Enhancing Customer Engagement through an AI-Powered Chatbot for Product Presentations and Demonstrations

Abstract

This paper presents the design and deployment of an AI-powered chatbot developed by HAVELSAN to enhance customer engagement and streamline product-related interactions in the software industry. The system integrates intention understanding, retrieval-augmented generation (RAG), robotic process automation (RPA), large language models (LLMs), and large audio models to deliver accurate, context-aware, and multimodal interactions. Implemented within HAVELSAN’s business intelligence (BI) ecosystem, the chatbot achieved a 30% increase in customer satisfaction, a 50% reduction in inquiry response times, and 92% response accuracy for product-specific queries. Additionally, voice-based interactions accounted for 25% of total engagements, improving accessibility and user experience. Case studies revealed improved product demonstrations that drove higher conversion rates and better understanding of technical features. These results validate the transformative role of AI-driven tools in enterprise engagement, providing a scalable and secure framework adaptable across industries. Future enhancements will target personalized interactions via adaptive machine learning and deeper integration with enterprise platforms, positioning the system as a cornerstone of next-generation digital engagement strategies.

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