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)
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.