Abstract

This paper details the development of a service-oriented, LLM-powered assistant integrated into complex web applications to enhance user interaction. The assistant provides context-aware, real-time support, guiding users through workflows, minimizing cognitive load, and aligning decisions with UI actions. The current system achieves situational assistance, guided dialogs, and real-time data access but faces challenges such as prompt efficiency and maintaining context accuracy over prolonged use. While promising, the assistant requires further refinement for full-scale reliability and precision. Future work focuses on fine-tuning for specialized knowledge retention and structured outputs to enhance consistency. This approach demonstrates the potential of service-embedded AI to improve user experiences through context-driven, adaptive support.

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