What it is
Candidate rediscovery is the practice of searching your own ATS or CRM for candidates you already know, rather than starting a new search from zero every time a brief lands. It covers anyone previously in your pipeline: past applicants, prior interviewees, silver medalists who nearly got an offer, placed candidates who might move again, and people sourced for a role that never closed. The database already holds them. Rediscovery just means going back to look.
It is more than a keyword search over old CVs. A genuine rediscovery match combines the stored profile with everything else on file: what role they were considered for, how far they got, what feedback the client gave, and how long ago you last spoke. Two candidates with an identical CV are not equally rediscoverable if only one of them has a warm history attached to their record.
The fastest hire is rarely a new name. It is one already sitting in your database, waiting to be looked at again.
Why it matters
The share of hires sourced from an agency's own CRM or ATS, rather than a brand-new search, has climbed sharply: from around 29% in 2021 to 44% by 2024, according to Gem's sourcing research. Most desks are sitting on more supply than they realise. They are simply not looking at it.
The problem is not a lack of data, it is a lack of retrieval. Most consultants can hold only a few dozen names in working memory, and an ATS search box was built for keyword filtering, not for surfacing someone who was strong for a similar role eight months ago under a different job title. Every candidate who goes back into the database without a plan to resurface them is a placement that gets re-sourced from scratch next time, at full cost, when the answer was sitting in row four thousand of your own system the entire time.
How boilr handles it
boilr treats your existing candidate base as inventory, not archive. Every candidate who has ever touched a search, whether they were placed, rejected, ghosted or simply parked, stays live in the Company Brain along with the context of that process: the role, the stage reached, the feedback given, the skills confirmed. Nothing depends on a consultant remembering a name.
When a new job order comes in, your AI sales employee matches it against that stored base automatically, not only against fresh sourcing, and surfaces the candidates worth a second look: silver medalists, prior applicants, anyone who fits on skills and seniority. It drafts the re-engagement outreach as a task, referencing the earlier relationship directly, so what would have been a cold approach starts warm. You verify and send. The search that used to start at zero now starts with names already on the table.
