International Journal on Science and Technology

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Domain-Specific Conversational Agents: Revolutionizing Customer Service

Author(s) Swapnil Hemant Thorat
Country United States
Abstract Domain-specific conversational agents are transforming customer service by addressing the limitations of traditional models that struggle with high volumes, inconsistent quality, and scaling challenges. These intelligent systems leverage fine-tuned Large Language Models on industry-specific data to understand complex terminology, navigate specialized processes, deliver personalized interactions, and manage multi-turn conversations while recognizing when human intervention is needed. The technical architecture requires sophisticated natural language understanding, seamless system integration, robust context management, graceful handover mechanisms, and scalable infrastructure. Implementation follows a structured approach encompassing data collection, model fine-tuning, integration development, conversation design, testing, and deployment with continuous monitoring. Emerging trends include multimodal interactions, proactive service capabilities, enhanced emotional intelligence, and sophisticated learning mechanisms that adapt from each interaction. These advancements create a balanced ecosystem where AI efficiently handles routine tasks while humans focus on complex situations requiring expertise and empathy.
Keywords Conversational AI, Domain-specific agents, Natural language understanding, Context management, Human-AI collaboration
Field Computer
Published In Volume 16, Issue 1, January-March 2025
Published On 2025-03-22
Cite This Domain-Specific Conversational Agents: Revolutionizing Customer Service - Swapnil Hemant Thorat - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.2755
DOI https://doi.org/10.71097/IJSAT.v16.i1.2755
Short DOI https://doi.org/g892dm
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