Paper Details

The development of artificial intelligence and natural language processing (NLP) technologies has realized a shift in the paradigm of handling customer services by companies. The paper will present a detailed description of NLP-based chatbot applications to assist customers, including the architectural paradigms, basic NLP components, deep learning algorithms, industry-related applications, performance metrics, and ethical standards. We address rule-based, retrieval-based, and generative models and specifically the transformer-based models, such as BERT, DistilBERT, GPT-3, and DialoGPT. We discuss such problems as context retention, multilingual support, unbalanced classes and more advanced approaches, such as retrieval-augmented generation (RAG), sentiment analysis, and voice-based communication. It is a compilation of published benchmark findings, case studies in e-commerce, banking, healthcare and hospitality and analysis of key performance indicators. The paper concludes by identifying the open research challenges and future directions, such as multimodal interaction, explainable AI, and ethical AI development.

Nazma A. Inamdar, Ganesh Anil Ghewari, Shaikh Nihalahamad Aslam, “Chatbots Using Natural Language Processing for Customer Support: Architecture, Techniques, Applications, and Future Directions”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 13, Issue 4, pp. 48-59, April 2026.