The life of a recruiter is filled with time-consuming tasks with low added value: publishing job offers, sorting CVs, and scheduling interviews.
Artificial intelligence is beginning to show its potential to help automate these tasks, and this is why we developed an AI-powered module for our on-demand video interviewing solution to rank and prioritize the best candidates based on their videos.
Our goal is to free up time for you to focus on the human side of recruiting.
Certain soft skills are a requirement for working in a corporate environment, such as communication, leadership and collaboration
We built a machine learning algorithmic model based on organizational psychology in order to study these social signals.
Our machine learning algorithm analyzes social signals and candidates' speech: verbal content (semantics, diversity in vocabulary etc.) and non-verbal content (prosody: rhythm, tone, intensity etc.).
The machine learning model was built in partnership with internationally recognized French engineering schools and research centers: CentraleSupelec, Télécom ParisTech and the French National Center for Scientific Research (see our R&D committee below). The R&D committee was awarded several times for their research on this topic at the most important artificial intelligence conferences around the world - WACAI, AAAI, ACII Cambridge.
Our AI algorithm ranks the on-demand videos based on the social signals it analyzes and holds out an attractive promise: helping recruiters find the best candidates more quickly, saving time for recruiters to focus on tasks with higher added-value, eliminating cognitive bias, and less subjective screeningrarie.
The candidate answers your questions during their video interview.
The process is identical to that of a regular on-demand video interview.
The video is anonymized. The AI analyzes the verbal and non-verbal content: prosody, lexical fields, etc. and ranks the candidates in your campaign in order of relevance.
After being fully trained on the product, the recruiter sees the video interviews in order of recommended best-fit rather than chronological order on the EASYRECRUE platform.
The recruiter has access to dashboards detailing each criterion taken into account to analyze a candidate's performance.
Professor Emeritus in computer science and mathematics
Professor in computer science
Lecturer-researcher in Affective Computing
PhD student in CIFRE
R&D Department at