Turn the EU AI Act from legal text into a concrete plan — risk classification, documentation and oversight, translated into normal engineering work.
The EU AI Act is now law, and it phases in over the next few years with real penalties for non-compliance. If you build or deploy AI that touches EU users, it applies to you — and the obligations depend on which risk category your system falls into. Getting that classification wrong in either direction is costly: too high and you burden a low-risk product with needless process, too low and you ship something that is quietly non-compliant.
The practical problem is that the Act is written in legal language, while your team works in code and models. Most of the requirements — risk management, data governance, technical documentation, human oversight, transparency — translate into concrete engineering and process work, but someone has to do that translation. Left too late, it becomes a scramble; done early, it is mostly straightforward.
Beyond avoiding penalties, credible governance is increasingly a commercial requirement. Enterprise customers and public-sector buyers now ask for it in procurement, and being able to show documented, well-governed AI is becoming a way to win business rather than merely a box to tick.
We start with a classification: we assess each of your AI systems against the Act's risk categories and tell you plainly which obligations apply and which do not. This alone often removes a lot of anxiety, because many systems turn out to be lower-risk than teams fear, and the ones that are not become clearly scoped.
From there we translate the applicable obligations into a concrete plan — the documentation, the data governance, the human-oversight mechanisms and the technical measures — and help your team implement them as normal engineering work rather than a separate compliance silo. Where we are engaged for evaluation or observability too, that evidence feeds directly into the conformity documentation.
We are engineers, not a law firm, and we will say so: for formal legal sign-off you will still want qualified counsel. What we provide is the technical and process translation that makes their job — and yours — straightforward.
Assess each system against the Act's categories, clearly.
Produce the records the Act requires.
Document data sources, quality and lineage.
Design meaningful oversight into the workflow.
Meet disclosure and labelling duties.
Assemble the file for high-risk systems.
We inventory your AI systems and how they are used.
We gather documentation, data sources and oversight already in place.
We classify each system against the Act's risk categories.
We map obligations and build the documentation and mechanisms.
We validate the evidence against the requirements.
We hand over a maintainable compliance file and guidance.
We use structured governance frameworks and connect them to your actual systems, so compliance is evidence-based rather than a paper exercise.
If you build or deploy AI touching EU users, very likely yes — but the obligations depend on risk category. We assess your systems and tell you plainly what applies.
No, we are engineers. We do the technical and process translation of the Act; for formal legal sign-off you should use qualified counsel, whose job we make easier.
Often lighter obligations apply, like transparency. We confirm your category so you neither over- nor under-invest.
Where we also run evaluation or observability, that evidence feeds directly into your conformity documentation.
Compact, efficient models that run at the edge — low latency, full privacy.
Privacy-safe training data at scale — augment, balance, and unblock ML.
Benchmark, stress-test and adversarially probe models before they ship.
Book a 30-minute call. We will tell you honestly whether we can help.
Book a call