<![CDATA[The advancement of Artificial Intelligence (AI) has accelerated digital transformation in the recruitment process through automated candidate data analysis. This study aims to develop a prototype of an intelligent recruitment system by integrating ChatGPT (OpenAI LLM), N8N (workflow automation framework), and Supabase (PostgreSQL-based vector database). The proposed system automatically analyzes job seekers’ Curriculum Vitae (CV) stored in Google Drive and transforms them into vector representations using AI embedding models. These vectors are then utilized to match candidate profiles with corresponding job requirements. N8N functions as a workflow orchestrator that connects data sources, AI models, and the Supabase vector database. ChatGPT serves as an interactive agent that enables recruiters to perform conversational analysis and information retrieval based on vectorized data. This research develops an intelligent recruitment prototype by integrating ChatGPT, N8N, and Supabase to automate CV analysis and job matching through vector embeddings. The system extracts CVs from Google Drive, converts them into high-dimensional embeddings, and stores them in Supabase for semantic similarity search. Quantitative evaluation using ten candidate datasets shows an average processing time of 25.6 seconds per batch and a 0.81 relevance score compared to manual screening. The results indicate that AI-driven automation can enhance recruitment efficiency and accuracy by reducing manual effort and bias.]]>
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