1. Overview (Project Background)

This project is an AICX Counselor Chatbot PoC,
and was initiated to validate functional feasibility of whether generative AI can improve counselors' work efficiency.

To enable faster and more accurate responses to repeatedly occurring inquiries during international flight consultations,
we built a generative AI chatbot exclusively for counselors
and applied RAG (Retrieval-Augmented Generation) structure based on international flight counselor processing guides.

Additionally, we connected practical functions such as consultation history inquiry and airline ticket refund fee calculation through APIs,

Before project initiation,
KMS, refund fee calculation tools, and consultation guide documents were provided in separate environments,
and consultation guides were managed in Excel file format, resulting in low searchability and usability.
In particular, the structure requiring manual calculation of airline ticket refund fees
caused inefficiencies in both consultation processing speed and accuracy.

2. Solution (Resolution Approach)

To resolve these issues,
we configured a Vector DB-based RAG pipeline specialized for counselor tasks.

We loaded counselor processing guide documents and airline-specific regulation documents
into an OpenSearch-based Vector DB,
and designed the system so that generative AI accurately understands counselors' query intent through semantic search
and generates responses based on relevant documents.

Through this, we implemented a consultation support structure that enables
context-based search and consistent answer provision, rather than the existing keyword search-focused approach.

3. Result (Achievements)

Through this PoC, we were able to validate the effectiveness of generative AI-based consultation support.

Counselors can now quickly search for airline-specific regulations and processing standards
through natural language queries alone,
and have secured an environment where consistent answers can be provided for identical questions.

Additionally, by automating airline ticket refund fee calculations,
we reduced the time required and error potential from manual calculations,
and confirmed that overall consultation processing speed and work efficiency can be improved.