Greenhouse Real Talent™ reduces risk at the top of the funnel with candidate fraud detection, identity verification and candidate matching software – all while keeping recruiters fully in control of decisions.
Spam blocklist lets you block specific IP addresses or email domains based on patterns you’ve already seen, like repeat spam submissions or known bad actors. You decide who to block and can update the list anytime.
Fraud detection flags low-quality and suspicious applications by analyzing signals like phone number, email, IP address and location, giving recruiters an early warning as they review applicants.
Greenhouse Real Talent is now available. Fill out the form to learn more, request pricing details or talk with our team about bringing Real Talent into your hiring process.
Real Talent is an AI-powered solution in Greenhouse that helps recruiting teams reduce fraud, spam and misrepresentation at the top of the hiring funnel. It combines candidate fraud and spam detection, identity verification with CLEAR® and AI-assisted Talent Matching so recruiters can focus on real, qualified candidates while staying in control of every hiring decision.
No. Real Talent does not automatically advance or reject candidates, nor does it make hiring decisions. AI is used to analyze the candidate’s resume and then compare it against the user-defined calibration criteria. The results are presented to the recruiter in their customized dashboard for further action and evaluation.
Candidate fraud refers to job applications that misrepresent or conceal a candidate’s true identity, qualifications or intent. This can include fake or automated applications, impersonation, falsified experience or applicants using AI or third parties to apply at scale.
Real Talent’s fraud detection analyzes a candidate’s phone number, email address, IP address and location to identify potential fraud risk signals. The system leverages our third-party vendor (IPQualityScore) to return 26 signals categorized into three distinct groups: high-risk signals that indicate a high risk, minor signals for moderate risk and authenticity markers that lend credibility to a candidate’s profile. By leveraging these risk scores, customers can make more informed decisions about which candidates to move forward.
No. Fraud detection uses objective data from applications (e.g., IP address, email, phone) to show fraud signals. Recruiters can then make decisions about how to interpret and apply the fraud signals.
No. CLEAR is identity verification, not a background check. It confirms that a candidate is who they say they are – it does not review criminal history, credit, employment records or make hiring recommendations.
CLEAR works at the top of the funnel, using biometric signals, document validation and trusted data sources to verify identity directly within Greenhouse. It adds an early layer of trust so recruiters can focus on real applicants faster, while all hiring decisions remain with the employer.
CLEAR shares only the following limited data with Greenhouse:
Yes. Candidates can decline to participate in identity verification, and declining is not considered a failure. Candidates should contact the recruiter to discuss next steps.
AI regulations typically focus on transparency, bias and data retention.
