Year: 2026
Type: conference-paper
Abstract: Travel agencies in many African countries face increasing pressure to handle large volumes of customer inquiries with limited staff or, either non-existent or outdated rule-based chatbots.To address this challenge, we develop a conversational virtual assistant powered by a Large Language Model (LLM) and enhanced with a Retrieval-Augmented Generation (RAG) pipeline.The system combines LLM reasoning, company-specific knowledge retrieval, and real-time API (Application Programming Interface) integration to deliver accurate, contextaware responses through WhatsApp, the region's most widely used communication platform.A dedicated web interface enables staff to upload and update internal documents, ensuring that the assistant remains aligned with changing service information.Demonstrations show that the proposed solution improves response speed, enhances user experience, and reduces operational burden.
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7140075377