Is candidate rediscovery software different from the search feature already built into our ATS?

Yes, in most cases. Built-in ATS search typically requires a recruiter to manually enter keywords for every search, while dedicated rediscovery software scans your full database automatically and scores results against a specific job's requirements.

The distinction comes down to three mechanics. Built-in search waits for a recruiter to open it and type a query, while rediscovery software starts scanning automatically the moment a new job gets created. Built-in search generally matches exact keywords or filters like job title and location, while rediscovery software evaluates skills and experience in context, so a candidate who wrote "data analysis" still matches a role requiring "business intelligence." Built-in search returns a filtered list, while rediscovery software returns a ranked list with a numeric score and specific reasons explaining each match.

Some ATS platforms include partial native rediscovery. Greenhouse's Past Candidates tab and Lever's Nurture Recommendations both surface past applicants using saved filters or scorecard data, but neither assigns a score against your current job's actual requirements, and neither triggers automatically for every new role.

However, software like Skima AI works alongside these native tools rather than replacing them. Teams typically use a platform's built-in search for a quick manual check on live applicants, then use Skima AI's Talent Rediscovery for a scored, automated scan across the full database, including candidates from closed requisitions that the built-in search does not surface.

If your ATS's built-in search already scores candidates automatically against new job requirements without manual triggering, a dedicated tool may add less value. Most mid-size companies find their built-in search stops short of that.