Industry
Energy and Utilities
Challenge
Manual call summarization, a lack of transcription capabilities, and high call volume created costly inefficiencies and slow documentation.
Results
The AI solution reduced call documentation time by 50%, saving 20% per call and lowering average handle time by up to 20%.
Technologies That Powered the Transformation
OpenAI, Azure Webapp, Azure Functions, ConvergeOne, Azure Communication Services
Overview
A Fortune 250 energy and utility company partnered with rSTAR to modernize its call center operations and reduce the burden on customer service agents. Agents were previously required to listen, respond, and summarize calls manually—often under time pressure and without transcription support. rSTAR introduced an AI-powered Agent Assist solution that transcribes calls in real time and generates structured summaries, enabling faster, more accurate documentation and paving the way for deeper call analytics and service improvements.
Business Problem & Stakes
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Agents had to listen, take notes, and summarize each call, increasing the risk of errors or incomplete documentation.Call Summarization Slowed Down Agents:
- No Built-In Transcription Capabilities:
IVR lacked transcription, preventing automated summaries or call analysis and limiting visibility into agent performance. - High Call Volume Across Divisions:
The utility received 60,000 to 80,000 monthly calls enterprise wide, and managing this volume manually was expensive.
rSTAR Solution
- Real-Time Transcription and Summarization:
Created a real-time call transcription and summary solution that captured key details. - Custom UI for Seamless Agent Experience:
A user-friendly interface was built to display live transcriptions and enable quick summary generation. - Scalable Architecture for Enterprise Deployment:
Scalable AI solution easily handled high call volume and lays the groundwork for quality scoring, coaching, and sentiment analysis.
