A recruiter opens a new job in Recruiterflow. Whether anyone checks the existing database against it depends on that recruiter remembering AIRA Matchmaker exists and choosing to use it before sourcing starts. Nothing happens automatically if it's skipped. A near-identical role filled six months ago has no record connecting it to the candidates who almost got an offer.
This expert guide covers what tools Recruiterflow offers for finding qualified applicants inside your own database. It also covers where those native tools fall short and how an AI integration fills the gap.
What Is Candidate Rediscovery?
Candidate rediscovery means matching people already inside your Recruiterflow database against a role that just opened. It covers candidates from closed jobs, profiles flagged as probable duplicates that nobody merged, and people your team added through the Chrome extension but never processed for a role.
Your database becomes a real placement source once those past candidates get matched against new openings automatically. Recruiterflow's AIRA Matchmaker and AIRA Search already do this kind of matching, but only when someone opens a job or types a query and asks for it.
Does Recruiterflow Provide Candidate Rediscovery?
No, Recruiterflow does not provide an automated candidate rediscovery feature. Its native AI tools get close, though. AIRA Matchmaker opens against a specific job: a recruiter clicks Generate, edits natural-language criteria, and gets a ranked list scanned across the whole database. You can click in to see which criteria drove the match.
Furthermore, AIRA Search works the same way through a typed natural-language query instead of a job, reading resumes, notes, and call transcripts, not just structured fields.
Both require someone to initiate them, either for each job or query, and neither is automatically included at every plan tier. The database does not scan automatically when a new job is created. A candidate must be manually searched for each new role, even if it is nearly identical to the previous one.
How to Rediscover Candidates in Recruiterflow
Since AIRA Matchmaker and AIRA Search still need a person to activate them for each job, most agencies connect Skima AI to automatically search and score the entire ATS database. This helps to bring back past qualified candidates. Below is a 5-step workflow, from connecting your account to acting on the results:
Step 1: Connect Your Recruiterflow Account With Skima AI
Get an API key from a Recruiterflow account owner under Settings → API Access, and configure webhooks to send candidate and job events to Skima AI's webhook URL. This connection uses Recruiterflow's own API directly, with no middleware required.
- Read access: Candidate, Job, and Application records, plus resume attachments
- Write access: Candidate tags, comments, and custom fields
- Pulled data: candidate contact details, resumes, and job descriptions for scoring context
- Optional webhooks: trigger scoring the instant a candidate or job record updates
If webhooks are not enabled, Skima AI falls back to safe polling every 10 to 15 minutes.
Step 2: Create Tags and Custom Fields, Then Confirm the Connection
Create a Skima Screened tag and the custom fields Skima AI writes to, or let Skima create them during setup. These are Skima AI match score, a number from 0 to 100, and reasons, a short block of text.
If your Recruiterflow instance restricts custom fields, Skima AI falls back to writing a candidate comment or attaching a SKIMA_Evidence.pdf instead. Optional HM Feedback and Comment fields capture manager or client responses once a shortlist goes out.
Before going further, test this on two or three jobs. Upload a resume, then confirm the Match Score and Reasons actually populate on that candidate's record.
Step 3: Launch Talent Rediscovery Against a Live Job
Open the job inside Skima AI, from the Jobs list or from within the job itself. Click the three-dots Actions menu and select Rediscover Candidates. A modal lets you scope the scan two ways. Limit it to a saved candidate segment, or leave it open to every candidate record Skima AI has synced from Recruiterflow.
Set the Candidate Created Date range next: All time, Last 6 months, Last 1 year, or a custom window. Click Apply. Skima AI scans the selected pool against this job's specific requirements and sends a notification once the scan finishes. Refresh the page to see the results.
Step 4: Review and Filter the Rediscovered Matches
Open the View Candidates tab to see a ranked list pulled from across your entire database. Each candidate carries an AI match score and reason bullets explaining the fit. Filter by Industry, Work Mode, Experience Level, Notice Period, Location, and Salary Range.
Start broad and tighten the filters gradually. Narrowing too fast hides good candidates. This step often catches candidates who were weak fits for an old search but line up well against this new one.
Step 5: Shortlist and Sync Feedback Back to Recruiterflow
Build your shortlist from the ranked matches Skima AI surfaced. Generate a secure, no-login link and send it to the hiring manager or client. They can click a thumbs up, thumbs down, or maybe on each candidate, with an optional comment.
Skima AI writes that decision back into Recruiterflow through the same API connection for the audit trail, logging the feedback as a candidate comment so it stays on the record without a second tool.
What If Your Recruiterflow Database Is Messy, Duplicated, or Stale
Recruiterflow already handles the cleanest tier of this problem automatically. If a new application matches an existing profile's email, phone number, or LinkedIn URL exactly, Recruiterflow attaches it to that existing record instead of creating a second one.
A looser tier catches the rest: matching name, current company, and current job title gets flagged as a probable duplicate, with a banner and a Merge button right on the profile.
Merging still takes a person clicking through that banner and confirming it, and it's irreversible once done. On a database that has grown for years across many jobs, sourcers, and Chrome extension imports, those probable-duplicate banners pile up faster than most teams get around to clearing them.
Moreover, Stale profiles carry the same problem more quietly, since nothing flags a candidate whose phone number or job title just went out of date. That isn't a duplicate, just an old record nobody's touched.
Skima AI treats this as ongoing maintenance rather than a one-time cleanup project. It matches on email, phone, or LinkedIn URL first, then checks name, location, and company together as a backup signal.
