Candidate rediscovery
The best candidate for the next role is already in your database
Goodfit AI re-ranks every candidate in your history against every new role you open. The strongest fits surface before you ever post the job - including the silver medalists you would otherwise lose.
Senior Backend Engineer
Live pipelineTrusted by HR teams at 200+ companies
The hidden pipeline
Your best next hire is probably someone you have already met
Every company quietly builds a database of strong candidates who almost made it - finalists who lost to a better fit, candidates from a role that closed, applicants for a role you were not yet ready for. Most teams forget they exist. Goodfit makes that database the first place you look.
- Surface strong-fit candidates from your past pipeline before any new sourcing spend
- Re-engage silver medalists from finalist rounds you closed without offering
- Reuse the scorecard signal you already paid for, instead of re-screening from scratch
- Shorten time-to-hire by days on every requisition that has a backlog match
Review queue
Senior Backend Engineer · 4 ready
Priya Nair
Senior Backend Eng
Arjun Verma
Senior Backend Eng
Rahul Mehta
Senior Backend Eng
Sneha Sharma
Senior Backend Eng
How matching works
Re-ranked against the role, not against a tag
When a job opens, Goodfit re-ranks your candidate history against that role using both the structured signal (assessment scores, scorecard criteria, prior stage) and the unstructured signal (interview transcripts, written reasoning). The output is a ranked shortlist with reasoning attached - not a tag-filter result.
- Re-ranking uses past scorecards, transcripts, and structured signal together
- Written reasoning per match - why this candidate, against which criteria
- Excludes candidates already in another active pipeline to avoid double-touch
- Filters for recency so you do not re-engage candidates from years ago
Priya Nair
Senior Backend · 8.2 overall
"Walked through trade-offs before coding."
Source · 04:12
"Explained decisions clearly."
Source · 08:15
Silver medalists
Stop losing the candidates you almost hired
A silver medalist is a candidate who reached your finalist round and was not the chosen offer. Most teams thank-and-close them; weeks later, when a similar role opens, they have to source from scratch. Goodfit auto-flags silver medalists against every new requisition and prompts re-engagement.
- Auto-flag finalists from similar past roles as the role opens
- Templated re-engagement message preserves the original scorecard context
- Track silver-medalist conversion as a distinct sourcing channel
- One-click move into the new role pipeline with prior scorecard attached
Automation rule
ActiveIf
Then
Re-engagement
One-click outreach with context attached
A rediscovered candidate is not a cold lead - you have already interviewed them. Re-engagement messages auto-fill with the original context (role, recruiter, last stage) and route back through your standard interview flow so prior signal is preserved end-to-end.
- Templated WhatsApp, email, and SMS outreach with original context preloaded
- Recipients land in the same interview flow - no duplicate screening
- Prior scorecard attached to the new application as evidence
- Track response, completion, and offer rate per re-engagement campaign
Same interview. Every channel.
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One sourcing funnel
Rediscovery alongside referrals and new sourcing
Rediscovery does not replace sourcing - it sits next to it. New applicants, referrals, and rediscovered candidates flow into the same ranked recruiter queue with source clearly attributed. Reporting shows which channel produced which hire and at what cost.
- Rediscovered candidates appear in the same ranked queue as new applicants
- Source attribution on every candidate (rediscovery, referral, careers page, direct)
- Per-channel cost-per-hire reporting out of the box
- Auto-deduplication when a rediscovered candidate also re-applies directly
ATS + HRIS connected, both ways
Customer story · Springworks
Teams running Goodfit see rediscovery convert at rates competitive with referrals - because the candidates were already screened once.
Over the years, I've tried several assessment platforms, but most were either too expensive or too static. Their questions stayed the same, and candidates often copied answers. I wanted something more adaptive and real-time. Goodfit offered that flexibility at the right price point, so we decided to try it, and within hours, we saw great results.
80%
Faster hiring turnaround
341 days
Hiring time saved
What you get
Re-ranked
on every new requisition
Silver medalists
auto-surfaced for similar roles
Prior scorecards
preserved end-to-end
One queue
with new applicants and referrals
FAQ
Questions hiring teams ask about Candidate rediscovery
How is this different from a tag-based search of past candidates?
Will candidates be re-engaged automatically?
How recent is "recent enough" for rediscovery?
What happens if a rediscovered candidate also applies directly?
Does this work without our prior data being structured?
Is this counted as a separate sourcing channel for reporting?
Pairs well with
Teams that use Candidate rediscovery also use
See Goodfit in action
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