Support-Agent

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.

Revolutionizing Real Estate Sales Transactions through AI Innovation

Enhancing accuracy

This project strives to transform the real estate sales transaction process by harnessing state-of-the-art AI technologies.The innovative approach proposed involves the utilization of Language Models (LLMs) and advanced deep learning models.The primary objectives are to enhance accuracy, streamline efficiency, and achieve scalability in real estate transactions.The integration of cutting-edge technologies marks a significant shift in the traditional real estate industry paradigm. The use of LLMs and deep learning models ensures a sophisticated and precise methodology for transactional processes.The focus is on continuous monitoring and updates, underlining the commitment to sustained and long-term success.This initiative aims to revolutionize how real estate transactions are conducted, paving the way for a more efficient and effective system.

The Challenge

A leading US real estate firm struggled with high volumes of support emails, often overwhelmed by spam and marketing emails coming to agent support email. To address this, they partnered with CentraLogic to implement Support Agent, an AI based tool with the aim to improve golden time for support personnel. This was achieved by the use of AI and LLMs to incoming emails that need support personals attention and filtering out all non-essential, spam and marketing email and moving those into separate queues. The support agents were also assisted by LLM based advanced RAG framework.

OUR SOLUTION

1

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.

2

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. The design prioritizes user experience to ensure seamless adoption and integration.

3

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.

BENEFITS

Real-Time Processing

The solution delivers immediate email classification and responses. While human agents typically take two to three minutes to analyze an email, the support bot completes this in less than 3 seconds, significantly accelerating response times and enhancing efficiency.

Insightful Analytics

The system provides valuable data on email interactions, offering insights that can drive strategic improvements. Analyzing these metrics helps identify trends and areas for enhancement in support processes.

Reduced Workload

The automated classification and filtering of emails reduced the workload on the support team, with 50% of emails handled by the Support Agent, allowing the team to allocate their time and efforts more effectively.

Proactive Email Response

The system identifies and flags 30% of critical emails, sending automated follow-up responses within minutes. This approach has led to a 25% increase in customer satisfaction while significantly improving operational efficiency by ensuring no important messages are missed.

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