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 has analyzed social signals for 9,000 anonymized video interviews that were evaluated by recruiters: the verbal content (semantics, singularity and lexical diversity) and non-verbal content (prosody).
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.
The recruiter sees the video interviews in order of recommended best-fit rather than chronological order on the EASYRECRUE platform.
The AI algorithm continues to learn from the recruiter’s evaluations.
Professor Emeritus in computer science and mathematics
Professor in computer science
Lecturer-researcher in Affective Computing
PhD student in CIFRE
R&D Department at EASYRECRUE