AI-Based Chatbot System for Automated Customer Support Using NLP and Machine Learning

This study presents an intelligent chatbot system developed to automate customer support services in digital platforms. As user expectations for instant responses continue to grow, traditional support mechanisms face limitations in scalability and availability. The proposed system combines Natural Language Processing and Machine Learning techniques to interpret user queries and generate meaningful responses. A DistilBERT-based model is applied for intent detection, while a Named Entity Recognition module identifies relevant information within user input. The system was trained using conversational datasets and tested through multiple evaluation measures. The results demonstrate strong performance in terms of accuracy and response efficiency, significantly improving over manual support approaches. These findings suggest that the proposed chatbot can be effectively deployed in real-world customer service environments.

Artificial Intelligence, Chatbot, Natural Language Processing

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