Solution · AI Operations
Comply with AI regulation while running your AI: classify risk, document and keep conformity a living function, not a PDF you sign once
AI compliance isn't won with a consultancy and a report that goes in a drawer. Your AI systems change model, data and use every month, and conformity has to move with them: classify each one by risk, document it, put oversight where the rules require it, keep evidence and manage incidents. If you sell into the EU, that's the EU AI Act; in the US it's the emerging frame — the NIST AI Risk Management Framework, state laws and your sector's regulator. Either way it's not a project that ends; it's an operation you keep. We build it and we run it.
The problem
You have AI in production and regulation closing in, but your compliance is a months-old report that no longer describes what runs today
- Nobody has the list of which AI systems are live or which count as "high-risk" under the rules — so you can't even start classifying what regulation asks you to classify.
- The technical and conformity documentation, if it exists, was done once and no longer matches the real model, data and use of today: the system evolved and the paperwork stayed behind.
- The human oversight the rules require on high-risk systems is "in the air": nobody has defined where a person steps in, on what criterion, or with what trail that they reviewed.
- If an auditor calls tomorrow — or an incident hits — there's no evidence to show: no decision logs, no model versions, no record of who oversaw what.
Cost of staying the same
Fake compliance doesn't fail the day you sign it: it fails the day an auditor asks for evidence, or a system makes a decision about a person and you have to prove there was oversight and there wasn't. AI rules phase in over time and obligations grow with a system's risk; being late isn't a warning, it's exposure — fines tied to revenue in the EU, a system you have to pull, an enterprise customer that drops you from the process because you can't evidence compliance. And the underlying cost is silent: every month your AI changes and compliance doesn't move with it, the paper you hold describes a system that no longer exists.
The solution
We build AI compliance over your systems —classification, documentation, oversight and evidence— and keep it alive as your systems change
- 1We inventory and classify: which AI systems are live and which risk category the rules put them in (prohibited, high-risk, limited, minimal). That's what tells us which obligations apply to each and where to start.
- 2We build the technical and conformity documentation the rules require for high-risk systems —purpose, data, limits, risk assessment— and keep it wired to the real system, not in a loose doc that expires at the first version.
- 3We set up human oversight where the rules ask for it: who reviews, on what criterion, which actions need a person's sign-off, and with a trail that the review happened — so "there is oversight" is demonstrable, not a statement.
- 4We run continuous compliance: evidence and logs ready for an auditor, model version control, incident management with an owner, and reclassification when a system changes use. We run it, or we hand it to you documented.
What changes
What you stop losing
Compliance stops being a report with an expiry date: each system is classified by risk and its documentation moves when the system moves, not six months later.
Mechanism
The human oversight the rules require goes from "someone supposedly watches" to a defined control point with a trail, so "there is oversight" can be shown, not just claimed.
Mechanism
An audit — or an incident — stops being a scare: the evidence, the decision logs and the model versions are ready to open, not to reconstruct from memory.
Mechanism
What we measure: AI systems classified by risk vs the total, documentation-current coverage per high-risk system, sensitive actions with logged human oversight, and time to detect and close incidents.
What we measure
Spec sheet
- Work it removes
- treating AI regulatory compliance as a one-off report instead of keeping risk classification, documentation, oversight and evidence alive as your AI systems change
- Typical setup
- 3–6 weeks for the build; continuous compliance from day one
- Input
- your AI systems in production, their real use, their models and data, and access to their logs
- Output
- AI compliance operating: systems classified by risk, technical documentation kept current, human oversight with a trail, and evidence ready for an audit
- Works with
- AI systems in productionLogging & observability stackGRC stack
- Can connect to
- Your logging and observability stackYour GRC and document stackImplementa's AI compliance framework
- What we measure
- AI systems classified by risk vs the totaldocumentation-current coverage per high-risk systemsensitive actions with logged human oversighttime to detect and close incidents
- Good fit for
- companies with AI in production that falls under AI regulation —especially high-risk systems or ones that assist decisions about people— and need compliance as a continuous function, with evidence that survives an audit, not a one-off report
- Not a fit for
- those after a certificate or a badge with no compliance operated behind it, or those with no AI system in production yet to classify and document
Frequently asked questions
The focus. Governing the fleet is the broad control layer — what each agent can touch, permissions, cost, audit — and regulatory compliance is one facet inside it. This is more specific and deeper in that facet: complying as a function — classify by risk, document, oversee where the law requires it and keep evidence — over your AI systems, agents or not. If what you need is the general control of your fleet, that's our other solution, governing your company's AI agents; this one focuses on surviving the rules.
It depends on what your AI does and where you operate, not on whether you call it "AI". If you sell into the EU, the EU AI Act classifies systems by risk and loads obligations on high-risk ones. In the US there's no single AI Act yet, but the NIST AI Risk Management Framework, state laws and your sector regulator already set expectations — and enterprise buyers ask you to evidence them. First thing we do is classify your systems to tell you exactly what applies, instead of you guessing.
No, and that's the point. An AI system changes model, data and use, and each change can move its risk classification and its documentation. If compliance is done once, it expires at the first new version. That's why we run it as a continuous function: compliance keeps pace with your AI, it doesn't freeze in last quarter's report.
Want it running in your business?
You’ve pinned the problem. We ship the fix and leave it measured.