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Faster First Call Resolution with AI-Powered Knowledge at Agents’ Fingertips

See how a Fortune 250 energy company used an Azure AI Knowledge Base to reduce call center handle times, improve first-call resolution, and enhance customer service

Industry

Energy and Utilities

Challenge

Agents struggled with long calls and low first-call resolution due to scattered data, multiple systems, and limited guidance for complex issues.

Results

The new AI knowledge base led to 30% faster responses and improved first-call resolution, with over 80% positive user feedback.

Technologies That Powered the Transformation

SharePoint, ProcedureFlow, Oracle Service Cloud, Customer Website, Oracle Customer Care & Billing, Azure AI Foundry

30% Faster Responses

The AI-powered Knowledge Base enables CSRs to find resolution steps almost instantly, significantly reducing the time spent navigating systems.

 

Improved First Call Resolution

With faster access to accurate information, CSRs are better equipped to resolve issues on the first call—enhancing customer satisfaction and reducing repeat inquiries.

 

80% Positive User Feedback and Ongoing Enhancements

The solution has been well-received by agents, who appreciate the ease of use and speed. Continuous feedback is being used to refine and expand the system’s capabilities. It helps new agents handle calls confidently.

 

energy & utilities AI

Overview

A Fortune 250 energy and utility company set out to reduce Average Handle Time (AHT) and improve First Call Resolution across its call center operations—a top priority for the year. The goal was to improve efficiency, reduce operational costs, and deliver a more consistent and satisfying customer experience. To achieve this, the company partnered with rSTAR to implement an Azure AI Foundry-powered Knowledge Base that centralizes information and empowers customer service representatives (CSRs) to resolve inquiries faster and more accurately.

Business Problem & Stakes

  • Long Average Handle Times:
    CSRs faced long handle times due to navigating multiple systems for information, causing delays and inconsistent service.
  • Scattered Information Across Systems:
    Critical data was scattered, forcing agents to search multiple sources, increasing response times and risk of errors.
  • Limited Guidance for Complex Scenarios: 
    CSRs struggled with complex queries due to a lack of unified system support, slowing resolutions and reducing first-call success.

 

rSTAR Solution

  • AI Knowledge Base with Natural Language Search:
    rSTAR launched an AI-powered Knowledge Base that enables CSRs to quickly find answers using natural language.
  • Generative AI for Dynamic, Contextual Responses:
    The GenAI solution mimics a ChatGPT-like tool, dynamically pulling data to deliver tailored answers—helping CSRs respond more accurately and efficiently.
  • Integrated Guidance and Feedback Loop:
    The system offers guided procedures and lets CSRs give feedback, ensuring the Knowledge Base continually evolves with user needs.

 

Download The Case Study

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