Pillar 03

A demo is built in a day. Production is a promise.

AI makes building easy, which makes the question “who is responsible once it runs?” more important than ever. Generated code without an owner is technical debt with an on-switch. We are that owner: we monitor, we maintain, and we stand behind your system by name and by SLA.

Have your system audited

What we do

  1. 01

    Taking over (AI-generated) codebases

    Audit, hardening, and then support with guarantees.

  2. 02

    SLAs that mean something

    Response times, uptime, and a human who picks up.

  3. 03

    AI-specific monitoring

    Model behaviour, cost control, drift detection and prompt-injection alerting, because AI systems fail differently from classic software.

  4. 04

    Hard guarantees

    We are willing to be held to the result. We did that before AI, and we still do.

What the audit gives you

A risk report and a support proposal within two weeks. You will know what is broken, what it costs to fix, and what it costs to keep running.

Who it is for

Organisations that built something, themselves or with AI, that is now “finished”, and are discovering that production is where it starts. And organisations whose current supplier no longer takes responsibility.

AI systems fail differently

Classic software either falls over or works. An AI system keeps answering while it is already wrong, and that is an entirely different kind of failure. The model drifts away from reality because the data changes. Costs climb because someone lengthened a prompt. A user talks the system past its instructions.

None of those three takes a server offline, so none of them is caught by standard monitoring. That is why we also monitor model behaviour, cost per request, drift and injection attempts. Otherwise you discover the failure when a customer calls.

Taking over what is already built

More and more often something arrives here that someone else made. Sometimes by an agency that has shut down, sometimes assembled with AI in a few weeks. That can work perfectly well and still not be sustainable: no tests, no documentation, no idea what happens at the first peak.

We take such codebases over. First an audit with an honest verdict. Sometimes the answer is that rebuilding is cheaper than repairing. Then hardening, and then support with an SLA.

Being accountable

We are willing to be judged on the result. That is not a new AI promise: it is how we worked with ANWB, ING, KPN and the Dutch Postcode Lottery for fifteen years. Technology changes, responsibility does not.

Is your AI stuck between demo and production?

In two weeks you will know what it takes to make it run: concrete advice, a risk report and a price.

Have your system audited