Enhancing Tool Orchestration and Planning for Agentic RAG Systems: A Case Study - Miyaji, Renato; Bedin, Vitor; Moulin, Renato; Machado, Leonardo (Anais do Simpósio Brasileiro de Banco de Dados (SBBD); 2026: Anais do XLI Simpósio Brasileiro de Bancos de DadosDO - 10.5753/sbbd.2026.249641, 2026)
Traditional RAG faces bottlenecks in industrial environments. To address these limitations, this paper proposes an Agentic RAG architecture that decouples high-level strategic orchestration from technical execution through an LLM Supervisor and domain-specialized sub-agents. Using a proprietary dataset, we evaluate the efficacy of System 1 and System 2 reasoning paradigms alongside tool integration. Our experimental results demonstrate that ReWOO combined with Few-Shot execution guidance achieves a maximum success rate of 93.33%. Furthermore, we introduce an evaluation methodology which reveals that the ToolVerifier module is essential for complex planning. This study establishes that modular planning and robust verification are critical for reliability in knowledge-intensive industrial applications.