A field comparison modal flags exactly what differs before anything merges; missing details get filled in through contextual profile enrichment, and a dedicated Duplicates tab logs every resolved case across In Database, From Uploads, and Resolved sub-tabs.
5 Benefits of Candidate Rediscovery with Skima AI in Recruiterflow
Rediscovery with Skima AI changes what an agency can do with its own database in 5 clear ways:
- Faster Time-to-Screen: Rediscovered candidates arrive already scored, so recruiters skip the raw resume pile entirely. In a 30-day Recruiterflow pilot, a team reduced time-to-screen by 58%.
- More Interviews From the Same Shortlist: The same pilot saw interviews from the top shortlist double compared to the prior process.
- One Scan Regardless of Plan Tier: Skima AI's scoring works the same way no matter which Recruiterflow plan a job sits on, so the full database gets scanned without anyone needing a plan upgrade first.
- Automatic on Every New Job: Once enabled, a scan starts the moment a job is created, closing the exact gap Recruiterflow's own best-practice advice warns about: forgetting to check the database before sourcing fresh.
- Hiring Manager and Client Engagement Without a New Login: The shortlist feedback loop keeps managers or clients responding through a link, no Recruiterflow credentials required. Manager satisfaction rose 24 points on NPS in that same pilot.
5 Best Practices to Rediscover Talent in Recruiterflow
None of these benefits happen automatically inside Recruiterflow, the 5 practices below cover search timing, data hygiene, and fitting rediscovery around tools your team already uses:
- Use AIRA Matchmaker First on Jobs Where It's Available: If your plan includes it, generate AIRA matches at job intake, exactly as Recruiterflow's own help center recommends. Let Skima AI's Talent Rediscovery cover jobs and plans where AIRA Matchmaker isn't an option.
- Turn On Automatic Rediscovery for Every New Job: Skima AI's setting under Preferences and General starts a database scan the instant a new job is created. Enable it so no search starts from zero without a first look at your existing candidates.
- Clear the Probable Duplicates Banner on a Schedule: A candidate counted twice skews a shortlist and wastes a client's review time. Resolve Recruiterflow's own Merge banner regularly, not just when Skima AI flags a repeat.
- Use Reverse Search for Candidates Added but Never Processed: People sourced through the Chrome extension often sit without a job attached. Reverse Search starts from one profile and returns every open job they match, ranked by score.
- Segment Scans With the Candidate Created Date Filter: Choose a 6-month or 1-year window when a search needs someone recently active. Widen to All time for a niche skill set where the pool is thin.
Is Candidate Rediscovery Worth It for Your Recruitment Team?
AIRA Matchmaker and AIRA Search only work when a recruiter opens them, and only on the Custom or AIRA plan. A firm on a different tier gets no AI matching from Recruiterflow at all.
Even a firm paying for those tiers only benefits from jobs where a dedicated person actually clicks Generate. Every job where that step is skipped is sourced from zero, while a matching candidate sits untouched in the database.
Skima AI works on every new job automatically, regardless of plan, without depending on a recruiter remembering to trigger it. Setup takes an API key, a webhook, and a handful of tags, usually 1-2 days of IT time. That's a small cost compared to the sourcing hours and job board spend a single missed match already costs.
The case is strongest for firms with more than a few months of hiring history, since that's exactly where missed searches add up. A firm with a small, new database has less to gain right now. For most established firms, this closes a gap Recruiterflow's own tools already prove is worth closing, just not consistently.
Final Verdict: Pilot Candidate Rediscovery in Recruiterflow Now
Recruiterflow agencies at scale usually have 3 or 4 live jobs struggling through normal sourcing at any given time. Those are the right ones to start with. Connect Skima AI, create the tags and custom fields, and launch Talent Rediscovery on those roles.
Skima AI's Recruiterflow integration operates as a 30-day pilot with regular ROI reports. You can track time-to-screen, the number of rediscovered candidates who reach an interview, and the responses from hiring managers or clients. Expect over a 58% reduction in time-to-screen and double the interviews from your top shortlist. After that, expanding to more jobs will be a decision based on your own data, not a guess.
Frequently Asked Questions
1. Does Recruiterflow have a built-in dedicated candidate rediscovery feature?
No, not an automatic candidate rediscovery. AIRA Matchmaker and AIRA Search already score and rank your database, but both need a person to trigger them per job or query, and both sit on separate paid plans not included for every account.
2. How to conduct candidate rediscovery in Recruiterflow ATS?
To conduct candidate rediscovery in Recruiterflow ATS, connect Skima AI to Recruiterflow using an API key and webhooks, create Skima Screened tags and custom fields, then launch Talent Rediscovery on a live job. Skima AI scores your full database automatically and syncs feedback regardless of plan tier.
3. What are the benefits of Recruiterflow candidate rediscovery?
Rediscovered candidates arrive pre-scored, cutting screening time by over 58% in a 30-day pilot and doubling interviews from the top shortlist. Skima AI works automatically on every job regardless of plan, unlike AIRA Matchmaker, which needs a manual trigger.
4. Is Skima AI safe to integrate with Recruiterflow for talent rediscovery?
Yes, Skima AI encrypts candidate data in transit and at rest, operates under a signed Data Processing Agreement, and follows SOC 2 practices. Scores rely on resume-based evidence, with no automatic rejections, and every decision stays logged for audit.
5. Is candidate rediscovery useful for Recruiterflow recruiting teams?
Yes, especially for agencies not on the Custom or AIRA plan, where native AI matching isn't available. Even on those plans, rediscovery's value grows with database size and age, since closed-search candidates stay unscored unless someone opens AIRA Matchmaker again.
