Chatbot uses Natural Language Processing (NLP) to analyse requests and to provide responses. Chatbot supports the languages it is designed for. A challenge faced is the difference between languages in the corpus with the expected response language in the chatbot application. The paper provides findings of a case study on a chatbot that extracts university admission Frequently Asked Questions (FAQ). The chatbot uses Google Translate API as the backbone and an innovative algorithm that matches questions and answers with the FAQ corpus. The case study has produced findings of a potential dual-language chatbot design that allows real-time translation from a corpus in English to answer specific questions in Bahasa Melayu.