Nice Intelligent Network Assistant (NINA): A Multi-Lingual Chatbot API for Subscription and Order Services Using REST and GraphQL

Authors

Tinashe Crispen Garidzira, University of Fort Hare, South Africa

Courage Matobobo, Walter Sisulu University, South Africa

Published in

IST-Africa 2026 Conference Proceedings

ISSN: 2576-8581

ISBN: 978-1-905824-76-2

DOI: https://doi.org/10.67725/IST-Africa.2026.PKFY4109

Publisher

IST-Africa Institute and IIMC International Information Management Corporation Ltd

Published in Ireland

Abstract

This study presents Nice Intelligent Network Assistant (NINA), a multilingual chatbot designed to support subscription and order services via both REST and GraphQL APIs. Developed following the CRISP-DM methodology, NINA integrates natural language processing (NLP) techniques to recognize user intent, extract key entities, and generate accurate responses. The system supports multiple languages, including English, Xhosa, Shona and Ndebele, by translating user inputs into English using Google Translate before intent classification. A Bi-Directional Long Short-Term Memory (Bi-LSTM) model was trained on a Kaggle dataset to classify English-language intents with high precision. The model achieved 100% test accuracy with zero test loss, demonstrating its robustness and reliability. These results underscore NINA's ability to deliver consistent and efficient support without human supervision. By combining deep language understanding with flexible API deployment, this work highlights the potential of multilingual AI assistants to enhance user experience and service delivery across diverse linguistic contexts.

Keywords

Multilingual Chatbot, Natural Language Processing (NLP), Bi-Directional Long Short-Term Memory (BiLSTM), REST APIs, GraphQL APIs

Cite this paper

T.C. Garidzira and C. Matobobo (2026) "Nice Intelligent Network Assistant (NINA): A Multi-Lingual Chatbot API for Subscription and Order Services Using REST and GraphQL", IST-Africa 2026 Conference Proceedings, Miriam Cunningham and Paul Cunningham (Eds), IST-Africa Institute and IIMC, 2026, ISSN: 2576-8581, ISBN: 978-1-905824-76-2, https://doi.org/10.67725/IST-Africa.2026.PKFY4109

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