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@article{195349,
        author = {Meesala Sai Lakshmi and Kodukula Nikhil and Nagarambilli Yogeswar Rao and Vanapalli Jyothika and K. T. DANIEL MOHAN},
        title = {DESIGN AND DEVELOPMENT OF AI-POWERED CUSTOMER SUPPORT CHATBOT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {7547-7549},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195349},
        abstract = {The rapid evolution of digital technologies has significantly increased the demand for efficient and real-time customer support systems. Traditional customer service methods rely heavily on human intervention, which often leads to delays, high operational costs, and limited scalability. To overcome these challenges, this research presents the design and development of an AI-powered customer support chatbot capable of understanding and responding to user queries intelligently.
The proposed system leverages Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) techniques to simulate human-like interactions. It incorporates preprocessing techniques such as tokenization, stop-word removal, and lemmatization, along with feature extraction methods like Bag of Words (BoW) and TF-IDF to transform textual data into meaningful representations. A supervised machine learning model is employed for intent classification, enabling accurate response generation.
The chatbot is implemented using a web-based architecture consisting of a frontend interface and a backend processing unit. The system is evaluated using performance metrics such as accuracy, precision, recall, and F1-score. Results demonstrate improved response time, enhanced user experience, and reduced dependency on human agents.
This system can be applied across various domains including e-commerce, healthcare, and education. Future enhancements include deep learning integration, multilingual capabilities, and voice-based interaction.},
        keywords = {Artificial Intelligence, Chatbot, Natural Language Processing, Machine Learning, Customer Support, Automation, TF-IDF, Intent Classification},
        month = {March},
        }