An AI-Powered Career Readiness Ecosystem for Campus Placements
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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.
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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},
}
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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.