Aura Hire: A Multi-Modal AI Framework for Autonomous, Bias-Reduced and Proctored Technical Recruitment
Year: 2026
Type: preprint
Abstract: Modern educational frameworks and industry demands necessitate highly scalable and equitable hiring ecosystems. However, conventional talent acquisition workflows suffer from severe manual bottlenecks and subjective human prejudices. To resolve these systemic inefficiencies, this paper introduces Aura Hire: an autonomous artificial intelligence recruitment platform. By integrating Large Language Models (LLMs), low-latency Voice Agents, and browser-based Computer Vision, the system orchestrates a comprehensive four-stage pipeline. This framework unifies automated resume shortlisting, interactive voice-based behav-ioral interviews, real-time proctoring, and live technical coding assessments into a single web application. Crucially, the system introduces edge-computed, zero-retention biometric proctoring, fundamentally mod-ernizing the preliminary candidate screening lifecycle while establishing a standardized, bias-resistant, and securely private evaluation methodology.
Source: Research Square
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: green
OpenAlex ID: W7160065601