AI-Powered QA Helps Scale a 20-Brand CMS Migration
20 brands migrated from Drupal/WordPress to ArcXP without rollback
Weekly automated regression supporting ongoing releases
Zero release issues achieved through continuous regression automation, AI-assisted failure analysis, and targeted manual validation
Engagement snapshot
The challenge
The customer was undertaking a migration from its legacy content management system to ArcXP across 20 brands, while also managing regular feature enhancements and business-as-usual releases.
Before Everest's involvement, QA was predominantly manual, with limited processes, visibility, and communication. QA visibility was lacking, and communication gaps created additional challenges during the migration.
The migration project was at risk of stalling as the internal team was increasingly occupied with migration-related work.
The turning point came when Everest Technologies joined the initiative in late 2024 to support the build and rollout, giving the internal team the capacity to remain focused on enabling the business rather than being consumed by migration activities.
What Everest delivered
Everest initially supported the migration to ArcXP, followed by ongoing QA support for day-to-day feature enhancements, rollouts, and business-as-usual activities.
The engagement evolved into an AI-enabled Quality Engineering practice, integrating Claude across test planning, automation, code quality, regression execution, failure analysis, and automation maintenance.
Solution components
- AI-assisted test planning
- Jira ticket analysis
- Test plan generation
- Test plan review and coverage validation
- Test automation
- Automation framework creation
- Regression test automation
- Automation script development
- Automation script fixes
- AI-assisted engineering
- Code refactoring
- Pull request reviews
- Reusable QA rules and instructions
- CLAUDE.md maintenance
- Claude skills creation and maintenance
- Regression & failure analysis
- Regular automated regression execution
- Regression failure analysis
- Fix recommendations
- Automation reports
- GitHub in-progress run analysis
- Run management
- Run scheduling
- Run abortion and control
Approach
Everest followed a phased rollout approach, with multiple brands rolled out in each quarter.
Alongside the migration, the team supported weekly releases for day-to-day enhancements and business-as-usual activities.
The approach combined AI-assisted QA activities, automated regression, and targeted manual validation to support ongoing release quality.
Quantified impact
Impact & outcomes
- 20 brands migrated to ArcXP without any rollback
- Weekly automated regression executed to provide consistent coverage before releases
- Zero release issues achieved through the combination of continuous regression automation, AI-assisted failure analysis, and targeted manual validation
- 10+ AI-enabled QA activities integrated across the QA lifecycle
- Faster identification and resolution of automation failures
- Continuous improvement of the automation framework
- Greater QA ownership across automation and engineering activities
- Stronger release confidence
Post go-live impact
The engagement continued beyond the initial migration.
Everest continues to support regular releases, future rollouts, improvements, and business-as-usual QA activities.
The initiative has enabled the continued adoption of AI in day-to-day QA activities while expanding the role of QA engineers beyond functional testing into automation, engineering, analysis, and continuous improvement.
Business impact
- Enabled the internal team to remain focused on enabling the business rather than being consumed by migration activities
- Supported the migration of all 20 brands without rollback
- Established regular automated regression for weekly releases
- Enabled QA engineers to contribute beyond functional testing into automation and engineering activities
- Supported ongoing releases, rollouts, improvements, and business-as-usual activities
- Created a foundation for continued AI-enabled QA adoption
Tools & platforms
- ArcXP
- Claude
- Pelcro
- GitHub
- Jira
- Other QA and engineering tools
Team composition
- 6 QA resources
Client perspective
The foundation is now in place, and what we build on it from here is the part that matters. The turning point was bringing on Everest Technologies in late 2024 to help with the build and rollout. The work didn't get easier, but their involvement gave us the capacity to keep our own team focused on enabling the business instead of being bogged down in migration work. It's a big part of why the rest of the roadmap didn't stall while this got finished.
Frequently asked questions
Quick answers about this engagement, drawn from the case content above.
The customer was undertaking a migration from its legacy content management system to ArcXP across 20 brands, while also managing regular feature enhancements and business-as-usual releases.
Everest initially supported the migration to ArcXP, followed by ongoing QA support for day-to-day feature enhancements, rollouts, and business-as-usual activities. The engagement evolved into an AI-enabled Quality Engineering practice, integrating Claude across test planning, automation, code quality, regression execution, failure analysis, and automation maintenance.
20 brands migrated to ArcXP without any rollback. Weekly automated regression executed to provide consistent coverage before releases. Zero release issues achieved through the combination of continuous regression automation, AI-assisted failure analysis, and targeted manual validation. 10+ AI-enabled QA activities integrated across the QA lifecycle. Faster identification and resolution of automation failures. Continuous improvement of the automation framework.
Key tools and platforms included ArcXP; Claude; Pelcro; GitHub; Jira; Other QA and engineering tools.
Enabled the internal team to remain focused on enabling the business rather than being consumed by migration activities. Supported the migration of all 20 brands without rollback. Established regular automated regression for weekly releases. Enabled QA engineers to contribute beyond functional testing into automation and engineering activities. Supported ongoing releases, rollouts, improvements, and business-as-usual activities.
This case study comes from the Business News & Information industry, delivered through Everest Technologies' Quality Engineering practice.
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