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Stream/Area:
-
Subject:
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Paper ID:
IJSREM68530
Volume:
10 |
10 |
Oct 2026
Pages:
1-5
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.
Department of Computer Science and Engineering
SNS College of Engineering
Department of Computer Science and Engineering
SNS College of Engineering
Department of Computer Science and Engineering
SNS College of Engineering
Department of Computer Science and Engineering
SNS College of Engineering
Department of Computer Science and Engineering
SNS College of Engineering
Recruitment teams often handle resumes, assessments, interviews, and candidate records across separate tools, creating repeated administrative work and fragmented evidence. Aegis Recruit is an AI-assisted recruitment customer relationship management (CRM) and applicant tracking system (ATS) designed to connect these activities within a structured workflow. The proposed platform combines resume parsing and skill extraction, job-candidate comparison, aptitude testing, coding assessment, AI-assisted technical interviewing, and a final human-led human resources (HR) interview. Candidates must meet the configured 75% threshold in the aptitude and coding rounds to be eligible for the next stage; eligibility is intended to be validated by backend rules rather than by the browser interface alone. The design also includes centralized candidate records, stage tracking, notifications, and consolidated evaluation reports. This paper describes the system scope, workflow, architecture, prototype screens, and responsible-use considerations. The available project artifacts show the intended design and illustrative interfaces, but verified runtime accuracy, security-test results, load performance, and end-to-end test evidence have not been provided. Accordingly, the reported outcomes are design- and prototype-level observations, not claims of measured production performance. A validation plan is outlined for assessing accuracy, reliability, security, usability, and fairness before deployment.
KEYWORDS
Aegis Recruit proposes an integrated recruitment CRM and ATS that connects candidate records, resume analysis, aptitude and coding assessments, AI-assisted technical interviewing, and a final human-led HR interview. Its core design contribution is a single traceable workflow with explicit eligibility gates and consolidated candidate evidence. The accompanying prototypes illustrate how recruiters could review candidate information and stage outcomes in a centralized workspace. The available artifacts establish the intended workflow and interface direction but do not establish verified runtime accuracy, security, scalability, or end-to-end reliability. Future work should implement and test server-side authorization and progression rules, benchmark resume extraction and candidate matching, integrate a secure code runner, validate AI outputs against role-related rubrics, and perform functional, security, usability, fairness, and performance testing. Candidate notices, accessible alternatives, controlled data retention, auditability, and human ownership of final hiring decisions should remain fundamental requirements. Quantitative performance claims should be added only when supported by reproducible evidence.
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Publication Date
10/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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