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@article{178916,
        author = {Tabrez and Tanisha Srivastava and Syed Raza ali and Falak Alam},
        title = {AI-Powered Chatbot Framework for Automated Customer Service},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4916-4921},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178916},
        abstract = {In the rapid digital age, organizations are moving toward AI-driven solutions to increase the efficiency of customer service. In this paper, a holistic AI-driven customer service chatbot has been presented to provide 24/7 customized support using enhanced natural language processing (NLP) technologies. The chatbot is easy to integrate with workflows, has an easy-to-use interface, instant response generation, and a continually updated knowledge base. Based on the MERN stack (MongoDB, Express.js, React, Node.js), this modular framework provides scalability and flexibility. The chatbot facilitates operational efficiency through automated repetitive tasks, higher response accuracy, and useful customer insights. Planned improvements include multilingual support, voice interface support, and machine learning-based personalization. Through this solution, organizations can attain enhanced customer satisfaction, lower operational costs, and more efficient service workflows.},
        keywords = {AI Chatbot, Customer Support Automation, Natural Language Processing, MERN Stack, Machine Learning, CRM Integration, Real-Time Response, Chatbot Architecture, Business Workflow Integration, Voice Assistant Support},
        month = {May},
        }