EvaluTech is an intelligent recruitment management platform that streamlines the complete hiring lifecycle from job posting to offer acceptance. The system provides dedicated portals for both employers and applicants, enabling employers to manage hiring workflows while allowing candidates to apply for jobs, complete assessments, and track application progress. Designed to modernize recruitment processes in organizational environments such as Factory Web Services, the platform supports AI-driven resume screening, customizable hiring pipelines, automated MCQs with anti-cheating features, live video interviews with transcript generation, and comprehensive candidate evaluation tools, enabling efficient, fair, and data-driven hiring decisions while reducing manual workload and improving recruitment transparency.
Objectives
The objective of EvaluTech is to develop a centralized AI-powered recruitment platform that addresses inefficient and manual hiring practices while significantly enhancing the hiring workflow of Factory Web Services and other companies. The system enables employers to create jobs, configure customizable hiring pipelines, conduct MCQ assessments, upload technical assessments, schedule live interviews, and manage applicants through a unified platform.
EvaluTech also supports AI-based resume screening, semantic skills matching, automated question generation, transcript generation, and candidate evaluation reporting. Candidates can create professional profiles, browse jobs, apply online, complete MCQ assessments, upload solved technical assessments, track application progress, and receive real-time notifications.
The platform aims to reduce hiring delays, improve recruitment quality, support fair and data-driven hiring decisions, and provide secure, scalable, and transparent recruitment workflows for organizations.
Socio-Economic Benefit
EvaluTech improves recruitment accessibility and efficiency for both employers and job seekers through a centralized digital hiring platform. It reduces dependency on informal, slow and less automated hiring methods and promotes transparent, merit-based recruitment. Developed with relevance to organizational hiring environments such as Factory Web Services, it reduces recruitment costs and manual workload using AI-assisted screening, MCQ assessments, structured hiring pipelines, and automated workflows. It also supports remote hiring and helps organizations connect with qualified candidates beyond geographical limitations.
Methodologies
EvaluTech was developed using an Agile and iterative software engineering approach. The system design included use cases, UML diagrams, ER diagrams, sequence diagrams, and requirement traceability matrices.
The frontend was built using Next.js 14, TypeScript, and Tailwind CSS, while the backend utilized Node.js and Supabase PostgreSQL with role-based authentication. AI features including resume screening, semantic matching, and question generation were integrated using Google Gemini API, while Deepgram API was used for transcript generation. WebRTC and Socket.io enabled live interviews and real-time notifications. Comprehensive testing was performed for all major modules.
Outcome
EvaluTech successfully delivers a fully functional AI-powered recruitment management platform supporting the complete pre-hiring lifecycle for both employers and applicants. Developed in alignment with real-world organizational needs, including contexts such as Factory Web Services, the platform enables employers to manage job postings, hiring pipelines, MCQ assessments, technical assessments, interviews, evaluations, and job offers through a centralized dashboard. Candidates can create profiles, apply for jobs, complete assessments, upload technical tasks, participate in interviews, and track applications in real time. The deployed system demonstrates practical implementation of full-stack development, AI integration, anti-cheating mechanisms, and scalable recruitment workflows.
