Enforcing data residency means ensuring that prompts, retrieved context, and outputs are processed and stored in approved regions and under your organization’s policies. With a hosted model API, you typically enforce residency through your vendor’s region controls (if available), contractual terms, and your own architecture: where your services run, where you store logs, and what content you send to the model. Start by classifying data: what is allowed to leave your network, what must remain in-region, and what must never be sent to external services.
Architecturally, minimize the sensitive payload you send. Use redaction for secrets and identifiers, strip unnecessary logs, and avoid sending full documents when only a snippet is needed. If you must keep everything within a strict boundary, consider a hybrid model: keep proprietary data in your own environment and send only non-sensitive summaries or extracted fields to the model. Also build an audit trail that records request metadata, access decisions, and retention policies without storing raw sensitive content unnecessarily.
Retrieval and vector storage are part of residency too. If you store embeddings and document chunks in Milvus or managed Zilliz Cloud, choose deployments that meet your residency requirements and enforce access controls at retrieval time. Filter by tenant, region, and policy tags so only authorized chunks enter the model prompt. This approach both reduces exposure and improves answer accuracy.