Grace Kevine Ngoufo
2026
Building a Conversational AI Assistant for African Travel Services with LLMs and RAG
Grace Kevine Ngoufo | Shamsuddeen Hassan Muhammad | Kevin Jeff Fogang Fokoa
Proceedings of the 7th Workshop on African Natural Language Processing (AfricaNLP 2026)
Grace Kevine Ngoufo | Shamsuddeen Hassan Muhammad | Kevin Jeff Fogang Fokoa
Proceedings of the 7th Workshop on African Natural Language Processing (AfricaNLP 2026)
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face increasing pressure to handle large volumes of customer inquiries with limited staff or, either non-existent or outdated rule-based chat-bots. 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, context-aware 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.