How to keep enterprise knowledge search updated with new data

“Updated” can mean the source accepted a write, the connector fetched it, the index stored it, or a user can retrieve it. Those moments are different. Name the service-level target for the workflow and measure each transition.

For a policy search, a same-day update may be adequate. For a customer or safety workflow, a stale answer may be unacceptable. The right target depends on consequence, source behavior, and the cost of blocking an answer while refresh is uncertain.

A full re-index can be simple but expensive and slow. An incremental route uses change notifications, delta tokens, or a modified-time watermark to fetch only the affected records. Microsoft Graph change notifications are one example of an event signal that tells a client a resource changed; the client still needs to fetch the current data and handle lifecycle and subscription limits.

Keep a reconciliation job that scans the source for missed changes. Persist the checkpoint only after the affected records are processed, and make the range replayable. If the connector fails halfway through, the next run should not silently move the watermark past the missing records.

Search freshness is also an authorization problem. A newly indexed record that appears to the wrong employee is a failure even if its text is current. Copy the source access model into the index or perform a reliable query-time check, then test revocation and group changes.

Deletion needs the same attention as creation. Remove the record from lexical and vector indexes, cached snippets, generated summaries, and result pages according to the retention policy. An archive hidden from the source can still leak through an old embedding if the deletion path is incomplete.

If a required source is overdue or a connector has failed, the user should not receive a normal-looking answer with no warning. Show the freshness state, cite the last checked time where appropriate, and route the question to a human or an approved fallback when current data is required.

Do not solve an index outage by silently widening the source set. A fallback can be useful, but it should name the source and its limitations. This is especially important when an AI answer combines current and old records.

Use one test record and run the full cycle: create it, edit it, revoke a user's access, delete it, deliver the same event twice, and stop the connector during processing. Check what a permitted user sees, what a revoked user sees, and how the system reports an incomplete refresh.

The continuous update trigger design guide covers the event and processing controls. This page focuses on the search contract and user-visible freshness state.