: an assessment is made of whether RPA, agentic AI or a hybrid fits, and you get an indication. Schedule a call via /en/contact.