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Technical Case Study
Implementing RAG in a Production-Ready AI Complaint Management System
The Core Objective
Traditional complaint systems lack intelligent prioritization and contextual response generation.
01.Engineering Approach
Built an NLP-driven chatbot integrated with Retrieval-Augmented Generation (RAG) to improve contextual accuracy and reduce hallucination.
02.System Architecture
Chatbot powered by NLP classification engine, vector-based retrieval layer, LLM API integration, and automated ticket creation system.
03.Lessons Learned
- RAG pipelines are essential for production-grade LLM systems.
- Persistent chat memory significantly improves user experience.