Developed a semantic retrieval system using a pre-trained transformer model and FAISS, enabling efficient matching of SQL queries based on similarity in syntax and intent. Researched, evaluated, and documented top embedding models for Retrieval-Augmented Generation (RAG) tasks, using metrics like NDCG@10 to select models optimized for SQL query matching .