| Available for | Roles | Super Admin (to enable Talent Fit for the Account), Super Admin, Admin, Team Member (to control job level settings) |
| Permissions | ||
| Packages | LeverTRM, LeverTRM for Enterprise |
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This article describes Talent Fit in Lever, which is included in the Spring 2025 Product Release and will be rolled out progressively in May 2025. For release information, refer to our Release Matrix. As of September 2025, off-cycle release, Talent Fit is also supported for Lever EU accounts. As a part of the Fall 2025 Release, all customers who utilize any AI features within Lever will automatically have the AI Disclaimer Statement Feature enabled. For release information, refer to our Release Matrix. |
Talent Fit automatically identifies top-matched candidates based on job requirements, providing clear justification for each match. This helps recruiters quickly focus on high-potential applicants, saving time and streamlining the hiring process.
In this article
- Setting up the Talent Fit integration
- Using the Talent Fit integration
- Disabling the Talent Fit integration
Additional Resources: Talent Fit AI Brief
Talent Fit Integration
Enable the Talent Fit toggle under the Settings page.
Only Super Admins can enable Talent Fit for the account.
Once it’s enabled, Job postings will have a toggle to enable Talent fit at the job level under the custom application questions.
Once Talent Fit is enabled at the job level, it will begin processing all candidates in the Leads and Applicants tabs. Candidates who match will be labeled with 'Talent Fit' next to their name.
The Talent Fit processed candidates will have insights into their positives, areas for clarification, and concerns.
Talent Fit will automatically reprocess candidates if there are any changes to the job description or their resumes.
Recruiters will be able to search for Talent Fit-matched candidates through the search filter.
FAQs
Q. If the other candidate who doesn't get highlighted in Talent Fit is not a match or a close match, are they not a suitable option?
A. The Talent Fit tool is meant to help streamline the screening process. Talent Fit will highlight the candidates who are a closer match. If a candidate who's not a Talent Fit doesn't mean they don't have some of the skills, just that they aren't the top fit.
Q. Is Talent Fit available for all customers, or is it an extra cost?
A. TalentFit is available at no additional cost.
Q. Does Talent Fit retroactively review those who have already applied?
A. Talent Fit is a Go Forward feature. So, as new candidates apply, they will be evaluated by Talent Fit.
Q. Does it read the requisition details or job posting details to determine the Talent Fit?
A. Talent Fit uses the job description and candidate resumes to determine if the applicant is a Talent Fit.
Q. Is the Talent Fit available in languages other than English?
A. Talent Fit is only available in English.
Q. Does Talent Fit consider those who are hired for the position when training the model for Talent Fit?
A. We don't directly train our models on customer hiring outcomes, as this could result in biased recommendations. However, we will be asking for feedback on the accuracy and quality of the feedback via surveys.
Q. If we enable Talent Fit, will it still push referrals as they fit, or filter them out if the skills don't match?
A. Talent Fit is not intended to filter out candidates, but to provide additional context on their background and highlight areas that require clarification.
Q. Will other hiring team members with access to the position pipeline be able to see the tagged candidates?
A. If the Hiring Team has access to the candidate, then they will be able to see the Talent Fit summary.
Q. Will we be able to see Talent Fit in the Resume Screening view?
A. The Resume Screening does include Talent Fit.
Q. Is there a way to “train” the AI used in Talent Fit by marking results as good or bad?
A. There isn’t a built-in feedback mechanism right now. We want to be careful because we don’t want to train our AI. For instance, we don’t train on hiring outcomes because we don’t want to train on someone else’s bias.