Candidate Rediscovery

Candidate rediscovery uses AI to search an existing ATS database semantically — finding candidates whose profiles match a new job description even when the exact keywords differ — rather than requiring recruiters to remember and manually search for past applicants. In practice, organizations with 2 to 5 years of ATS data have a substantial warm candidate asset that is rarely utilized: past applicants who were strong but not quite the right fit for a previous role often become excellent matches for a subsequent one. The most common barrier is data quality: ATS records that were never properly tagged, have missing information, or have not been updated since the original application are difficult for any matching system to use effectively.