The swift evolution of artificial intelligence (AI) has revolutionized customer service systems, especially with the incorporation of AI-based chatbots in complaint management systems. In this paper, the creation and refinement of a complaint management system based on an AI-based chatbot are discussed with a view to enhancing user experience, minimizing time for resolution, and increasing operational efficiency. Through natural language processing (NLP) and machine learning algorithms, the chatbot is programmed to interpret user complaints, categorize grievances, send real-time updates, and escalate issues when required. The system presented seeks to mitigate typical drawbacks of conventional complaint handling, including waiting periods, human errors, and limited scalability. One of the important aspects of the system is its capability to process user sentiment so that sensitive or urgent complaints are processed on priority. The paper also introduces a modular system architecture involving authentication, query understanding, feedback collection, and reporting modules, among others. Test cases and evaluation criteria are detailed to verify the performance, accuracy, and reliability of the chatbot. The paper ends on a note of optimism that the system has the capacity to revolutionize complaint handling practices in different industries, providing a future-proof solution that evolves with changing user requirements and organizational needs.
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Chabot AI-based, complaint management system, NLP, ML, automation of customer service, sentiment analysis, complaint classification, real-time updates, escalation management, user experience.
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