Pillar 02

The AI Act is not a legal problem. It is a software problem.

Lawyers tell you what has to happen. We make sure it actually does: in the code, in the pipeline, in production. Transparency obligations, human oversight, logging and documentation: we build it in from day one, so compliance is not a brake but a given.

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What we do

  1. 01

    Risk classification

    Does your application fall under prohibited use, high risk, or the transparency obligations of Art. 50? We map it and document the reasoning.

  2. 02

    Compliance as code

    Mandatory AI disclosures, opt-outs, logging and traceability as parts of the system that cannot be bypassed, not as a policy document.

  3. 03

    Audit-ready documentation

    Technical documentation, data provenance and model choices recorded the way regulators want to see them.

  4. 04

    Making existing systems AI Act-proof

    Assessment and remediation of AI features built before enforcement began.

From practice

For an AI outreach platform we implemented a mandatory, non-bypassable AI disclosure field under Article 50. Compliance enforced by the software itself, not by a user manual.

Who it is for

Organisations using AI in a customer-facing or decision-making process who need to be able to prove it holds up.

A PDF does not make you compliant

Most AI Act projects end in a document: a risk analysis, a policy paper, a manual explaining what users must do. That is usually where it stops, and that is exactly where it goes wrong. An obligation that only exists in a manual is broken by the first user who does not read the manual.

We build the obligation into the system. An AI disclosure you cannot switch off. Logging that is not optional. A human approval step you cannot skip because today is busy. Then compliance is no longer a promise about behaviour, but a property of the software.

What a regulator wants to see

In an audit it is not about your good intentions but about your records: which model, which version, which data, which trade-off, who approved what and when. That kind of information cannot be reconstructed afterwards. We make sure the system already keeps it before anyone asks.

Also for what is already there

Many AI features were built before enforcement started. They do not have to go, they have to be reviewed. We run an assessment, name what is not in order, and fix it. With a report you can hand to your board or your auditor.

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.

Request an AI Act quick scan