Ctrl+F is broken. Keyword search is one of the most frustrating experiences in modern software. If you search an internal wiki for "vacation policy," but the HR Director named the file "Time Off Guidelines 2025," you find nothing. The computer sees "Vacation" != "Time Off".
Semantic Discovery
Vector Search (Semantic Search) solves this. It indexes the *meaning* of the document, not just the words. It knows that "Vacation," "PTO," "Time Off," and "Holiday" are all semantically related concepts.
User: "How do I book a flight?"
Vector DB: "I found a document called 'Travel & Expense Policy' which contains a section on 'Air Travel Booking'. Here it is."
The "Zero-Click" Search
The best search doesn't actally give you a list of links (blue links). It gives you the answer.
Instead of "Here are 10 PDFs about travel," the AI says: "To book a flight, log in to Concur using your SSO. Expenses under $500 do not need manager approval." It extracts the needle from the haystack.
Solving the "Knowledge Silo"
Every company has "Tribal Knowledge"—information that isn't written down, or is buried in Slack threads. By indexing Slack/Teams history (with privacy controls), Semantic Search enables "Organizational Memory." You can search for: "Who worked on the Project Apollo migration last year?" and it will find the engineers who were chatting about it, even if there is no official project doc.