How AI Simplified a High-Volume Customer Support Workflow

Client Overview

This insurance client was looking to bring automation into its customer service operations. Rather than adding more manual effort as interaction volumes increased, they wanted to see where AI could handle repetitive work in the background. This led to a focused opportunity to rethink how information from customer interactions was managed.

The Challenge

• • Every customer call created additional documentation work for the support team.
• Agents had to manually turn conversations into usable policy information.
• Important policy updates depended on the completion of post-call tasks.
• As call volumes grew, keeping the process efficient became increasingly difficult.

The Solution

We used AI to redesign the workflow so the support team no longer had to manually turn every completed call into a policy update.

• The process starts automatically when a customer call is completed.
• It gathers the conversation along with the customer and agent information needed for documentation.

• An LLM identifies what matters from the interaction and condenses it into a useful record.
• Important decisions, next steps, and customer-specific information are retained.
• The result is turned into a standardized policy note that is ready for the next step.

• The AI-generated output is passed through APIs to the policy management system.
• The workflow maps each generated note to the appropriate policy, eliminating the need to update policy records manually.

Business Outcome

The biggest impact came from removing a high-volume, repetitive task from the support team’s daily workload. The automation saves around 334 hours every day while ensuring the information from each conversation flows into the policy record without another manual step. It also gives agents more time to stay focused on customers rather than post-call administration.