Open WebUI

Map sign-in, administrator roles, model selection, prompts, uploaded files, and generated responses from browser to backend. Put Open WebUI behind the organisation's approved identity and network boundary. Restrict administrative access separately from normal chat use. Keep a controlled recovery route, test offboarding, and identify the owner who can approve a new model endpoint or integration.

Prompts and uploads may contain source code, customer identifiers, security details, or internal plans. Set a written policy for permitted use, retention, deletion, export, and incident review. Test what data is stored by the configured instance and what is passed to each backend. A model endpoint outside the controlled boundary may introduce a separate processor, contract, or jurisdiction question.

Store backend credentials in a controlled secret mechanism. Scope each credential to one endpoint where possible and prevent browser users from receiving it. Network egress rules should allow only approved inference services. A local interface that can send prompts to arbitrary internet endpoints is not a private AI boundary.

Model integrations differ in authentication, API shape, context handling, error messages, and data location. Validate each one with a standard prompt set that contains no sensitive production content. Check model selection, an expected failure response, rate or capacity handling, and the information shown to a basic user. Keep an inventory of endpoint URL, owner, model family, approval status, and test date.

File and knowledge features need a separate review. Identify file storage, extraction or embedding services, indexes, and downstream model calls. A document marked private in a source system does not automatically stay private after copying it into an index. Test permissions with ordinary accounts and remove test material after the exercise.

Read current release guidance before upgrades. Capture persistent application data according to the documented deployment method, test login and a representative model connection in a non-production environment, and have a rollback criterion. Recheck retention and integration settings after a version change; defaults and compatible features can change.

Monitor browser availability, authentication failures, model endpoint failures, storage growth, and unusual upload or request patterns. Pair those signals with backend capacity monitoring. A user reporting that chat is slow may be seeing a queue at the inference server, a network path issue, or an oversized request; the runbook should show how to distinguish them.

Give the service a named product owner and technical owner. The product owner decides intended use and approved data; the technical owner manages access, updates, backup, and incident handling. Endpoint owners are responsible for their runtime. That separation avoids the common handoff where everyone assumes another team has checked a provider change.

Acceptance should show a restricted user signing in, reaching only an approved model, completing a safe test prompt, and failing to reach an excluded endpoint. It should also show an administrator reviewing retained content according to policy and restoring the agreed persistent configuration in an isolated exercise.