Published on: April 2026
SMART HIRE: AI-DRIVEN RECRUITMENT AND CODING ASSESSMENT SYSTEM
Sowndarya.V Oviya.R Subhiksha.S Iyswarya K Varshini.G
Article Status
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Abstract
Traditional recruitment systems rely heavily on manual screening and static evaluation methods, which often lead to inefficiencies, bias, and limited insight into candidate capabilities. The Smart Hire AI-Driven Recruitment and Self-Assessment Platform addresses these limitations by introducing an intelligent, full-stack web-based solution that enables automated, data-driven technical hiring. The system adopts an AI-assisted evaluation approach to continuously assess candidate performance through coding challenges, mock interviews, and structured assessments, eliminating dependency on one-time evaluation processes.
The platform integrates a dynamic performance tracking module that monitors user progress over time, capturing metrics such as problem-solving efficiency, accuracy, and skill proficiency. These metrics are processed to generate personalized feedback, enabling candidates to identify strengths and improvement areas. On the recruiter side, a centralized analytics dashboard provides real-time insights into candidate performance, facilitating efficient shortlisting and informed hiring decisions through data visualization and automated reporting.
How to Cite this Paper
Sowndarya.V, , Oviya.R, , Subhiksha.S, , K, I. & Varshini.G, (2026). Smart Hire: AI-Driven Recruitment and Coding Assessment System. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.226
Sowndarya.V, , et al.. "Smart Hire: AI-Driven Recruitment and Coding Assessment System." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.226.
Sowndarya.V, , Oviya.R, Subhiksha.S,Iyswarya K, and Varshini.G. "Smart Hire: AI-Driven Recruitment and Coding Assessment System." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.226.
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Ethical Compliance & Review Process
- •All submissions are screened under plagiarism detection.
- •Review follows editorial policy.
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- •Peer Review Type: Double-Blind Peer Review
- •Published on: Apr 17 2026
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