Increase Your Hiring Intelligence


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.

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The Problem


Fifty-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

We offer ECLAIR - a Natural Language Processing (NLP) tool to automate the accurate and non-biased identification of suitable job candidates for open job description(s).

The Solution

Intelligent Natural Language Resume Processing


Reduced Recruiter Involvement

Reduces resume screening time by 15-fold

Accurate Matches

Equals (or betters) the accuracy of a human candidate-to-position match

Intuitive Candidate Score

Easy to understand candidate rating (0-100) for multiple target positions

API Access

Easy programmatic integration into existing Applicant Tracking Systems

Current Status


Contacts for ECLAIR are Elaine Fisher (elaine.fisher [at] emory.edu) and Steve Pittard (wsp [at] emory.edu)

ECLAIR is an Emory University-based collaboration between members of the Nell Hodgson School of Nursing, the Emory Department of Computer Science, the Department of Biostatistics and Bioinformatics in The Emory Rollins School of Public Heath, Emory Healthcare, and the Emory Office of Technology Transfer.

ECLAIR is an acronym - "Electronic Competence-Level Analysis on Resumes".

The early work in support of the project is described in the publication: "Competence-level prediction and resume-job description matching using context-aware transformer model." See https://aclanthology.org/2020.emnlp-main.679.pdf

The ECLAIR 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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