ImmiGo - An Adaptive Multilingual Chatbot for Immigration Assistance

This demo paper presents ImmiGo, an adaptive multilingual chatbot designed to effectively address user needs by providing accurate and timely responses to visa and immigration inquiries in users’ preferred languages. A system supporting such important inquiries relies on being up-to-date and accurate. To this end, ImmiGo is built on a sophisticated agentic Retrieval-Augmented Generation (RAG) pipeline, seamlessly integrating the Groq-accelerated OpenAI GPT-OSS-120B model for faster inference. The system also incorporates an advanced embedding model and a dynamic storage mechanism, leveraging a vector database to ensure efficient real-time retrieval, contextual accuracy, and robust handling of out-of-knowledge-base queries. Additionally, an ensemble document retrieval method and composite grading mechanism refine response quality by filtering less relevant context, ensuring that the language model generates precise, reliable, and factually accurate responses. The system underwent rigorous evaluation and testing for its multi-turn, multilingual, and conversational capabilities, demonstrating its ability to perform consistently across multiple scenarios.