Improving customer experience for a global telecom leader

Reducing investigation time, strengthening test confidence and speeding licensing turnaround across a complex application landscape.

5 min Lesen

Published: 14 September 2026

Last updated: 14 September 2026

Overview

A leading global telecommunications company set out to improve the efficiency and reliability of its enterprise application ecosystem while supporting broader digital transformation goals. With a large-scale environment spanning legacy and modern systems, the priority was to reduce complexity, improve developer productivity and create a more responsive operating model for the business.

The Challenge

The client's enterprise application environment was under pressure from a mix of legacy architecture, high transaction volumes and deep dependency chains across multiple value streams. These conditions made it harder to resolve issues quickly, reproduce production behavior in test environments and maintain applications at scale.

The main challenges included:

High mean time to detect issues and slower debugging due to limited proactive monitoring and intelligent diagnostics.
Difficulty reproducing production issues in test environments because of incomplete or inconsistent test data.
Complex dependencies across multiple value streams, extending investigation time and root-cause analysis.
Time-intensive test design and maintenance as business logic evolved while automation capabilities remained limited.

The Solution

HCLTech implemented a GenAI-led, automation-first approach to improve engineering efficiency, troubleshooting speed and testing productivity across the client's enterprise application ecosystem. The engagement combined application support with targeted modernization initiatives that translated technical improvements into greater business responsiveness.

Key elements of the solution included:

Amazon Q for development support to accelerate debugging, improve code understanding and reduce investigation effort.
A rule-based NLP agent for bottleneck detection to identify likely root causes more quickly.
An AI-powered test data replication solution to support issue replication and test data creation, reducing dependence on manual analysis.
Microsoft Copilot and Amazon Q to improve testing efficiency and shorten delivery cycles.
A joint client–HCLTech governance model with regular reviews and demonstrations to maintain alignment on priorities and delivery outcomes.

The Impact

The new operating model delivered measurable gains in adoption, productivity, quality and customer turnaround. The business achieved faster license key delivery, stronger test reliability and reduced manual effort across support and engineering workflows.

Highlights included:

33% improvement in customer wait times and operational delays, with retrieval keys delivered within one business day and a 98% first-time success rate.
100% GenAI adoption and acceptance, reducing manual intervention in license processing.
19% improvement in delivery velocity, helping teams accelerate licensing turnaround.
15% reduction in defects, improving the reliability of license key delivery.
98% test case maintainability and 100% automation coverage, strengthening release confidence and reducing testing effort.

Beyond the Numbers

The client valued HCLTech for its responsiveness, accountability and consistent ownership throughout the engagement. The team adapted quickly to evolving requirements and remained focused on delivering measurable business outcomes.

The engagement also established the foundation for the next phase of modernization, including:

Reducing dependence on core legacy platforms to improve scalability, agility and maintainability.
Enabling parallel license key generation to reduce processing time.
Lowering turnaround time for change requests and new feature delivery.
Reducing total cost of ownership by minimizing legacy infrastructure and third-party dependencies.