Silva, Ivanovitch Medeiros Dantas daOliveira, Gabriel Barros Lins Lelis de2025-01-232025-01-232025-01-20OLIVEIRA, Gabriel Barros Lins Lelis de. Desenvolvimento de um sistema multi-agente baseado em inteligências artificiais generativas para avaliação de qualidade em atendimento ao cliente. 2025. 92 f. Trabalho de Conclusão de Curso (Graduação em Engenharia de Computação) - Departamento de Engenharia da Computação, Universidade Federal do Rio Grande do Norte, Natal, 2025.https://repositorio.ufrn.br/handle/123456789/61715This work presents the development and validation of a multi-agent system based on Large Language Models (LLMs) for quality assessment in customer service, aiming to overcome the limitations of traditional monitoring methods. The system implements an innovative architecture composed of five specialized agents: Supervisor, Quality Monitor, Operator, Judge, and Reporting Analyst, each responsible for specific aspects of the evaluation. The methodology employed the CrewAI framework for multi-agent system development, using the GPT-4o-mini model as a base, and implemented a web interface in Streamlit for user interaction. The system validation was performed through tests with a real dataset from an energy sector company, comparing its performance with specialized human evaluations and other language models. The results showed 90% to 100% agreement with human evaluations, significantly higher than the 50% achieved by approaches based on isolated models. The system maintained a consistent average time of 6 minutes per analysis, representing a reduction of up to 52% in the time required compared to traditional monitoring. The solution also demonstrated exceptional economic viability, with a 95.4% reduction in cost per analysis while maintaining high quality in evaluations. The quality of generated reports was validated by independent evaluators, obtaining an average score of 32.5/35. The developed system establishes a new paradigm for quality assessment in customer service, combining operational efficiency, economic viability, and consistency in analyses, allowing quality monitors to focus on higher value-added strategic activities.CC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/Inteligência ArtificialSistemas Multi-agenteAtendimento ao ClienteAvaliação de QualidadeGrandes Modelos de LinguagemProcessamento de Linguagem NaturalArtificial IntelligenceMulti-agent SystemsCustomer ServiceQuality AssessmentLarge Language ModelsNatural Language ProcessingbachelorThesisCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO::ENGENHARIA DE SOFTWARECNPQ::CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA::ANALISE DE DADOSCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOCNPQ::CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICACNPQ::ENGENHARIAS