Engineered an AI-driven system using Large Language Models and Retrieval-Augmented Generation to transform equipment maintenance processes. The system intelligently processes 100+ page manuals, performs automated maintenance item extraction and database population, and enables dynamic schedule generation. This project drastically reduces manual data entry, improves maintenance efficiency, ensures timely equipment upkeep, centralizes maintenance information, and increases operational reliability.