Applied AI · Netherlands

AI, built to healthcare standards.

Production systems for organisations that cannot afford to get data wrong.

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Eindhoven · Working across Europe

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01The gap

Most AI never survives contact with a real business.

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The demo is the easy part. What breaks is everything after it: the model that is confidently wrong at three in the morning, the integration nobody scoped, the audit that arrives eighteen months later asking where the data went.

We build for that day rather than for launch day. Monitoring, fallbacks, audit trails, and a written answer for what happens when the model is wrong.

02What we build

Five systems we have built often enough to describe in advance.

If it is not on this list, ask. The list describes what we have shipped, not the limit of what we can build.

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01

Medical & health software

Software that can hold patient data. Practice platforms, patient portals and clinical tooling, designed to the standard health data demands from the first sprint rather than retrofitted before an audit.

Medical & health software →
02

AI receptionists

A phone line that always answers. Takes calls, books appointments, answers the twenty questions you get every day, and hands to a human the moment it should. It works at three in the morning.

AI receptionists →
03

Booking & scheduling

Scheduling that runs itself. Intake, availability, reminders, rescheduling and no-show chasing, synced to the calendar you already use. Built around your rules, not someone else's software.

Booking & scheduling →
04

Knowledge assistants

An assistant that has read everything you have. Grounded in your own documents and policies, with citations, so staff and customers can check the answer. Runs on your own infrastructure if the data cannot leave it.

Knowledge assistants →
05

Custom AI applications

Whatever the thing actually is. Internal tools, document pipelines, vision and OCR systems, consumer apps, integrations between software you already pay for. If it involves a model and has to work in production, it is in scope.

Custom AI applications →
03How we work

You will know the price and the date before you commit.

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  1. Tell us the problem, not the solution. The quote form asks for exactly that and takes about five minutes.
  2. A short call, if it looks like a fit. Thirty minutes, free, no deck. Sometimes this is where we tell you AI is not the answer.
  3. On-site, if it helps. When the work runs across several people or teams, the engineer who will build it spends one to three days in your office first, watching how the work is really done.
  4. A written scope with a fixed price and a date. Free, like the call, and yours to keep either way.
  5. Weekly demos on real data. You see it working, or not working, every week rather than at the end.
  6. Deployment into your environment, with staff training. Then monthly support, or the keys and the documentation.
04Why Neurova

Five things that are true here and often are not elsewhere.

None of these are promises about effort. They are structural, and you can hold us to each one in writing before the work starts.

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01

Healthcare-grade by default

European storage, least-privilege access, full audit trails, data minimisation designed into the architecture. Your customer data gets the same treatment as patient data, whether you are a clinic or not.

02

Production, not pilots

Systems that run your business on Monday, not demos that impress on Friday. Monitoring, fallbacks and a documented plan for when the model is wrong, because that is where these projects actually fail.

03

You work with the person who builds it

No account managers, no offshore handoff, no discovery deck. Whoever scopes your system is whoever writes it, and you have their phone number.

04

A number before you start

Fixed scope, fixed price, a date. No open-ended hourly billing and no discovery phase that quietly becomes the project. Scope changes are agreed before the work, not invoiced after it.

05

You own what we build

Your code, your data, your infrastructure, in Europe. No per-seat licence, no lock-in, no hostage situation if you take it in-house.

05Who we are

Engineering out of Eindhoven, for clients across Europe.

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Neurova AI works where applied AI meets regulated data. That is a harder place to build than either on its own, and it is where the interesting problems are.

You can read how we think before you ever speak to us. The blog carries fifty-six articles on AI in production, the EU AI Act, the MDR, NEN 7510 and building software for the Dutch market. Consider it the working version of a portfolio.

06Do it yourself

Rather build it yourself? Four guides, one weekend each.

Each fast-track guide takes one job and walks through it step by step, on a worked example we built for real while writing it. Copy-paste prompts and a checklist come with every one, and you can read the first chapter of any of them free.

Guide 04 · Experienced professionals (3–15 years)

AI Job-Search Fast-Track

Turn your experience into proof that screening systems and recruiters can read, then tailor each application in about 15 minutes without inventing a thing.

Chapter 1 free (PDF)

All guides and editions →

07Questions

Straight answers.

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How long does an AI project take?
A focused pilot is typically two to four weeks. Production, with the monitoring and fallbacks that production actually means, is usually four to twelve or more depending on what it has to integrate with. You get a date in the written scope before you commit, and we tell you early if it moves.
What does it cost?
We do not publish price lists, because the range between a simple assistant and a compliant clinical platform is enormous and any figure we printed would be wrong for most people reading it. You get a written scope with a fixed price and a date, at no charge and with no obligation, before anything starts.
Where does our data live?
In the EEA by default, and on infrastructure you control where the data calls for it. For anything covered by professional confidentiality we will design it to run without leaving your own environment, and we will be straight about what that costs in capability before you decide.
What happens when the AI gets something wrong?
It will, so we treat that as a design question rather than an accident. Every system ships with an answer: a confidence threshold, a human review step, a deterministic fallback, or a clear failure message. Anything that cannot say it does not know will eventually say something worse.
Do we need to know exactly what we want first?
No. Describe the problem rather than the solution. Part of the scoping work is deciding what should actually be built, and sometimes the honest answer is that AI is the wrong tool or that something off the shelf will do the job for a fraction of the cost.
Who owns what you build?
You do. Your code, your data, your infrastructure. No per-seat licence, no lock-in, and no hostage situation if you want to take it in-house or hand it to someone else later.
08Contact

Tell us what you want built.

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The form asks what you are trying to solve, what you think you want built, and when you need it. You will get a reply within one business day, from the person who would build it.

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Occasional notes

New articles on applied AI and healthcare compliance, when there is something worth saying. No sequence, no drip campaign.

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AI, built to healthcare standards.

Get a quote