Creation of a chatbot assistant for improving client service

Abstract

The rapid evolution of client service technologies poses both challenges and opportunities, particularly in harnessing artificial intelligence to enhance interaction quality and efficiency. This thesis presents the development and implementation of a sophisticated multi-agent chatbot system designed to improve client services at Voxist. Titled “Building a Chatbot Assistant to Enhance Client Services,” this work focuses on overcoming the inherent limitations of large language models (LLMs), such as the inability to access private data sources, lack of real-time updates, and limited reasoning capabilities. The core of the proposed solution involves a structured multi-agent system centered around a Meta Agent that orchestrates interactions among various specialized sub-agents. Each subagent is tailored to specific roles, enabling dynamic interactions, real-time data management, and the execution of complex functions. The system leverages Retrieval-Augmented Generation (RAG) to enhance the chatbot’s responsiveness and access to updated information, significantly improving the chatbot’s ability to handle sensitive data, execute commands, and perform operational tasks efficiently. Additionally, by effectively prompting the LLM, the system enhances its reasoning capabilities, enabling more accurate and contextually aware responses. Key outcomes from this implementation indicate that the multi-agent system effectively addresses the limitations of traditional LLMs by facilitating secure access to private databases, enabling real-time updates, and enhancing reasoning abilities. The system not only improves operational efficiency but also ensures that interactions are personalized and contextually aware, which are critical for maintaining client trust and satisfaction. In conclusion, the implementation of this multi-agent system at Voxist represents a transformative step in enhancing client services. By integrating advanced technologies, strategic agent roles, and enhanced reasoning capabilities, the system offers scalable solutions that adapt to evolving business needs and client expectations, showcasing the robust capabilities of AI-driven chatbot systems.