Vertex Achieves 100% Defect-Free Releases & 2× Faster Feature Adoption with CloudTestr

Sutherland’s CloudTestr empowered Vertex with 100% test coverage, defect-free releases, a 72% reduction in execution time, and twice the speed in feature adoption.

Industry: Banking and Financial Services | Services: Digital Engineering Services

Client Overview

Vertex, a major global provider of tax compliance solutions with over US$570 million in revenue in 2023, operates internationally across complex systems. Testing customizations and integrations posed a growing challenge due to fragmented processes and reliance on manual testing

The Challenge

Manual Testing Hindered Feature Velocity and Quality

Vertex relied heavily on manual testing across its multi-system processes, resulting in poor test coverage, resource strain, and delays. This not only sapped internal capacity but also jeopardized solution reliability—threatening feature rollouts and user confidence

Sutherland Solution

Cloudtestr Powers Ai-enabled, Continuous Quality Automation

Sutherland performed a proactive impact analysis on upcoming Workday HCM and ERP releases to ensure comprehensive coverage. Then, they implemented CloudTestr, an AI-powered, no-code continuous testing platform delivered via an ‘as-a-service’ model. CloudTestr enables automated release validation, real-time monitoring of performance and security, and built-in audit documentation—combined with Sutherland’s reusable libraries and domain expertise for rapid deployment.

The Outcome

Quality Assured, Feature Velocity Unleashed

Through continuous quality automation, Vertex attained 100% defect-free releases, slashed test execution time by 72%, and validated quarterly patch releases in less than two days. As a result, feature adoption speed effectively doubled, enhancing reliability and user confidence.

KEY OUTCOMES

100%

Defect-free releases through automated validation

2x

Faster new feature adoption rate

72%

Reduction in test execution time and effort

Discover How Continuous Testing Doubles Feature Velocity