Reimagining Quality Engineering at Scale with Testing-as-a-Service

As a global financial advisory leader, the client manages multiple mission-critical platforms supporting advisory services, policy management, and customer engagement. Ensuring consistent quality across these systems was crucial for maintaining regulatory compliance, operational reliability, and customer trust across geographies.

• Heavy dependence on individual testers and contractors with no unified governance model
• Limited automation and CI/CD adoption across platforms
• Gaps in reporting, risk management, and tooling standardization
• Misaligned stakeholder priorities and lack of QE governance awareness
• Rising QE costs and slower time-to-market for critical projects

We implemented a Software Testing Governance Assurance Framework (STGAF) to establish standard practices, enforce governance, and embed automation-driven efficiencies across all enterprise testing operations.

Key solution components:

• Governance model with defined templates, roles, and compliance reviews
• End-to-end test coverage across functional, integration, security, API, and performance layers
• Standardized tooling using open-source frameworks and in-house accelerators
• Scalable TaaS delivery model with flexible resourcing and burst capacity (+25% for critical cycles)
• Integration of CI/CD pipelines for automated health checks and regression testing
• Centralized repository for test artifacts and documentation, reducing silos and promoting reusability
• Training and enablement programs to upskill internal test engineers
   

• TMMi-based maturity assessment to benchmark existing QE practices
• Phased STGAF rollout – from assessment to policy definition, process standardization, pilot, and continuous improvement
• Embedded RACI-based governance and risk-based prioritization for automation and performance testing
• Continuous reporting and dashboards for monthly, half-yearly, and annual quality tracking
• Parallel chatbot testing stream to validate enterprise-grade AI solutions within a governed framework
   

• AI-Driven Automation Enablement: Conducted GenAI automation pilots and tool evaluations for Microsoft Dynamics 365 and other enterprise environments, improving scalability and cost efficiency.
• Conversational AI Policy Assistant: Built a Copilot Studio–powered Teams assistant integrated with the Policy Master Knowledge Base to deliver accurate, context-aware responses for up to 100 concurrent users.
   

• 30% month-on-month resource cost savings since TaaS implementation
• 25% quarterly improvement in testing output and efficiency
• Expanded automation coverage across regression cycles, reducing manual effort and release cycles
• Reduced defect leakage and higher execution rates across platforms
• Improved QE governance maturity with a clear roadmap toward TMMi advancement
• Reusable, scalable QE framework embedded into enterprise delivery value chain
• AI-ready QE ecosystem supporting safe and governed adoption of conversational AI solutions