Abstract
This work describes the development and implementation of a digital assistant for the remote management of industrial facilities, focused on improving precision and operational decision making. The digital assistant, developed in three phases, integrates both manual and real-time data to diagnose and recommend corrective actions. In the first phase, the system assesses component health using a database of operational, safety, and environmental parameters. The second stage integrates historical and real-time data, and the third automates corrective actions. Preliminary results demonstrate significant improvements in operational efficiency and safety, emphasizing the assistant's potential as a critical tool in the sector's digital transformation. This document details the system architecture, evaluation methodology and observed benefits, providing a roadmap for the future implementation of this type of technologies in the industry.