AI-Driven Interview Analysis for Precision Hiring

Coach Name

Jordi Bosch i Garcia

EU Organization

Training Experience SL

Members

  • Fernando José Gómez Gil
  • Egidius Simkus
  • Luis Escribuela Tercero
  • Clara Peiró Jiménez
  • Gaspar Fernández Moreno
  • Nicolás Ladino

US Organization

University of Maryland Baltimore County (UMBC)

Members

  • Houbing Herbert Song, PhD

Project Overview

VeriRecruit is an AI-powered recruitment platform designed to assist HR professionals in evaluating candidates more efficiently and accurately during job and internship interviews. The platform integrates advanced technologies, including facial recognition, emotion analysis, and intelligent interview support. By analyzing verbal and facial cues, VeriRecruit helps assess candidates’ confidence, stress levels, and enthusiasm, enabling recruiters to make more informed decisions.

The goal is to reduce time-to-hire, improve candidate-job alignment, and enhance the overall recruitment process, making it more data-driven and precise.

Methods and approaches

AI-Driven Candidate Evaluation

Utilizes facial recognition and emotion analysis to assess non-verbal cues, including expressions of confidence, stress, and enthusiasm.

Real-Time Interview Optimization

AI-powered question suggestions based on the candidate's responses, improving the flow and depth of interviews.

GDPR and Privacy Compliance

Ensures all candidate data is processed securely in compliance with GDPR, HIPAA, and other data protection regulations.

Key Achievements

AI Integration

Developed a comprehensive AI-driven tool integrating facial recognition, emotion analysis, and real-time interview support.

Enhanced Recruitment Efficiency

Reduced average interview times by 25% through AI-driven insights and automation.

Open Source Contributions

The project actively contributed to the open-source community, making key components like emotion analysis and interview support tools available for developers.

Cross-Cultural Adaptability

Expanded the platform to support multilingual features, starting with Spanish, to cater to diverse global markets.

Impact & Results

Improved Recruitment Efficiency

The platform has enabled faster, more data-backed hiring decisions, reducing recruitment cycles by up to 25%.

Better Candidate Evaluation

AI-driven analysis provides recruiters with deeper insights into a candidate's emotional state and non-verbal cues, improving the accuracy of evaluations.

Enhanced Job-Candidate Alignment

By using objective, data-driven insights, VeriRecruit ensures a stronger alignment between candidates and job roles, reducing turnover and improving organizational performance.

Market Demand

Significant interest from HR departments and recruitment agencies, confirming the platform’s potential to transform recruitment processes globally.

Publications and Open-Source Contributions

  • Publication: “AI-Driven Enhancements in Recruitment Processes: A Case Study of VeriRecruit with UMBC Collaboration” – This paper explores the integration of AI in recruitment and its transformative potential.
  • GitHub Repository: VeriRecruit GitHub Repository – The repository includes core components for facial recognition, emotion analysis, and interview tools, making them available for wider use.
  • Social Media Campaign: Engaged users through LinkedIn posts and Instagram reels highlighting the platform’s capabilities and milestones.

Future directions

Avatar Recognition

Developing a tool to detect AI-generated avatars used in interviews to prevent fraud and ensure authenticity in the recruitment process.

Platform Expansion

Plans to integrate VeriRecruit with other platforms like Google Meet and Zoom to further enhance its usability and expand its user base.

Global Scaling

Expanding to international markets by adding support for more languages and adapting the platform for different cultural contexts.

Continuous AI Refinement

Ongoing efforts to improve AI-driven insights, focusing on more accurate emotion analysis and deeper interview support.