Empathetic Agents in Generative AI Applications
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.
Fields of Study & Subjects
AI in Service Interactions
Sentiment Analysis and Opinion Mining
Emotion and Mood Recognition
Publication details
- Journal / source
- Journal of Software Engineering and Applications
- Volume
- 19
- Issue
- 03
- Pages
- 25–54
- Publication date
- 1 January 2026
- Language
- EN