Filling a role usually starts with a new posting, not a look back at who almost got the last similar one. That closed requisition from a year ago still holds qualified candidates, but finding the right one inside it takes more effort than most recruiters have time for on a given day.
In this guide, we cover what Jobvite does with a company's stored candidate history once a new requisition opens, where that native falls short of full rediscovery, and how connecting an external AI tool closes the gap with an explainable score and a manager feedback trail.
What Is Talent Rediscovery?
Talent rediscovery means searching and matching candidates already stored in a company's ATS against a role that just opened. It covers applicants from closed jobs, candidates parked in a talent network, and anyone who advanced partway through a hiring process before the role got filled or shelved.
A year or two of application history turns into an active sourcing channel once those stored candidates get checked against every new opening automatically. Most ATS platforms leave that to a recruiter's memory. Rediscovery performs the check every time, without anyone needing to recall a name.
Does Jobvite Provide Candidate Rediscovery?
Partially, Jobvite's Auto Talent Rediscovery scans the existing candidate database and surfaces qualified, previously engaged people when a similar role opens, based on skills, experience, past interactions, and hiring signals, then recommends matches to the assigned recruiter.
Talent Fit, a separate capability, scores applicants already in a job's pipeline with a stated justification for each match.
The gap is in what Auto Talent Rediscovery's recommendations carry. They arrive without a numeric score or a written reason tying a candidate to the new role, unlike Talent Fit's justified matches. Nothing scopes the scan by how long ago a candidate entered the database, and nothing records a hiring manager's decision on a recommended name.
How to Rediscover Candidates in Jobvite
Jobvite's Auto Talent Rediscovery gives a recruiting team a starting point for rediscovery. However, recruiting teams connect Skima AI to add the explainable score, the date-based scoping, and the manager feedback loop that the native tool lacks. Below is a 5-step workflow that starts with what Jobvite already provides and builds on it:
Step 1: The Native Path, Start With Auto Talent Rediscovery
When a new requisition opens, Auto Talent Rediscovery scans the existing candidate database for people who match on skills, experience, past interactions, and hiring signals, then recommends those names to the assigned recruiter. The recruiter reviews each recommendation and decides whether to move the candidate into the pipeline.
This step surfaces candidates from a company's own history without a manual search. It returns no score or written reason for the match, though, and it does not track what a hiring manager decides once a candidate moves forward. For a scored, auditable version of this same search, Skima AI builds on this next.
Step 2: Connect Your Jobvite Account With Skima AI
Create an API key with read access on Candidates, Applications, Attachments, and Jobs, and write access on Notes, Custom fields, and Tags. This connection uses Jobvite's own REST API directly, with no middleware required.
- Read access: candidate profiles, application data, requisition details, and resume attachments
- Write access: application custom fields, candidate tags, and activity notes
- Pulled data: candidate contact details, resumes, application stage and source, requisition title and description for scoring context
- Event triggers: application created or updated, stage changed, and attachment added
Step 3: Configure Custom Fields and Enable Webhooks
Create the application custom fields Skima AI writes to: Match Score, Reasons, and Shortlist Link, or let Skima AI provision them automatically. Enable webhooks for application, stage, and attachment events so Skima AI provides the endpoint and secret. If webhooks are not available, Skima AI falls back to a 10 to 15 minute polling interval instead.
Before rolling this out further, test the connection on two or three requisitions. Upload a resume, confirm the Match Score and Reasons appear on the application, submit sample hiring manager feedback, and check that it logs to the activity note correctly.
Step 4: Launch Talent Rediscovery Against a Live Requisition
Open the job inside Skima AI, from the Jobs list or from within the job itself. Click the three-dot Actions menu and select Rediscover Candidates. A modal opens with options to narrow the scan: select a specific candidate segment, or leave it open to every synced Jobvite record.
Set the candidate created date range next: All time, Last 6 months, Last 1 year, or a custom window, and optionally check the location filter to restrict the scan geographically. Click Apply. A "Performing Rediscovery" notification appears while the scan works in the background, and turns green with a refresh option once it completes.
Step 5: Review, Filter, and Sync Feedback Back to Jobvite
Refresh the page and open the Rediscovered source tab inside View Candidates. Each match carries a Skima AI score and reason bullets, tagged with a Rediscovery source label. Filter by Industry, Work Mode, Experience Level, Notice Period, Location, and Salary Range to narrow the list.
Once the shortlist looks right, generate a secure, no-login link and send it to the hiring manager. They click thumbs up, thumbs down, or maybe on each name, with an optional comment. Skima AI writes that decision back into Jobvite as an activity note on the application record, keeping the feedback on the record without a second login.
What If Your Jobvite Database Is Messy or Duplicated
Jobvite's core ATS does not support merging candidate profiles. A profile gets created from the email address used to apply, so multiple applications with that same email stay under one profile automatically. However, two profiles created under different emails for the same person remain separate permanently, with no merge option available.
Jobvite's Recruitment Marketing module, Evolve RM, handles this differently. Profiles entering Evolve RM under the same email merge automatically, and a separate setting, enabled through a support ticket, also merges records sharing the same first name, last name, and phone number. Even so, that setting only applies going forward unless a company specifically requests historical processing.
Skima AI closes this gap by applying one matching standard across the database instead of splitting the logic between two systems. It matches first on email, phone, or LinkedIn URL, then checks name, location, and company as a backup signal.
When a match surfaces, a field comparison modal highlights differences across Name, Title, Company, Location, Email, Phone, and LinkedIn, tagging each mismatch as Differs.
