This thesis explores the use of Generative AI agents, Retrieval-Augmented Generation (RAG) systems, and the Model Context Protocol (MCP) to improve knowledge management within complex organizational contexts. Conducted at Reale Mutua Assicurazioni within the Data Science Center of Excellence, the work focuses on two Proofs of Concept: the POD Assistant, a multi-agent system designed to support project teams in managing documentation and interacting with corporate platforms such as Azure DevOps, and the CGA Copilot, a chatbot specialized in querying and interpreting lengthy and technical insurance documents (General Conditions of Insurance). The research combines multi-agent architectures orchestrated through LangGraph, hybrid retrieval pipelines with semantic re-ranking on Azure AI Search, and the integration of MCP for scalable tool interoperability.