We reduce resume screening time by 15-fold while equaling (or bettering) the accuracy of a candidate-to-position match performed by a human recruiter.
We provide an intuitive job suitability score which can be balanced with other factors, (e.g., diversity, hiring regulations), thus allowing recruiters to retain control of the recruitment process
Our solution helps human resource organizations recover and reallocate recruiter time spent on manual resume review without sacrificing accuracy.
Find Out MoreFifty-two percent of talent acquisition leaders report that the hardest part of recruitment is identifying the ‘right candidates’ from a large and diverse applicant pool
Matching applicants to open job positions is a time-consuming screening effort, which relies on imprecise semantic searching, and/or unsophisticated AI screening methodology.
Hiring the wrong applicant results in frustration, attrition, and delayed progress which costs the organization time and money
Talent Trace: An Advanced Decision-Based Tool for Accurate Candidate to Position Matching in Multi-Level Job Positions The Solution
Reduces resume screening time by 15-fold
Equals (or betters) the accuracy of a human candidate-to-position match
Easy to understand candidate rating (0-100) for multiple target positions
Easy programmatic integration into existing Applicant Tracking Systems
Contacts for Talent Trace are Elaine Fisher (elaine.fisher [at] emory.edu) and Steve Pittard (wsp [at] emory.edu)
Talent Trace is an Emory University-based collaboration between members of the Nell Hodgson School of Nursing and the Department of Biostatistics and Bioinformatics in The Emory Rollins School of Public Heath, and the Emory Office of Technology Transfer.
The Talent Trace project receives funding from the Georgia Research Alliance via a Phase 1 Development Grant.
We are working on a Minimum Viable Prototype in support of our effort. Our intent is to pursue Phase 2 funding including an application for NSF funding.
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