DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE APPLICATION FOR THE INTERPRETATION OF TECHNICAL DOCUMENTATION AND AUTOMATED GENERATION OF RESPONSES

Abstract

This work presents the development of an artificial intelligence-based application aimed at the interpretation of technical documentation and automated generation of responses. In industrial environments, manual consultation of technical documents is frequently a slow process, dependent on specialized knowledge and prone to errors. The proposal utilizes language models combined with the Retrieval-Augmented Generation (RAG) technique, enabling the integration of pre-trained knowledge with external databases. The methodology involves a literature review, architecture definition, prototype implementation, and initial testing. The results indicate a significant improvement in the accuracy and relevance of the responses. It is concluded that the solution has the potential to optimize technical consultation processes, increasing efficiency and reliability.