70% Faster Modernization: How a U.S. Digital Health Leader Transformed Legacy SQL Systems into Cloud-Native APIs with Mastek
This case study details how a U.S.-based digital health company, in partnership with Mastek, leveraged advanced Digital Engineering to modernize hundreds of complex SQL stored procedures into scalable .NET Core Web APIs deployed on Azure Kubernetes Service – delivering 70% faster modernization, improved quality, and a future-ready cloud architecture
About the Company
A U.S.-based digital health innovator, this company operates a virtual-first care platform that integrates primary care, behavioral health, diagnostics, and genomics. Its flagship Digital Medical Home™ solution empowers employers, payers, and providers to deliver personalized, proactive healthcare experiences. The company is actively redefining connected healthcare through technology innovation and deep integration across the care continuum.
Challenge
The company’s core business logic was deeply embedded within hundreds of SQL stored procedures – built over years without documentation or dependency mapping. This monolithic design made it increasingly difficult to scale, modify, or integrate with modern cloud and API-based platforms.
Key challenges included:
- Business logic locked inside complex SQL procedures with no visibility into dependencies or data flows
- Every change to business rules required direct database intervention, raising release risk and slowing delivery cycles
- The architecture was incompatible with the scalability, reuse, and API-based integrations required for a modern virtual care platform
- Lack of standardized documentation and inconsistent testing practices made quality validation slow and unreliable
To achieve the agility and cloud readiness demanded by a growing virtual health platform, the company needed a comprehensive Digital Engineering strategy to modernize its entire business logic layer – without disrupting ongoing operations.
Solution
Mastek charted a comprehensive AI-led modernization roadmap, translating legacy database logic into a clean, cloud-native API architecture deployed on Azure Kubernetes Service (AKS). Rather than a manual rewrite, Mastek embedded AI across every phase of the modernization lifecycle.
AI-Powered Reverse Engineering Mastek utilized AI Powered Reverse Engineering through GitHub Copilot and LLM-based analyzers to extract, translate, and document logic from stored procedures – turning opaque SQL into well-understood, portable business rules ready for re-implementation
Web API Development Business logic was rebuilt as modular .NET Core Web APIs with AI-assisted endpoint generation and input/output validation. The new APIs are independently deployable, reusable across channels, and fully decoupled from the legacy database layer.
Automated Documentation OpenAPI (Swagger) specifications and developer documentation were generated using Copilot Chat and Postman AI, ensuring every API is self-describing and ready for third-party integration from day one.
AI-Assisted Testing Unit and integration tests were created with TestGPT, code quality was enforced via SonarQube AI Insights, and automated reviews were integrated into the Azure DevOps pipeline – building quality in at every stage rather than inspecting it at the end.
The result is a scalable, maintainable platform that supports analytics integration, rapid feature releases, and continuous improvement through automated documentation and monitoring.
Impact
The partnership between this digital health company and Mastek delivered a step-change in modernization speed, architecture quality, and operational resilience.
70% Faster modernization through AI-assisted logic extraction and code generation
Scalable Architecture: Maintainable, cloud-native platform fully decoupled from legacy databases – enabling independent deployments and API-first integrations
Higher Quality: AI-driven testing, continuous code reviews, and automated pipelines significantly improved reliability and reduced defect escape rates
Future-Ready: Platform now supports analytics, AI feature integration, and rapid release cycles – positioning the company for continued digital health innovation
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