Identify every copy of the data and every service that receives it. Evaluate access, retention, provider terms, and operations for each component instead of relying on a hosting label.
1. Map the complete request and data lifecycle
List what enters the application: user messages, uploaded files, retrieved passages, account records, and audio where applicable. Then list which components receive it: application servers, model endpoints, extraction services, search indexes, telemetry, and support tools.
Include derived data. Extracted text, embeddings, cached responses, conversation history, and evaluation datasets may outlive the original upload. Record who owns each copy, who can read it, and how an update, permission change, or deletion should propagate. This map makes deployment choices concrete.
2. Review the actual managed-service configuration
A managed model API can reduce the work of serving a model, but the provider processes the information included in the request. Review the current service terms, account settings, supported regions, retention controls, and the features you plan to use. Avoid assuming that consumer-chat settings apply to an API project.
Check the client library and your own instrumentation as well. Tracing and debugging can capture inputs and outputs depending on their configuration. Decide what evidence is needed for support and evaluation without turning ordinary logs into an unrestricted archive of customer documents.
3. Account for the dependencies around a self-hosted model
Operating a model in your infrastructure creates responsibilities for licensing, compute, serving, updates, access, and monitoring. It does not automatically determine where embeddings, document extraction, search, or telemetry run. Assess those services independently.
Test the hardware and model on representative workloads before promising capacity or response time. A model that fits in memory may still be unsuitable under expected concurrency or quality requirements. Assign an operating team and a recovery process; self-hosting changes ownership of the work rather than making it disappear.
On small screens, scroll the table sideways to see every column.
| Component | Question | Evidence to record |
|---|---|---|
| Model processing | Which endpoint receives request content? | Service, account, region, and settings |
| Retrieval | Who may read each source and index entry? | Access model and permission-change tests |
| Logs and history | Which inputs or outputs are retained? | Fields, access, retention, and deletion process |
4. Define the boundary in a hybrid design
A hybrid product may keep application records and search in one environment while sending selected context to a model API. Write down exactly what crosses that boundary. Removing a name does not necessarily remove identifying or confidential information from a document.
Use the minimum useful context, supported data controls, and application authorization. Review error reports and traces as part of the boundary. If a task cannot send particular information externally, that constraint must affect model and feature selection, not just the wording in a privacy notice.
5. Make the operating responsibilities visible
Assign owners for credentials, permissions, retention, provider changes, and requests to correct or remove information. Test deletion and access changes across the systems in your map. Verify that a former user cannot continue retrieving a document from an old index or cached application result.
Record the choices as part of the project design and revisit them when adding a provider, tool, source collection, or new data type. These technical checks inform your organization’s privacy and contractual review; they do not establish universal regulatory compliance.
6. Frequently asked questions
Is a privately hosted web application also a privately hosted AI model?
Not necessarily. The application can run in your network while calling an external model, embedding, search, or transcription API. Map each component and the data it receives.
Are embeddings automatically anonymous?
Do not assume that. Treat derived representations according to the information they come from, the access they enable, and your organization’s handling requirements.
Does disabling one logging option stop all retention?
No single setting establishes that. Review provider behavior, application logs, traces, storage, caches, histories, and backups separately for the features you use.
7. Related articles and next steps
Bring representative inputs, expected outputs, and the systems involved. Discuss your requirements with OdooMatrix.