Knowledge base search for your whole company: search knowledge base articles, wikis and chat at once

Because the knowledge is not in the knowledge base. Every company that has run this exercise finds the same split: the documented answer exists for perhaps a fifth of the questions people actually ask, and the rest live in chat threads, ticket resolutions, email replies and comments on a doc nobody reopened.

Native search inside a wiki is generally fine at its job. The failure is one of scope, not relevance. Confluence search does not know your Slack exists, and a help desk search cannot read the Drive folder where the runbook was actually written. Fixing this means one index across all of them, not better queries inside one of them.

Connect the sources, build one index, and enforce permissions at query time. In practice that means an OAuth connection to each system, an initial crawl that normalizes very different content types into comparable records, then incremental syncs that pick up changes. A cross-app tool finishes the first index in hours to a couple of days depending on volume.

The step people skip is deciding what should not be indexed. Personal drives, HR case files and anything under legal hold usually need excluding by policy rather than by permission. Draw that line before the first crawl, not after someone finds a document they should never have seen in a result.

It has to, and the mechanism matters. Permission-aware search checks each source system's own access controls when the question is asked, so a document is excluded because you cannot open it in Confluence right now. The weaker approach copies permissions into the index on a schedule, which means a revoked user keeps seeing content until the next sync runs.

Ask any vendor how long that gap is. It is a straightforward number and it is the answer your security reviewer needs. InSearch enforces the source permissions on every query, which is the design behind permission-aware AI search.

Consolidation projects are worth doing for documentation you actively maintain, and they fail as a search strategy. The reason is arithmetic: knowledge is created continuously in whatever tool the work happens in, and a migration only fixes the backlog that existed on the day it ran. Six months later the split is back.

The better division of labor is to keep curating the documents that deserve curation, and let search reach everything else where it sits. That way nobody has to copy a Slack decision into the wiki for it to be findable, which is the step that never reliably happens anyway.