Transforming Support Operations with Gen AI

Executive Summary

This case study explores how a leading US real estate company, with CentraLogic, transformed their support operations using an AI-driven Support Agent. The Support Agent efficiently classified emails, filtered spam, and provided intelligent responses, significantly improving efficiency and response times. Testimonials highlight enhanced operations and satisfaction. 

 
The Challenge

A leading US real estate firm faced challenges with high volumes of support emails, overwhelmed by spam and marketing messages. To address this, they partnered with CentraLogic to implement Support Agent, an AI-powered tool leveraging LLMs to prioritize essential emails, filter out non-essential ones, and organize them into separate queues. Support agents were further assisted by an advanced LLM-based RAG framework, enhancing efficiency and response time.

Our Approach

Data Analysis

We conducted an in-depth analysis of the support team's operations to identify where time was being spent and which tasks could be automated with AI. This allowed us to prioritize areas that would benefit most from AI intervention, ensuring maximum impact.

Customizable Solution

We crafted a solution tailored to the support team's specific needs. This framework can be customized to accommodate various numbers of pipelines, incorporating features like intelligent query routing and automated responses. 
 

Implementation

Adhering to agile principles, we broke the solution into smaller components for rapid development and deployment. This approach allowed us to deliver key features quickly, incorporating feedback and adjustments along the way to maximize effectiveness.  

 

We conducted an in-depth analysis of the support team's operations to identify where time was being spent and which tasks could be automated with AI. This allowed us to prioritize areas that would benefit most from AI intervention, ensuring maximum impact. 

 
In-Depth Data Analysis

 

We crafted a solution tailored to the support team's specific needs. This framework can be customized to accommodate various numbers of pipelines, incorporating features like intelligent query routing and automated responses. 
 
 
Customizable Solution
Adhering to agile principles, we broke the solution into smaller components for rapid development and deployment. This approach allowed us to deliver key features quickly, incorporating feedback and adjustments along the way to maximize effectiveness.
Implementation Proccess

Outcomes Achieved

Real-Time Processing

  • The support bot classifies and responds to emails in under 3 seconds, ensuring rapid handling of customer queries. 
  • This automation accelerates response times and significantly improves overall operational efficiency. 

Reduced Workload

  • Automated classification and filtering of emails handle 50% of incoming messages, reducing manual effort.  
  • This allows the support team to allocate more time and resources to focus on complex, high-priority tasks.  

Insightful Analytics

  • The system generates detailed insights from email interactions, providing valuable data for decision-making.  
  • By analyzing these metrics, it helps identify trends and pinpoint areas where support processes can be improved.  

Proactive Email Response

  • The system identifies and flags 30% of critical emails, sending automated follow-up responses within minutes.
  • This proactive approach boosts customer satisfaction by 25% and ensures no important messages are overlooked.

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