Auralytica: An AI-Powered Intelligent Recruitment and Job Matching Platform

Authors

  • Yamparala Srinivas Students, Department of Computer Science and Engineering, SRK Institute of Technology, Vijayawada, India Author
  • Lanka Swathi Students, Department of Computer Science and Engineering, SRK Institute of Technology, Vijayawada, India Author
  • Tippani Deepika Students, Department of Computer Science and Engineering, SRK Institute of Technology, Vijayawada, India Author
  • Kodali Samuel Sanjay Students, Department of Computer Science and Engineering, SRK Institute of Technology, Vijayawada, India Author
  • Kilaru Chaitanya Associate Professor, Department of Computer Science and Engineering, SRK Institute of Technology, Vijayawada, India Author

DOI:

https://doi.org/10.47392/IRJAEH.2026.0226

Keywords:

AI recruitment, job matching, resume optimization, intelligent screening, MERN stack, large language models, career advisory, recruitment automation

Abstract

Modern recruitment faces serious challenges like manual resume screening, unconscious bias, poor candidate matching, and excessive time spent on administrative work. We developed Auralytica, an AI-powered recruitment platform that uses Large Language Models to help both job seekers and recruiters. Our system has 14 AI features including resume optimization, smart job matching, automated screening, interview question generation, and bias detection. We built it using the MERN stack (MongoDB, Express.js, React, Node.js) integrated with advanced language models. The platform gives job seekers personalized career advice while helping recruiters make better hiring decisions based on data. Our implementation shows major improvements in recruitment speed, candidate experience, and overall hiring quality through AI automation and intelligent decision support.

Downloads

Download data is not yet available.

Downloads

Published

2026-04-16

How to Cite

Auralytica: An AI-Powered Intelligent Recruitment and Job Matching Platform. (2026). International Research Journal on Advanced Engineering Hub (IRJAEH), 4(04), 1725-1734. https://doi.org/10.47392/IRJAEH.2026.0226