LLM data residency requires you to check where the content covered by your policy is processed and stored across the request path. Your application’s hosting region establishes only one part of that path. The prompt may leave that region through a provider connection, a fallback path or a secondary service. A useful LLM data residency review follows the request rather than stopping at your application's deployment region.
Start by expressing your organization's requirement as a set of questions. Which content is covered? Is the restriction about processing, storage, or both? Does it apply to derived records and attachments? Who can approve an exception? These questions turn an ambiguous requirement into something engineers can test.
Separate the locations you need to review
An internal AI application can involve several independently configured locations. Your application server has one location. An inference gateway has another. The provider may offer regional processing, regional storage, both, or neither for the exact features your application uses.
Your retrieval service, observability system and support tooling are also part of the data path when they receive covered content. A request can satisfy an inference routing constraint while an application log sends the prompt elsewhere. Inventory the systems that receive original content before assessing a specific provider.
Use a simple review table. The following entries are hypothetical and are questions to resolve, not endorsements of any provider configuration.
| Component | Evidence to obtain | Failure to test |
|---|---|---|
| Application | Deployment region and outbound integrations | Debug logging includes prompt text |
| Gateway | Environment region and allowed connections | A connection has the wrong declared region |
| Provider | Current account terms and feature documentation | A feature lacks regional processing |
| Retrieval | Index region and ingestion path | A document parser sends content elsewhere |
| Operations | Logging, export and support configuration | A troubleshooting export copies covered content |
Give every row an owner. An unowned assumption is likely to survive the first review and fail during an incident.
Check the exact provider configuration
Provider capabilities vary by feature and account. OpenAI's data controls documentation describes residency configuration and distinguishes it from other data controls. Assess the specific endpoint and features in your application instead of treating a provider-wide statement as proof for every request.
Amazon Bedrock makes another important distinction. Its cross-Region inference documentation separates geographic profiles from global profiles. Those profiles can route to different sets of processing locations. An SDK configured with a source region is therefore insufficient evidence of the destination set when a cross-Region profile is involved.
Record the identifiers of the actual accounts, projects, connections and inference profiles you approved. Keep the evidence with its review date. Repeat the review when those identifiers or enabled features change. Marketing descriptions alone are not a substitute for the applicable contract and configuration.
Make fallback preserve the boundary
Consider a hypothetical EU-only internal assistant. It can use two approved EU connections. If both fail, the correct operational result is an unavailable feature with a clear explanation. A global fallback would contradict the application's stated boundary, even if it provides a faster answer.
Write this behavior as an acceptance test. Disable the preferred destination, then every approved destination. Inspect all attempts and confirm that no request leaves the approved set. The test must inspect attempted destinations, not just the provider that returned the final answer.
Also include background paths. Summarization, evaluations and attachment processing can use different code from the interactive assistant. Inventory those paths explicitly. A routing rule in the chat handler does not automatically constrain a scheduled summarization job.
Review records independently from content retention
A request record and a prompt are different objects with different uses. Your operations team may need the model identifier, policy version, processing destination, timing and refusal reason. It may not need the user's original text.
Decide what each field reveals and where the records are stored. Opaque identifiers can still be linkable to people through other systems. A content-free record is not a reason to skip access control, deletion decisions or an assessment of the metadata itself.
Set separate expectations for temporary buffers, application state, audit evidence and backups. A statement that content is not retained in one system should not be presented as an end-to-end deletion guarantee. Document the boundary of the statement so another team can evaluate it correctly.
Produce a review that survives a configuration change
Your output should be an evidence table, an allowed-destination policy, failure tests and a named owner for changes. Include what you could not verify. Missing provider confirmation is an unresolved dependency, not a box that engineering should tick based on an assumption.
Alectura provides regional environments and policy-controlled provider routing; the regions and routing section describes that boundary. It can form part of the technical implementation, while the broader review still covers your application, other services and the terms of each provider connection.
This is an engineering review pattern, not a determination of regulatory compliance. Take the documented behavior to the people who own your organization's contractual and data-handling requirements. They need the actual permitted paths and evidence, rather than a general assurance that the application is hosted nearby.