This case study examines the deployment of a scalable Light Retrieval-Augmented Generation (RAG) system designed for processing and querying Albanian legal data. The system leverages lightweight retrieval methods combined with generative AI to deliver accurate, context-aware responses from a comprehensive corpus of Albanian laws and legal documents. Deployed using Kubernetes, the architecture ensures high availability, scalability, and efficient resource management, making it well-suited for legal professionals and institutions seeking fast and reliable access to complex legal information.
Emiliano Mankolli is a distinguished university lecturer and the Head of Data Science and Machine Learning at Ritech International AG. He completed his Bachelor's and Master's degrees in Mathematics and Computer Science from the University of Tirana in 2012, graduating at the top of his class. In 2019, Mankolli embarked on his PhD research, focusing on "Optimization Methods for Machine Learning Applications" under the guidance of Prof. Vassil Guliashki. His research interests encompass Machine Learning and Optimization, with a primary emphasis on developing algorithms that enhance and optimize the hiring process for various companies within the recruitment industry. This year, he successfully defended his doctoral thesis at the Bulgarian Academy of Sciences in Sofia and continues to apply his research findings to various startups.
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