See where searches in your data sources come back empty, which files answers rely on and which sources nobody needs — and help search along with a glossary and file marks
Three tools show admins how the data sources are searched, and help search along:
The Knowledge search tab in the AI Cockpit sums up all Cloud data sources of the workspace for the selected period — the last 30 days by default, at most 90 days are evaluated:
| Section | What it shows |
|---|---|
| Searches, No results, Not searched | How often people searched, the share of searches that found not a single passage, and how many sources nobody searched |
| Searches per day | Searches over time, with searches without results highlighted |
| Where searches come back empty | Per source, the share of searches without results |
| Not searched in this period | Sources without a search, with the last search date and a "Sleep mode" badge if the source already sleeps |
| Most cited | Files that answers name as a source in their text |
In the list under Settings → Data sources, the Usage (30 d) column shows the same numbers per source for the last 30 days, for example "241 searches" with "36 % without results". "never searched" means the source was never searched at all; "no search in 30 d" means it was, just not in the last 30 days. You can sort by it.
How to read the numbers:
Note
No search terms. MeinGPT doesn't store what people searched for — only that they searched and whether anything was found. That's why there is no list of frequent or unanswered search terms. Every view is in the audit log.
What to do with it: If a source often comes back empty, documents are missing there, or they use other words than the questions — that's what the glossary is for. Sources nobody searches go to sleep mode on their own after 60 days; if you don't need them at all, you can remove them.
Open the glossary under Settings → Data sources with the Glossary · N terms button at the top right; it opens as a side panel. There you enter words that mean the same in your documents — for example KST and Kostenstelle, or company car and pool car. When someone searches for one of them, MeinGPT also searches for the others, and the assistant learns that they mean the same. This applies to every Cloud data source of the workspace from the next search on.
Suggestions from the assistant. When the assistant notices in a chat that your documents use another word — for example because a search for "KST" found nothing and one for "Kostenstelle" found the answer — it suggests an entry. A hint on the button counts waiting suggestions (for example "3 suggestions"); in the side panel they are at the top; they change search only once you accept them. A suggestion doesn't record who asked or in which chat.
Note
Applies to Cloud data sources. Outpost folders are searched by the device itself; the glossary has no effect there.
A Cloud data source's Knowledge map shows two lists below the map:
You find any other file in the Files tab through its file search and mark it the same way; marked files are listed below in a list of their own. Sources with permissions from the source switched on show no file names on the knowledge map.
Older editions of the same file in the same folder ("Policy_2022", "Policy_2024") are recognized without a mark. Marking pays off for everything the name doesn't tell.
Every change to the glossary and to marks is in the audit log.