Agentic AI Solution Delivers Speed and Efficiency
A leading provider of specialty logistics services engaged CapTech to reduce workforce costs, improve operational efficiency, and maintain customer satisfaction.
Topic
Summary
For a logistics company, time is of the essence. However, as this leading provider of specialty logistics services grew through acquisition and expanded its global footprint, it faced challenges due to the increasing volume of manual activities that accompanied this growth. Wanting to keep its existing transportation management system (TMS) intact due to budget and time considerations, the company was looking for a way to manage these inefficiencies through automation solutions.
Challenge
Through a process assessment, interviews, and shadowing sessions, CapTech discovered that email volume was driving highly manual, time-intensive tasks for customer service representatives. Emails containing unstructured order creation information requests, "Where’s my package?" inquiries, and routing and re-rerouting requests were focusing customer service representatives’ attention away from addressing questions that were critical and more time sensitive. The logistics company engaged CapTech to develop a solution to improve operational efficiency, reduce workforce costs, and maintain customer satisfaction in the process.
Approach
For the greatest impact, our solution had to understand a variety of communication styles, interpret customer requests, execute repeatable tasks, and close the loop with minimal human oversight. Because of the nature of their business, the client knew that responding to the nuances of each customer’s needs and communication style would require more than traditional, rules-based workflows.
Results
CapTech worked with the client to create an agentic artificial intelligence (AI) solution to address a variety of customer requests, creating opportunities to expand AI capabilities in the future. Unlike generative AI, which requires humans to direct its task completion, agentic AI adjusts to new information as conditions change and carries out tasks in real time. The first agentic AI use case automated the process of converting unstructured order creation email messages from customers into new orders in the existing TMS that are ready for routing.
Today’s AI agents have been trained to:
- Review email threads and understand the new order request
- Extract essential shipment information
- Create new orders
- Provide a confirmation message and tracking information to the customer
By automating these tasks, the company can accelerate responses to routine email requests and empower customer service representatives to respond to emails requiring more complex and unique thinking.
