Choosing where a language model runs does not settle where an application’s information goes. A search query can contain sensitive context, and the retrieval provider becomes another participant in processing it. For teams with location and retention constraints, the search layer needs the same scrutiny as the model endpoint.
In an October 6 case study, Linkup says Aleph Alpha uses its search API in internal tools and customer-facing solutions. The account describes EU-hosted infrastructure and zero data retention, with search intended to fit the customer’s wider sovereignty requirements. It includes a named customer statement, but does not publish an independent audit or a controlled comparison of answer quality. Primary source.
Follow the request, not the label
The practical implication is a need to map the whole request path. A team should identify which information becomes a query, which service receives it, how results return and what is retained in application logs. A provider’s stated retention policy does not automatically describe the behavior of every integration built around it.
Nor does the location of processing resolve whether a result is a good source. Retrieval still needs freshness, relevance and attribution checks. A compliant path that returns stale information can support a wrong answer; a highly relevant source does not by itself establish that the processing arrangement meets the organization’s requirements. Both assessments matter.
Evidence for an integration decision
The first adoption test should combine representative queries with a documented data-flow review. The evaluation can compare supported answers and missed evidence while the operating team checks actual configuration against its requirements. This is a deployment assessment, not a conclusion that any particular legal obligation has been satisfied.
The customer account is useful because it identifies two concrete workflows rather than discussing sovereignty only at the model level. Its limits are equally important: the published narrative does not show request volumes, measured reliability or the full contractual arrangement.
Search providers that make these boundaries explicit could give specialized AI builders more options when assembling a controlled stack. The next evidence is operational documentation and repeatable service measurements for the intended workload. A customer case study is a starting point for that inquiry, not a substitute for it.
References
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