From there, a recruiter chooses which values to keep and merges the records, or adds the profile as new if the two genuinely differ. Every resolved case logs under the Duplicates tab, split into In Database, From Uploads, and Resolved sub-tabs for audit.
5 Benefits of Candidate Rediscovery with Skima AI in Jobvite
A documented 30-day pilot with Jobvite reported 5 highlights once Skima AI starts rediscovery and scoring a company's stored candidate history:
- Faster Time-to-Screen: Rediscovered candidates arrive already matched and scored against the open role, reducing time-to-screen by 58% compared to starting a fresh search.
- Interviews Double From the Shortlist: The same pilot saw interviews booked from the shortlist double compared to the prior process.
- A Score That Shows Its Reasoning: Every rediscovered match carries a 0 to 100 score with reason bullets, giving a written answer where Auto Talent Rediscovery's recommendations offer none.
- One Application Record, No New Login: Match scores, reasons, and tags write directly to the same application fields and activity notes a recruiter already checks inside Jobvite.
- Manager Trust, Backed by Data: Hiring manager satisfaction rose 24 points on NPS in the same pilot, tied to a feedback link that logs every decision instead of a verbal note.
5 Best Practices to Rediscover Talent in Jobvite
Getting real ROI out of this connection takes a few habits beyond the integration itself. The 5 practices below cover search timing, data hygiene, and fitting rediscovery around a high-volume hiring team workflow:
- Start With Auto Talent Rediscovery: Let the native tool surface obvious matches first when a requisition opens. Move to a scoped Skima AI scan once a numeric score, a written reason, or a feedback record becomes necessary for the decision.
- Automate Rediscovery on Job Creation: Skima AI's setting under Preferences and General starts a database scan the instant a new job gets created inside the connected account. Enable it so no requisition goes live without a first look at existing applicant history.
- Use Reverse Search Across Brands and Regions: For companies running Jobvite's CRM across multiple brands or geographies, Reverse Search starts from one candidate and surfaces every open job they match, ranked by score.
- Segment Scans by Candidate Created Date: Choose a 6-month or 1-year window when a role calls for someone recently active. Widen to all time for a niche or hard-to-fill role where the applicant pool has stayed thin for years.
- Watch the Gap Between ATS and CRM Records: Since the ATS and Evolve RM apply different duplicate rules, a candidate can end up recorded twice across the two systems with no automatic link between them. Reviewing the In Database sub-tab on a set schedule catches what neither native system checks on its own.
Is Candidate Rediscovery Worth It for Your Recruitment Team?
A company that uses both Jobvite's ATS and its CRM side ends up with candidate data split across two systems that apply different rules for what counts as a duplicate. That split creates a genuine backlog: records the CRM merged on its own, records the ATS never touched, and candidates who exist in both places with no link tying them together.
Connecting Skima AI takes coordination, not a login and a click. Someone needs administrator access inside Jobvite to set up the connection, configure the fields Skima AI writes to, and test it on two or three requisitions before anything touches a live role. That setup adds time and a subscription cost on top of a Jobvite plan a company already pays for.
A company with several years of closed requisitions across multiple brands or regions gives Skima AI a deeper pool to score and clean up than one that started using Jobvite recently. A newer, thinner database returns a thinner Rediscovered list regardless of how the connection is configured, which makes the setup harder to justify early on.
Pilot Candidate Rediscovery in Jobvite Now
For a company with a multi-year Jobvite history, a pilot with Skima AI can deliver high ROI. Start with two or three live requisitions, ideally roles the company has filled more than once before, so there is a real historical pool to score against.
Connect Skima AI to Jobvite, configure the custom fields, and test the connection on those two or three requisitions before going live.
Track how many rediscovered candidates reach an interview and how the hiring manager responds to the shortlist link. Skima AI's documented 30-day pilot with Jobvite reported a 58% drop in time-to-screen, interviews from the shortlist doubling, and hiring manager satisfaction rising 24 points on NPS. From there, expanding to more requisitions becomes a decision backed by the pilot's own numbers.
Frequently Asked Questions
1. Does Jobvite have a built-in talent rediscovery feature?
Partially, Jobvite's Auto Talent Rediscovery scans the existing candidate database and recommends matches when a similar role opens, but the recommendations carry no numeric score or written reason, and nothing tracks a hiring manager's decision on them.
2. How do I rediscover candidates in Jobvite?
Start with Jobvite's native Auto Talent Rediscovery for automatic recommendations. For a scored, auditable version, connect Skima AI through Jobvite's API, configure custom fields for Match Score and Reasons, then launch Talent Rediscovery on a live requisition.
Start with Jobvite's native Auto Talent Rediscovery for automatic recommendations. For a scored, auditable version, connect Skima AI through Jobvite's API, configure custom fields for Match Score and Reasons, then launch Talent Rediscovery on a live requisition.
3. What are the benefits of candidate rediscovery in Jobvite?
Based on a documented 30-day pilot, rediscovered candidates cut time-to-screen by 58% and doubled interviews from the top-10 shortlist. Matches carry an explainable score and reason bullets, and hiring manager satisfaction rose 24 points on NPS.
4. Is Skima AI safe to integrate with Jobvite for talent rediscovery?
Yes, Skima AI scores candidates using resume-based evidence only, with no automatic rejections, and logs every hiring manager decision and shortlist action for audit. Data stays encrypted in transit and at rest, backed by a signed Data Processing Agreement.
5. Is candidate rediscovery useful for Jobvite's typical customers?
Yes, especially for larger organizations running Jobvite's CRM across multiple brands or regions, where candidate data often splits across two systems with different duplicate rules. The value grows with the size and complexity of that history.
