In our previous work, a novel approach emphasizing a Knowledge Graph-based, distributed, and Collaborative conversational Artificial Intelligence (AI) multi-chatBot system (GraphCoBots) for museums was introduced, towards addressing limitations in scalability, knowledge reuse, and coordinated interaction across conversational services. The architecture was designed to deliver an efficient deployment solution where cultural knowledge can be distributed and shared among different chatbots that collaborate when needed. In this paper, we investigate the realization and effectiveness of this architecture through the implementation and evaluation of the GraphCoBots system. Three chatbot services were developed: (a) Nikos Kazantzakis Museum in Crete, (b) life and work of Nikos Kazantzakis and (c) selected artifacts of the museum. Two knowledge graphs (KGs) were designed and implemented, enabling structured knowledge representation, interoperability, and collaborative reasoning. The system was also designed to utilize external Linked Open Data (LOD) sources. An expert’s evaluation was conducted to assess usability and interaction quality. The outcome indicated that users prefer receiving comprehensive information delivered in a human-like manner, without encountering technological barriers or complexity. Based on these findings, the researchers integrated Generative AI services, addressing limitations and improving system efficiency. Finally, a broad audience evaluation was conducted, leading to further improvements.