TITLE:
Empathetic Agents in Generative AI Applications
AUTHORS:
Siow Yen Chong, Aishwar Gupta, Vijay K. Madisetti
KEYWORDS:
Emotion-Aware AI, Conversational Agents, Sentiment Analysis, Retrieval-Augmented Generation, Large Language Models
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.19 No.3,
March
11,
2026
ABSTRACT: We present EAGAA, an emotionally intelligent agent integrating real-time sentiment and emotion analysis with Retrieval-Augmented Generation (RAG) to deliver empathetic customer support at scale. EAGAA employs a multilayered pipeline: SentimentAgent, ManagerAgent, TaskAgents, ResponseGenerator, and SessionManager to adapt tone and personality dynamically. In extensive evaluations including 100 simulated sessions and a 200-user survey, EAGAA achieved a 77% F1 on emotion benchmarks, 98.6% top-1 retrieval accuracy, sub-second median latency, and a 4.85/5 CSAT score, outperforming baselines by over 20%. This work demonstrates the viability of human-like, scalable emotion-aware AI.