Transport & Logistics — User Intent Classification for RAG Agent Interaction

Overview

The purpose of this DAG is to improve user-agent interactions in the Transport and Logistics sector by accurately classifying user intents. It ingests data from various sources, including CRM interaction logs, ITSM ticket data, and user feedback forms. The ingestion pipeline normalizes this data to ensure consistency and prepares it for analysis. The processing steps involve intent identification through natural language processing algorithms, followed by quality control measures to validate the

The purpose of this DAG is to improve user-agent interactions in the Transport and Logistics sector by accurately classifying user intents. It ingests data from various sources, including CRM interaction logs, ITSM ticket data, and user feedback forms. The ingestion pipeline normalizes this data to ensure consistency and prepares it for analysis. The processing steps involve intent identification through natural language processing algorithms, followed by quality control measures to validate the accuracy of the classifications. These measures include cross-referencing with historical data and implementing feedback loops for continuous improvement. The outputs of this DAG include classified intent data, insights on user behavior, and reports on agent performance. Key performance indicators (KPIs) are monitored throughout the process, focusing on customer satisfaction scores and response times. The business value derived from this DAG is significant, as it enables RAG agents to provide faster, more relevant responses, ultimately leading to improved customer satisfaction and retention in the highly competitive Transport and Logistics industry.

Part of the AI Assistants & Contact Center solution for the Transport & Logistics industry.

Use cases

• Enhanced customer satisfaction through timely responses
• Improved agent efficiency with accurate intent classification
• Data-driven insights for better decision-making
• Increased retention rates in a competitive market
• Streamlined operations through automated intent processing