Virtual assistant using generative AI applied to iron ore concentration
Tiago Caixeta Nunes, Rodrigo Martins Gomes, Felipe Novaes Caldas, Ednei Rodrigues Rocha, Eric Guimarães Vieira, Marcelo Pereira de Castro Alves
Abstract
The use of Artificial Intelligence (AI) in the competitive mining market has attracted increasing interest in recent years, as these technologies play a significant role in data interpretation, modernization of production processes, and efficient use of mineral reserves. Among the various AI approaches, Generative Artificial Intelligence (Gen-AI) stands out as one of the most promising and disruptive. This paper aims to present a virtual assistant application based on Gen-AI, capable of providing answers to user questions using natural language about operational aspects, based on several data sources to assist in decision-making that influences the performance of iron ore concentration. The assistant considers information security infrastructure, uses language models (LLMs) and Retrieval-Augmented Generation (RAG) techniques to access plant databases and documents, while a multi-agent flow centralizes application information with production data, historical data, and technical documentation.
Keywords
References
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Submitted date:
10/24/2025
Accepted date:
03/19/2026
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