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@article{171930,
        author = {Manya A J and Subhash N and Abhishek A and Shaik Nihal Basha and N Sultan Basha and Dr.Joseph Michael Jerard V},
        title = {Machine Learning-Powered Customer Support Chatbot},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {1469-1472},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171930},
        abstract = {This research paper explores the development of an intelligent NLP-powered chatbot designed to address the challenges of traditional customer service, which often relies on slow and resource-heavy manual processes. The chatbot can autonomously understand and resolve customer complaints, and if it cannot find a solution, it escalates the issue to a support team member. A key feature of the bot is its ability to learn from every interaction, improving its problem-solving capabilities over time. The study evaluates the system using metrics like escalation rate and response time, finding that the chatbot leads to faster resolutions and reduced reliance on human intervention, ultimately improving customer satisfaction. The research demonstrates how AI-driven chatbots can offer scalable, flexible, and continuously improving customer support, making them a more efficient and cost-effective alternative to traditional methods.},
        keywords = {AI-powered chatbot, Natural Language Processing (NLP), customer service, complaint resolution, escalation process, self-learning, customer satisfaction, response time, scalability, cost-effective, human intervention, automation, continuous improvement, intelligent chatbot, customer support.},
        month = {January},
        }