An AI-Powered Career Readiness Ecosystem for Campus Placements

Paper Details
Manuscript ID: 2126-0520-6006
Vol.: 2 Issue: 5 Pages: 298-307 May - 2026 Subject: Computer Science Language: English
ISSN: 3068-1995 Online ISSN: 3068-109X DOI: https://doi.org/10.64823/ijter.2605025
Abstract

Campus placement preparation is a crucial phase in a student’s academic journey; however, the current ecosystem is highly fragmented, requiring students to depend on multiple platforms for aptitude practice, coding preparation, resume building, and interview training. This lack of integration leads to inefficiencies, poor progress tracking, and difficulty in assessing overall readiness. Students often struggle to identify their weaknesses due to the absence of centralized feedback, while Training and Placement Officers (TPOs) lack real-time insights into student performance, and recruiters face challenges in evaluating candidates holistically. To address these limitations, this paper proposes PrepWise AI, an AI-powered career readiness ecosystem that integrates all aspects of placement preparation into a unified, intelligent platform. The system combines aptitude and coding assessments, AI-proctored mock interviews, and ATS-based resume analysis within a single web-based environment, enabling a seamless and structured learning experience. It leverages Artificial Intelligence and Machine Learning techniques to provide personalized recommendations, adaptive testing, and predictive performance analytics. Additionally, the platform offers real-time dashboards for TPOs, allowing continuous monitoring of student progress, while recruiters gain access to structured candidate profiles and intelligent shortlisting based on skill proficiency, consistency, and behavioral insights. Built on a scalable cloud-based architecture, the system ensures high availability, secure data handling, and efficient performance under concurrent usage. By centralizing preparation, evaluation, and recruitment processes, PrepWise AI bridges the gap between academic learning and industry expectations, ultimately improving placement success rates, reducing recruitment time, and enhancing overall efficiency for students, institutions, and recruiters.

Keywords
Artificial Intelligence (AI) Campus Placement System Mock Interviews ATS Resume Analysis DSA Practice Face Detection Proctoring Performance Analytics Cloud-Based Platform.
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Cite this Article

Mehul Chavan, Ajinkya Bondge, Atharva Patil, Pratik Chinchawadkar, Soham Bhogale, Satyajeet Shinge (2026). An AI-Powered Career Readiness Ecosystem for Campus Placements . International Journal of Technology & Emerging Research (IJTER), 2(5), 298-307. https://doi.org/10.64823/ijter.2605025

BibTeX
@article{ijter2026212605206006,
  author = {Mehul Chavan and Ajinkya Bondge and Atharva Patil and Pratik Chinchawadkar and Soham Bhogale and Satyajeet Shinge},
  title = {An AI-Powered Career Readiness Ecosystem for Campus Placements },
  journal = {International Journal of Technology &  Emerging Research },
  year = {2026},
  volume = {2},
  number = {5},
  pages = {298-307},
  doi =  {10.64823/ijter.2605025},
  issn = {3068-109X},
  url = {https://www.ijter.org/article/212605206006/an-ai-powered-career-readiness-ecosystem-for-campus-placements},
  abstract = { Campus placement preparation is a crucial phase in a student’s academic journey; however, the 
  current ecosystem is highly fragmented, requiring students to depend on multiple platforms for aptitude 
  practice, coding preparation, resume building, and interview training. This lack of integration leads to 
  inefficiencies, poor progress tracking, and difficulty in assessing overall readiness. Students often struggle to 
  identify their weaknesses due to the absence of centralized feedback, while Training and Placement Officers 
  (TPOs) lack real-time insights into student performance, and recruiters face challenges in evaluating 
  candidates holistically. To address these limitations, this paper proposes PrepWise AI, an AI-powered career 
  readiness ecosystem that integrates all aspects of placement preparation into a unified, intelligent platform. 
  The system combines aptitude and coding assessments, AI-proctored mock interviews, and ATS-based resume 
  analysis within a single web-based environment, enabling a seamless and structured learning experience. It 
  leverages Artificial Intelligence and Machine Learning techniques to provide personalized recommendations, 
  adaptive testing, and predictive performance analytics. Additionally, the platform offers real-time dashboards 
  for TPOs, allowing continuous monitoring of student progress, while recruiters gain access to structured 
  candidate profiles and intelligent shortlisting based on skill proficiency, consistency, and behavioral insights. 
  Built on a scalable cloud-based architecture, the system ensures high availability, secure data handling, and 
  efficient performance under concurrent usage. By centralizing preparation, evaluation, and recruitment 
  processes, PrepWise AI bridges the gap between academic learning and industry expectations, ultimately 
  improving placement success rates, reducing recruitment time, and enhancing overall efficiency for students, 
  institutions, and recruiters.},
  keywords = { Artificial Intelligence (AI), Campus Placement System, Mock Interviews, ATS Resume  Analysis, DSA Practice, Face Detection Proctoring, Performance Analytics, Cloud-Based Platform.},
  month = {Jun},
}
Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.