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DataDream

RPA and workflow automation for Dutch businesses

Robotic process automation, agentic AI or a hybrid: we build automation that fits your stack, without yearly RPA licenses or vendor lock-in. Start small, scale what works.

  • What you get
  • What it delivers
  • Frequently asked questions

Robotic process automation, or RPA, is software that takes over manual office work by walking through the same steps a person would: log into a system, copy a field, press a button, download a file. Classic RPA uses scripted bots that follow a fixed flow. For stable, regular processes like invoice posting, stock updates or CRM synchronisation, RPA has been delivering real time savings since 2015. A large share of office work at Dutch SMBs and scale-ups is repetitive and structured enough to be automated this way. The question is not whether but how and with which tools.

The landscape in 2026 is different from 2018. Alongside classic RPA bots there is now agentic AI: software that understands language and context, and can therefore automate processes that used to be too variable. Triaging an inbound email to the right department, classifying an unstructured document, answering a phone call to a script: things where pure RPA hit a wall now belong to agents. The difference is predictability versus flexibility. RPA is faster and cheaper for tight processes, agentic AI is more robust under variation. In practice, hybrid is almost always the right route: RPA for the structured steps, agentic AI for the steps where judgment is needed.

The tool choice is broad. UiPath and Blue Prism are the enterprise veterans with the highest license costs. Microsoft Power Automate is logical if your organisation already lives in M365. Automation Anywhere and Workato play in the mid-market. n8n and Make are open-source or low-cost alternatives that often suffice for scale-ups, and custom Python is the most flexible route for those with a development team. We are tool-agnostic: per project we evaluate which package offers the best ratio of Total Cost of Ownership, maintenance burden, integration options and compliance. No partnerships that colour our advice, no yearly licenses passed on if we do not need them.

Our approach is build rather than license. For most SMB cases a custom workflow on n8n or Python is cheaper over three years than a UiPath license. We set the system up in an EU-only environment you control, with audit trails on by default for AI Act compliance. We start with one defined use case (typically two to four weeks to production), measure what it delivers in time or error rate, and only then expand. For strategic advice on RPA-vs-agentic decisions see AI strategy. For agentic AI implementations without a classic RPA layer see AI agents; the broader automation roadmap sits separately.

What you get

01

Invoice processing and order-to-cash

Incoming invoices still read, coded and posted manually. Per invoice it costs one to four minutes, and at hundreds per month that ties up half a working week or more. The same pain on the outgoing side: orders that need to come from a webshop or CRM, into the ERP and then into accounting.

We connect email or OCR input to your accounting package (Exact, Twinfield, AFAS, Yuki) via API or an RPA bot, with an AI layer for classification and field extraction on uncertain values. A doubt flag sends edge cases to a human, the bulk flows through. Audit trails are on by default for accountant review.

02

Client onboarding automation

A new client signs: contract data must go into CRM, project into project management tool, invoice template into accounting, welcome email out, calendar invite for kickoff. Five systems, five manual steps that currently cost an hour or more per onboarding. At ten clients a month that is half a working week.

A workflow on n8n, Make or Power Automate that ties all steps together, triggered by one signal (signature, payment or form submission). Variable steps where judgment is needed, such as tone check of the welcome email or segment selection, go through an agentic AI step. If a step fails, your project channel shows exactly where it went wrong.

03

Reporting and data pipelines

Weekly or monthly collecting data from multiple sources, cleaning, joining and sending to a dashboard or email for management. The kind of work a data analyst spends two to four hours a week on, and very suited to automation.

We build a pipeline (Python, n8n or Workato) that fetches sources each period (Google Analytics, HubSpot, Exact, Excel exports, Snowflake), cleans according to a fixed rule set, and delivers the report in your template. For deviations we use anomaly detection so reports do not only show numbers but also flag what stands out. See AI data for the full data approach.

04

Lead qualification and routing

Inbound leads from website forms, email or LinkedIn that are manually read, enriched and assigned to the right account manager. At higher volumes this means warm leads go cold before anyone sees them, and bad leads unnecessarily consume time.

An agentic workflow that immediately enriches every lead (KvK data, LinkedIn, mention scrape), classifies by your ICP criteria, and routes to the right person in CRM with a priority flag. Uncertain or edge cases go to the sales manager with context. Response time back from hours to minutes, without adding headcount.

05

Document extraction and contract analysis

Contracts, policies, delivery notes, passports or compliance documents currently read manually for specific fields or clauses. At volume or under audit this is unfeasible, and under urgency it costs the most time.

A document pipeline that does OCR (where needed), then uses agentic AI to extract the relevant fields or clauses: counterparty, end date, notice period, liability, ID number, exceptions. Result in structured JSON or directly into your DMS or CRM. For legal review see AI for lawyers; for accounting flows see AI for accountants.

What it delivers

  • Start small with one process, in production within 2-4 weeks
  • Tool-agnostic: UiPath, Power Automate, n8n, Workato or custom Python
  • No yearly RPA licenses if we can build on your existing stack
  • Hybrid RPA + agentic AI for processes with variation
  • EU-only deployment for GDPR-sensitive data
  • Audit trails on by default for AI Act compliance
  • Bot ownership stays with you, no vendor lock-in
  • Human-in-the-loop for edge cases via Slack or Teams
  • Maintenance documentation so you can adjust internally
  • 30-minute discovery call for an honest scope estimate

Frequently asked questions

What is the difference between RPA and agentic AI?

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. We often build 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.

Do you work with UiPath or a specific RPA vendor?

We are 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. We are not certified partners with any single vendor because that would colour our advice, and your interest comes first.

How long does it take to build an RPA bot?

A defined bot for one process is often operational in two to four weeks, including testing and pilot deployment. A full workflow automation that ties multiple systems together with escalation and monitoring typically takes six to ten weeks. We 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 we first measure what it currently costs you in time, then build a first version, go live with a limited user group, and only then scale up. The pace stays in your hands.

What if our process changes after implementation?

Process change is the biggest reason RPA projects fail. Classic scripted bots break the moment a UI or field name shifts. We therefore design 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 we deliver documentation that lets you make small adjustments internally. For large process changes we charge by the hour, so no surprises. We have clients who maintain their bot themselves after six months, and clients who keep us as their extended development team. Both work.

Is RPA AI Act compliant?

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. We therefore build 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, we deliver an extended compliance file. For lower-risk categories logging plus a usage notice is usually enough. We always advise upfront which category applies.

Can we start small with a pilot?

That is exactly our preferred route. We start with 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. We measure what it delivers in hours, lead time or error rate, adjust, and expand. A Quickscan upfront helps pick the right use case. We no longer build six-month RPA platforms where you have to discover afterwards whether it works.

What does RPA implementation cost?

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. We work with fixed pilot prices or hourly rates for open-ended projects. We do not pass on yearly RPA license fees if we can build on tools you already have or on open source. For a fair price quote we need a 30-minute discovery call: we assess whether RPA, agentic AI or a hybrid fits, and give you an indication. Schedule a call via /en/contact.

Let's get acquainted.

Book a free call or send us a message. We always respond within 24 hours on business days.

Phone / WhatsApp

+31 85 124 95 22

Location

Middelburg, Zeeland

Availability

Reachable 24/7 digitally

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