Case Study 7
No Guesswork, Just Clear Guidance: AI Standardizes Service Excellence for a Leading Education Assessment Organization

Simplifying complex queries with AI-orchestrated customer support

The Question: How could the organization manage these complex queries without adding manpower, while simplifying the process for the agents involved?

Disconnected systems led to fragmented knowledge and inconsistent responses.
Manual processes were inefficient and non-scalable, increasing handle times.
High training costs due to non-standardized, complex processes.
Agents struggled with test scheduling, fee returns, and policy clarifications, contributing to long resolution timelines.

About the Client

The client, a leading education assessment organization, managing millions of test-takers annually and handling complex inquiries from students and institutions, struggled to manage over 20,000 complex help desk queries annually and deliver quick, consistent, and policy-aligned resolutions.

The Answer

RAG Core + Knowledge Graph: Indexed policies, FAQs, guides, and historical tickets for structured understanding and precise retrieval.
Multi-system Orchestration: Automation of routine lookups within refunds, scheduling, and CRM systems.
Guided Workflows: Step-by-step assistance for complex processes, empowering agents with confidence.
Trustworthy AI Outputs: Integrated compliance and traceability controls to ensure accurate, policy-aligned responses.
Seamless Integration: Fully embedded into the Help Desk tools for smooth human-AI collaboration.

To align their customer service operations with the demands of a high-pressure industry, the client leveraged an agentic AI foundation for their Education Services Platform.

The Outcomes

With the implementation of AI-driven strategies, the client achieved measurable improvements in operational efficiency and customer satisfaction.

40% reduction in Average Handle Time (AHT) led to faster resolutions, transforming customer experience.
30% reduction in agent training time enabled quicker onboarding.
10–20% improvement in First Contact Resolution (FCR) enhanced service accuracy.
Consistent and transparent interactions, facilitating policy-aligned and explainable responses, ensured trust among users.
A scalable AI foundation laid the groundwork for future AI advancements to support students, educators, and internal teams.

The deployment of Retrieval-Augmented Generation (RAG) and guided workflows revolutionized the client’s help desk operations, paving the way for scalable, AI-driven support services.