Authors: Ragula Rajesh, Potti Rakesh, Poojari Jayakrishna, Mrs.V. Elavenil
Abstract: This study describes the deployment of a cloud-native AI system designed to assist HR departments by offering automated resume screening and candidate-job matching. To provide precise and contextually aware responses, the system employs a Retrieval-Augmented Generation (RAG) technique, which combines a language model with a local knowledge store of job descriptions. We developed this totally with free and open-source technologies like AWS Lambda, BERT, and ChromaDB to make the solution more accessible for startups and SMEs. Open-source approaches, such as Tesseract for OCR, are used to add scanned resume capabilities. To ensure accuracy and validity, the data is also gathered from reputable sources like ESCO skill ontology and LinkedIn datasets. We used PDFs from these sources for RAG and stored them in vector databases for efficient document retrieval, as this system aims to bridge the information gap in high-volume hiring.
DOI: https://doi.org/10.5281/zenodo.20304132
