Custom AI Solutions Built for Your Business

It can answer customer questions, search your content by meaning, predict demand or churn, detect fraud, read documents, automate repetitive work and add intelligent features to your product. The best uses are wherever your team does repetitive thinking or where the data you already hold could drive a faster decision.

An AI solution in the Netherlands typically costs between EUR 10,000 and EUR 80,000 in 2026, depending on scope. A focused proof of concept or a RAG assistant can start around EUR 4,000 to EUR 15,000, while a production feature integrated into a full product reaches the upper end. We usually begin with a small fixed-price proof of concept so you see results before committing.

RAG, or retrieval-augmented generation, means the AI answers using your own documents and data instead of guessing from what a model learned online. You almost always want it for any assistant that answers questions about your business, because it keeps answers accurate, current and grounded in sources you control.

We choose the model for the job rather than committing to one. GPT and Claude are excellent for general reasoning and language, while open-source models like Llama and Mistral suit lower cost at scale, full control or private deployment. We often combine them and explain the trade-offs in plain language.

Yes. We use private deployment and retrieval from your own sources, so the model uses your data to answer without absorbing it into a public model. Everything runs on European, GDPR-compliant infrastructure, and your data never trains someone else's AI.

Quite possibly, and it is better to design for it from the start than to retrofit later. The EU AI Act sets rules on transparency, data handling and human oversight, with stricter requirements for higher-risk uses. We build with those rules in mind so your AI is defensible rather than a compliance risk.

Because the demo is the easy part. Most projects stall when the model meets real data, real users and real cost, and was never engineered for accuracy, safety or scale. We focus on exactly that engineering — the retrieval, guardrails and evaluation — which is what gets AI into production.

A proof of concept usually takes two to four weeks, and a production feature commonly three to four months from there, depending on complexity. We deliberately start small, proving the AI works on your data before the full build, so you are never months in before knowing if it holds up.

Yes, that is one of the most common things we do. We integrate search, automation, language or prediction features into your current app and connect them to your existing data, rather than asking you to rebuild. The same team handles any backend work the AI needs.

AI is the broad field of software that performs tasks needing intelligence. Machine learning is AI that learns patterns from data, used for prediction and classification. Generative AI, like GPT and Claude, creates new text, images or code. Most modern products combine them, and we pick the right tool for each task.

It depends on the task. Generative AI and RAG work with your existing documents and need no training data as such. Predictive models need relevant history, though often less than people expect. We assess this early and tell you honestly what is required rather than overpromising.

Yes, all AI can be wrong, which is why we engineer around it. We ground models in your data, add guardrails and validation, and keep a human in the loop for anything high-stakes, so an uncertain case is flagged rather than acted on blindly.

Ready-made tools are great for standard needs and we will say so. Custom AI is worth it when you need it built around your own data, workflow or product, or when an off-the-shelf tool cannot reach the accuracy or privacy you need. We help you judge honestly which fits.

Yes. We build assistants trained on your own help content that answer common questions instantly and hand off cleanly to a human when unsure, in Dutch and English. This is one of our most common and highest-value AI projects.

Yes. The same team builds the AI model, the backend, the integrations and the interface, so you get a finished product rather than a model nobody can deploy. That full-stack ownership is a big reason our AI features actually ship.

Our approach is to remove repetitive thinking, not people. We automate the routine, high-volume work and keep humans in charge of judgment and exceptions, so your team spends time on what genuinely needs a person.

Yes. AI is not set-and-forget, because data and usage shift over time. We monitor quality, cost and drift from day one, retrain and tune as needed, and extend the system as you find new uses, so it stays accurate and useful.

Yes. You own the code, the models and the IP. There is no lock-in that forces ongoing payments to keep using your own system.

Yes, the Netherlands and the wider EU are home turf for us. Our European base is in Amstelveen, near Amsterdam, so Dutch and EU clients get a local point of contact in the same time zone, AI built to GDPR, AVG and EU AI Act standards, and invoicing in euros.

Book a short call and tell us the problem you want AI to solve, such as answering customer questions, predicting demand or reading documents. We will tell you honestly whether AI fits, and how we would build it.