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@article{196884,
        author = {Ms. Bhagyashri S. Chaudhari and Venkatesh S. Bathe and Parth S. Sonawane and Rohit M. Shitole and Aniket N. Kale},
        title = {Qnix- All-Rounder AI Chatbot for College Inquiry},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {5376-5379},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196884},
        abstract = {Chatbots have become indispensable in modern digital ecosystems by enabling real-time, intelligent, and interactive communication. This project presents the design and development of Qnix (Query + Theory), an all-rounder AI chatbot specifically developed for Polytechnic college inquiry and educational assistance. Qnix is built with multilingual capabilities (English, Hindi, Marathi) to enhance inclusivity among diverse student communities in India. In addition to answering general academic questions, Qnix supports educational guidance (programming, formulas, study help) and provides institution-specific details such as admissions, courses, faculty, and events at Trinity Polytechnic, Pune. The integration of Speech-to-Text (STT) and Text-to-Speech (TTS) makes Qnix more accessible to students who prefer voice-based interaction. By combining Natural Language Processing (NLP), Machine Learning (ML), and Speech AI, the system aims to replace inefficient, error-prone, manual inquiry processes with an automated, efficient, and user-friendly platform.},
        keywords = {Qnix, Text-To-Speech, Natural Language Processing},
        month = {April},
        }