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AI and residency

Where does model inference run, and what leaves with it?

A detection pipeline hosted entirely in the EU that sends alert context to a model endpoint elsewhere has moved customer data across a border without moving anything on the architecture diagram. That is not a hypothetical failure mode; it is the default shape of most AI-driven security tooling, because the model layer was added to products whose data-residency statements were written before it existed. The payload is not metadata either. Alert context is the interesting part of the alert: hostnames, usernames, file paths, command lines, sometimes the contents of a suspicious document. This page sets out the hops that exist in a model-driven security platform, which of them are usually covered by a residency statement, and the four questions that have documented answers.

Extra hop
Inference
Payload
Content
Usually covered
No
Questions
Four
Written byRobin ÖsterdalFounder & CEOReviewed byMalthe Bang NorengaardCo-founder & CTO

Reviewed against EUR-Lex, NIST and the EDPBLast reviewed 4 min read

Kort sagt

  • Model inference is a separate contract in a separate location from the rest of the platform.
  • Alert context is customer content, not metadata: hostnames, usernames, command lines.
  • Residency statements often predate the model layer and do not cover it.
  • Retention of prompts and outputs is a second question, distinct from where inference runs.
  • Bring-your-own-model shifts the question to your own contract, which is usually an improvement.
  • Four questions have documented answers. A vendor who cannot give all four has not decided them.
The hops in a model-driven security platform
HopWhat crossesTypically in the residency statement
Agent to collectorEndpoint telemetryYes
Collector to storageRetained eventsYes
Storage to analysisCorrelated contextUsually
Analysis to model endpointAlert context, often verbatimOften not
Model endpoint to platformReasoning and verdictOften not
Prompt and output retentionWhatever the provider keepsRarely addressed
Support accessWhatever an engineer can readRarely addressed

Källa: GDPR Chapter V, EUR-Lex

Why this hop is different from the others

Every other hop in a security platform was designed by the vendor and appears in their architecture. The model hop is frequently a call to somebody else's API, which means it is a subprocessor relationship with its own terms, its own regions and its own retention behaviour.

That has a practical consequence: the answer can change without your involvement. A vendor switching model providers for cost or quality reasons has changed where your alert context goes, and unless the subprocessor list is change-controlled you will find out when you next read it.

It also has a contractual consequence. Your data processing agreement with the vendor covers the vendor. Whether it flows down adequately to the model provider is a separate question, and it is the one worth asking in writing.

Run the analyst on Anthropic, or an EU-hosted model that meets your residency rules.

What is actually in the payload

It is tempting to treat model calls as metadata traffic, and for some product analytics that is fair. For security triage it is not.

To form a useful verdict a model needs the specifics: which account, which host, which process, which parent process, which destination, and often the text of whatever looked suspicious. That is the same material that makes the alert worth investigating, and it is customer content by any reading.

It can also include material you did not intend to send. A suspicious document attached to a phishing alert, a command line containing a credential, an error message quoting a database row. None of that is exotic, and all of it travels with the context.

Why the payload is rich

60 %
of European cases began with social engineering, whose alerts carry message content

Källa: ENISA Threat Landscape 2025

21.3 %
began with vulnerability exploitation, whose alerts carry host and version detail

Källa: ENISA Threat Landscape 2025

68.6 %
of recorded intrusions led to a data breach, which is what the context describes

Källa: ENISA Threat Landscape 2025

The four questions

Which model, named, and whether you are told when it changes. Model identity matters less for sovereignty than provider identity does, but a vendor who will not name it usually cannot name the rest either.

Which provider operates the endpoint, and under whose contract. This is the sovereignty question proper: it determines which legal orders reach the inference layer.

Which region executes inference. Distinct from where the provider is headquartered, and distinct again from where the vendor is hosted.

Whether prompts and outputs are retained, by whom and for how long. A zero-retention arrangement is a materially different exposure from a thirty-day one, and the difference is contractual rather than technical.

Three arrangements, three exposures
Vendor's own choiceopaqueEU-hosted modelvendor contractsBring your ownyou contract
You know which provider~
You control the retention terms
Provider can change without you~
Inference region is contractual
Adds a procurement burden
Cost is visible to you~

Bring-your-own is not automatically better. It moves the relationship to your own paper, which helps sovereignty and adds work. The right choice depends on whether you have the procurement capacity to use it.

Källa: NIST AI Risk Management Framework

How this interacts with the regulations

If the context contains personal data, and in security telemetry it almost always does, a transfer outside the EEA needs a lawful mechanism under GDPR Chapter V like any other transfer. The model layer is not a special case, it is just an easy one to overlook.

Under NIS2 Article 21 the vendor's dependencies are inside your supply chain assessment, and the model provider is a dependency. Under DORA Article 28 financial entities need contractual terms including where the service is provided from, which reaches the inference layer through the vendor.

The AI Act adds obligations that vary with the risk class of the system, and whether a given security tool falls into a regulated class is a legal assessment for your organisation. It is worth noting that none of these requires the inference to happen in the EU. They require you to know where it happens and to have a basis for it.

Questions

Common questions

Does AI security tooling send our data outside the EU?
It can. Alert context is usually sent to an inference endpoint that is a separate contractual arrangement in a separate location, and residency statements written before the model layer often do not cover it.
Is alert context personal data?
In security telemetry it almost always contains some. Usernames, hostnames, command lines and message contents are the specifics a model needs to form a verdict.
What should we ask about inference?
Which model, which provider operates the endpoint, which region executes inference, and whether prompts and outputs are retained, by whom and for how long.
Is bring-your-own-model better?
For sovereignty usually yes, because the relationship moves to your own contract. It also adds procurement work, so the right answer depends on your capacity to use it.
Does any regulation require EU inference?
No. GDPR Chapter V, NIS2 Article 21 and DORA Article 28 require you to know where processing happens and to have a lawful basis and contractual terms for it.

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Further reading

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We will go through your requirement and the questions worth asking, including the ones where our own answer is inconvenient. Half an hour, no preparation needed.