Risk classification
Establish which class each system falls into, and record the reasoning — the part most likely to be challenged first.
EU AI Act
Regulation 2024/1689 applies by risk class rather than by sector. What you owe depends on what your system does and how it is used — and the first task is proving which class you are in.
Coverage
In short
The Act sorts AI systems into prohibited, high-risk, limited-risk and minimal-risk categories. Most of the substantive duties — risk management, data governance, technical documentation, logging, human oversight, accuracy and robustness — attach to the high-risk tier, with transparency duties reaching further down.
Unlike ISO 42001 this is law, with penalties attached and no certification to opt into. Classification is therefore the first piece of work, because it decides the size of everything after it.
Where the platform helps
Establish which class each system falls into, and record the reasoning — the part most likely to be challenged first.
Drafted against the specific articles it has to satisfy, and kept current as the system changes.
Evidence about training and validation data drawn from the registries and pipelines that already hold it.
Show that a person can intervene, and that the intervention is recorded rather than assumed.
A trail behind each conclusion: what triggered it, what was observed, what changed and who approved it.
Evidence expires and is re-gathered on a schedule, so the record describes the system running now.
Regulatory change against the Act is tracked continuously, and each change names the controls, policies and evidence it affects.
Alongside
Evidence is credited across every framework that asks for the same proof, so overlapping programmes cost far less than running them separately.
Next / evaluate the platform
We will walk through the platform against your own governance and compliance needs, and what getting to audit-ready would take.