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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM60951
Volume:
10 |
4 |
April 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Using Next.js, Supabase, and VapiAI, the AI Recruiter Voice Agent is an automated web-based recruitment platform that conducts real-time, voice-based first-round candidate interviews. This system conducts structured, conversational interviews using predefined role-specific criteria, real-time automatic speech recognition (ASR), and natural language processing (NLP) for intelligent response evaluation, in contrast to conventional manual screening, phone-based interviews, or static chatbot questionnaires. Using an easy-to-use dashboard, recruiters set up interview templates, specify scoring criteria, and send prospects safe links. The system uses text-to-speech (TTS) to engage candidates in adaptive dialogue during interviews, transcribes responses using VapiAI with industry-leading accuracy, and analyzes material for behavioral cues, skills extraction, and experience mapping. The solution allows recruiters to make data-driven decisions 80% faster than with conventional techniques by producing clear, rubric-aligned evaluations with shortlist recommendations after the interview. The platform facilitates concurrent interviews at scale, keeps audit-friendly records for compliance, and provides interview artifacts (transcripts, scores, and summaries) via an analytics-rich recruiter dashboard. It is implemented as a cloud-native full-stack application on Supabase with role-based security. The AI Recruiter Voice Agent minimizes screening bottlenecks, enhances candidate experience, and enforces bias-mitigating uniformity throughout recruiting pipelines by combining conversational AI with structured assessment to provide a scalable, equitable, and consistent solution. Automated Recruitment, Conversational AI, Natural Language Processing, Automatic Speech Recognition, VapiAI, Next.js, Supabase, NLP Evaluation, Candidate Screening, Full-Stack Development, Candidate Assessment, AI in HR, Recruitment Automation, and Real-Time Speech Processing are among the
KEYWORDS
Publication Date
4/21/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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