EU AI Act risk intelligence
Your AI risk exposure, as one euro number your board can act on.
Margelis.ai turns weak signals — model incidents, vendor drift, regulatory movement, operational telemetry — into a single reproducible, euro-denominated risk figure. White-box from input to output. A human signs every number.
Estimated annual AI risk exposure — example
€1 420 000
band €0.9M – €2.1M · confidence 80%
EV-2026-031 · 14 signals · method v2.3 · reproducible from evidence file
White-box, end to end. No oracle scores.
Most AI risk tools return a traffic light or a 0–100 score you cannot audit. Margelis.ai works the other way: every number decomposes back to its evidence, and every step in between is inspectable.
Collect weak signals
Model and vendor incidents, audit findings, regulatory movement, internal telemetry, contract exposure. Each signal is logged with source, date, and weight.
every signal carries a source receipt
Quantify in euros
Signals map to loss scenarios through a documented, versioned methodology — frequency, severity, and exposure assumptions are all visible and challengeable.
method card published per version
Human signs the number
No figure reaches your board without expert review. The reviewer's name and the full evidence file ship with the number. Rerun it yourself; you get the same result.
human-in-the-loop · reproducible
The AI Act clock moved. The exposure did not.
The Digital Omnibus shifted key EU AI Act enforcement dates — but obligations for high-risk systems are coming on a fixed horizon, and supervisory expectations are forming now. Boards that can already state their exposure in euros enter that period negotiating; boards that cannot enter it reacting.
In force today
Prohibitions and AI literacy duties
The earliest AI Act obligations already apply. Inventory gaps here are findable in any due-diligence exercise — by regulators, insurers, or acquirers.
2027–2028
High-risk system obligations land
Under the revised Digital Omnibus timeline, the heavy compliance load for high-risk AI systems arrives in this window. Quantifying exposure now turns a future fire drill into a budget line.
Every quarter in between
Your AI estate keeps changing
New vendors, new models, new incidents. A one-off compliance report ages in weeks. A reproducible number can be rerun whenever the estate moves.
What lands on your board table
One pilot engagement produces a complete, audit-ready package — not a dashboard subscription you have to interpret yourself.
The number
Euro-denominated annual exposure with confidence band — one figure, defensible in front of auditors, insurers, and supervisors.
Evidence file
Every signal, weight, and assumption behind the number, in a form a third party can rerun and verify.
Method card
The versioned methodology document: what is modelled, what is excluded, and what would change the number.
Action register
The ranked list of interventions that reduce the number — each priced against the exposure it removes.
Built in the EU, on operating experience
Margelis.ai is built and operated by Rūpestėlis Holding UAB in Klaipėda, Lithuania — a holding that runs its own fleet of production AI agents alongside six veterinary clinics. The risk methodology was not written in the abstract: it is the same discipline we use to monitor, diagnose, and account for our own AI systems daily.
Data stays in the EU. The methodology is white-box by principle, not as a feature tier. And every number that leaves the house is signed by a human who can defend it.
EU-built · EU-hosted · human-signed
Get your first number in 30 days
A pilot covers one business unit or one AI estate: signal collection, first euro figure with evidence file, and a board-ready briefing. Write one sentence about your AI estate — we reply with a scoped proposal.
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