Not experimenting with AI, but building an application that takes over a concrete task — the phone, documents, recurring messages.
AI is only useful once it takes over a task that costs time today. I start with the process, not the model: which steps are repetitive, where does it go wrong, and what may be automated? Then I build the application — a phone assistant, a document parser, or an integration that replaces a manual step. Where possible the data stays in Europe or on your own server.
Which task costs the most today and is the most predictable? That's where it starts.
Where may the data live, what may the model see, who is responsible for what?
A working version on real input, not on sample data.
What goes well, what goes wrong, and where should a person take over?
Projects I actually built — not sample cases.
Healthcare organizations spend a lot of time on phone handling — simple questions block the line for emergencies.
AI-driven phone assistant with speech recognition, LLM triaging and seamless handover to human staff.
Automatic handling of routine questions, healthcare staff relieved, patients helped faster.
Orders with customer data and print PDFs came in at Boogaard Textiles. Those orders had to be placed into the print program with cutting lines — but it was so much manual work that the €100k cutting machine stayed unused. Instead, everything was cut with scissors.
A Laravel API that automated the entire process: process incoming orders, generate cutting lines, place them paper-efficiently in the print program. A dashboard tracked everything with barcode scanning — no more lost orders. Connected to the website, financial administration and postal dispatch.
The cutting machine is finally in daily use. A permanent employee was hired to operate it. The boss's son was freed from manual cutting work, editing cutting lines and order management. The workflow went from a day to 20 minutes.
Government organizations need to match CVs against CompetentNL competencies — a manual, error-prone process. HR staff lost a lot of time interpreting widely varying CV formats and mapping them to standardized competencies.
A Laravel + React application that automatically parses CVs, extracts competencies and matches them against CompetentNL standards. The tool recognizes free-text experience and translates it into structured competency profiles. Fully bilingual English/Dutch, with Docker deployment.
Immediately usable for UWV migration projects. Scalable to all Dutch government layers. Reduces manual CV processing by tens of percent.
Sectors where this work pays off most.
Background on this service, without the sales pitch.
No fuss, no unnecessary meetings. Just clear agreements and steps you understand.
Free, no-obligation conversation about your idea, problem or project. No sales talk — I want to really understand what you're up against.
I work out a plan of action with concrete milestones, technical choices and a fixed price or hourly rate. No vague estimates.
I build in short 1-2 week sprints. You see continuous progress and can steer along the way. No black box.
Going live, documentation, and a support period. You're not on your own — you can reach me afterwards too.
Ongoing operation, tuning and further development as long as your systems run. No 'done' moment — a fixed monthly price with one point of contact.
What clients usually want to know before they call.
I work from Vaals, on site across South Limburg and beyond.
Not sure what you need? I'm happy to think along.
Intro call: free & no obligation
Get in touch