Why keyword search misses your best candidates
An ATS that has collected candidates for years holds enormous value, but most of it sits in free text: interview notes, free-text fields and communication. A candidate who applied three years ago may be perfect for today's role, but is never found if mistagged or untagged.
How AI search by meaning works
- The talent base is read in: names and contact details are hidden before any AI tool sees the text.
- The recruiter describes the role in plain language, not as a boolean string.
- The search combines vector and keyword search to match on meaning.
- Every match shows why it appeared, so the selection can be audited.
What you gain
Most of a recruiter's time goes to finding candidates. By activating the existing talent base, the time from brief to shortlist shrinks and candidates that would otherwise be lost become visible again. It is often cheaper and faster than sourcing anew.