Interesting. Does this actually scale though ? I've never seen enterprises which have "internal knowledge" in proper readable form - it's often in code, and more importantly in people who wrote them.
I recall that even at Google - with its own search engine and so on - the best way to understand anything was to read code or to reach out to those who wrote them. I don't know how it works in places that work with the "real world" like ASML.
Often the issue is not even about documentation - it's just that it's extremely hard to include all the nuances in text and still have it be readable (code-documentation comes to mind).
Interestingly, I strongly feel that this also where LLMs (and some of our more textually-obsessed academics) fail.
My sense is that it sounds amazing in theory to executives who have never had to themselves look at internal data. In reality the internal knowledge base is a mix of incomplete, inaccurate, self serving lies, out of date and so on. At worst, the data is explicitly biased to hide reality from executives so the AI will look extra good to executives. Of course, a business that makes all tactical decisions based on lies is not going to do well.