How to pick an AI company in the Netherlands in 2026: SMB checklist

Choosing an AI company is not a tool choice

Anyone looking for an AI company in 2026 enters a market that has multiplied fivefold in two years. Hundreds of Dutch agencies, from one-person operations to consultancy arms of Big Four firms, claim "AI implementation for SMBs". The differences are vast: between those who deliver a PowerPoint and those who put a working system in production sits a factor-of-ten value gap. This article gives an honest checklist for choosing an AI company, written from our own perspective as a builder and from projects where we encountered peer agencies.

The seven selection criteria

1. Can they show you what is running in production?

The most important question. An AI company that only shows pilots, demos, or "POCs" often does not deliver working systems in practice. Ask concretely: which client has an AI system live now, how many hours per week does it save, and can we briefly speak with that client? An honest agency has three to five examples ready. A marketing agency that does AI as a side product, often not.

2. Do they build or only advise?

Two kinds of AI companies: builders and strategists. Strategists deliver reports, builders deliver working systems. Both have a place, but SMBs usually benefit more from a builder that can also think strategically than from a strategist that hands you off to a vendor afterwards. Ask: who writes the actual code or builds the actual automation? If the answer is "a subcontractor in Poland", you know where you stand.

3. Who sits on the other side of the table?

At larger agencies you get account managers and project managers between you and the technology. At small agencies you talk directly to the builder or the founder. For SMBs direct contact with the founder is usually faster and cheaper, because intermediate layers cost money and often lose information. Ask: who is my fixed point of contact and how often will I speak to that person?

4. Tool-agnostic or partner-locked?

A certified UiPath partner will recommend UiPath. A Microsoft Gold Partner will recommend Copilot Studio. That advice is not necessarily wrong, but it is biased. Ask: how do you arrive at a tool choice, and what would your advice be if we did not want Microsoft or UiPath? An honest agency evaluates per project and has no partner bonus to defend. For the RPA decision see /en/rpa, for agentic AI see /en/ai-agents.

5. What do they do with your data?

Three things to check: where is your data processed (EU-only or US cloud?), is it used for model training (default for consumer tiers), and what does the data processing agreement (DPA) say. For GDPR-sensitive sectors (healthcare, legal, financial) this is not a detail but a dealbreaker. A serious AI company shows how they can build on-premise or EU-only when needed. For the broader AI Act context see /en/ai-act.

6. AI Literacy (Article 4) in order?

From 2 February 2025 the EU AI Act requires staff using AI to have sufficient knowledge. An AI company that does not explain this, does not deliver training, and does not provide a compliance file per use case exposes you to fines and reputation damage on audit. Ask: how do you handle AI literacy for my team, and what documentation will I receive? See /en/ai-training for our take on this.

7. What does it cost and how do they bill?

Three models you encounter: fixed price per project, hourly rate, and subscription (retainer). For defined pilots fixed price works best. For open-ended work hourly billing pays off (provided there is a budget cap). For ongoing monitoring + small changes a retainer is logical. Honest discussion topics: how is overage billed, what is the exit clause, and what does the client own (code, prompts, documentation)?

Red flags

Three patterns we encounter in the market that we view as warnings:

"Six months of AI strategy, then we start building." For 90 percent of SMB cases that is overkill. A good AI roadmap takes two to four weeks; after that you start building. Agencies selling six months of strategy often sell strategy to you and do not build themselves.

No fixed prices, no scope document. If an agency starts with "we can only give you a price after extensive intake" and that intake itself costs €5,000 to €15,000, the scope is unclear. For defined use cases a serious AI builder can give a target price after a 30-minute conversation.

Tools pitch instead of problem analysis. "We use UiPath and GPT-4 and n8n and LangChain" is a tool stack, not an approach. A good conversation starts with "what does it cost you now, in hours or euros, and what would a 50 percent reduction be worth?". Tools come after.

Realistic price ranges

As of early 2026 in the Dutch market:

One-person operation / freelance AI developer: €60-110 per hour. Suitable for small defined projects. Risk: bus factor of 1.

Small specialised agency (2-10 people): €100-180 per hour, or fixed pilot prices €5,000-€20,000. Sweet spot for SMBs and scale-ups.

Mid-market consultancy: €150-300 per hour, projects from €50,000. Suitable for enterprise tracks with many stakeholders.

Big Four consultancy: €250-500+ per hour, projects from €100,000. Suitable for compliance-heavy sectors needing board buy-in.

DataDream sits in the second category. We do not list fixed prices on the website because scope varies per project; a 30-minute discovery call is enough to give an honest indication. Schedule via /en/#contact.

How DataDream positions against this checklist

We did not invent this checklist; clients asked us similar questions during selection conversations. Our answers:

1. Production: five+ clients with live AI systems, voice agents, document extraction, content pipelines. References available on request.
2. Builder or strategist: primarily builder. We do strategic advice where it helps, but our value sits in working systems.
3. Direct contact: you work directly with Laurens (founder and lead engineer). No account-manager intermediate layer.
4. Tool-agnostic: no partner lock-ins. Per project we evaluate UiPath, Power Automate, n8n, Workato, custom Python and the right LLM provider.
5. Data: EU-only deployment available, on-premise possible for sensitive sectors. GDPR compliant by default.
6. AI Literacy: Article 4-compliant training via /en/ai-training, compliance file per use case.
7. Rates: fixed pilot prices for defined projects, hourly billing for open-ended. Ownership stays with the client.

For the full service overview see /en/ai-oplossingen. For agentic AI and voice AI see /en/ai-agents. For RPA and workflow automation see /en/rpa.

Conclusion: three questions to ask upfront

In every conversation with a potential AI company, these three questions filter out the time-wasters:

1. "Which client currently has an AI system in production that you built, and can I have a 10-minute call with them?" If the answer hesitates or redirects to "we can demo it", that is a red flag.

1. "Suppose I want a working first version in six weeks. Which use case would you recommend, and with which tools?" A good agency gives a concrete answer within 5 minutes. A poor agency says "that depends on the intake process".

1. "What does your standard data processing agreement say about AI data?" If they have one and can explain it, good. If not, look elsewhere.

Want to apply this checklist to DataDream? Schedule a free 30-minute discovery call. No sales pitch, just an honest assessment of whether we are the right choice for your situation. Or start with the free AI Readiness Scan for an initial direction.