Manual & Automated Testing for a Healthcare Document Management Platform

Challenge

At the project’s start, the client faced multiple hurdles that impacted software quality and delivery speed:

• Three development teams working in parallel on different functional areas, requiring coordinated testing efforts;
• Extremely fast development cycles leading to frequent changes and tight deadlines;
• Insufficient internal QA resources to cover all functional areas and keep pace with development;
• Lack of automated testing infrastructure, causing reliance on slow, error-prone manual testing;
• No unified test data management across web and mobile platforms, risking inconsistent test coverage;
• Limited capabilities for testing client-facing notifications, such as email and SMS, which were critical for user communication;
• Absence of CI/CD pipelines integrated with automated test execution and result analysis, slowing feedback loops.

To address these challenges and improve product quality without delaying releases, the client turned to our QA expertise for scalable support and process enhancement.

Solutions

To meet growing quality demands and reduce release bottlenecks, our QA team launched a structured automation strategy early in the project. Initially, the team consisted of three manual testers working in a fast-paced release cycle with expanding functionality. The heavy regression workload, however, made automation a priority.

We began by testing Selenium IDE but quickly switched to Cypress due to its flexibility and scalability. JavaScript became the primary scripting language, and all tests were integrated into CI/CD pipelines via Azure DevOps. This setup allowed us to focus on automating critical business flows while maintaining test reliability.

Over time, our automated test suite grew to over 450 cases running nightly. This significantly reduced manual regression work and improved release stability. The team scaled strategically, and manual testing was phased out for covered scenarios.

We also implemented extensive API testing. This helped us generate reusable test data, validate backend functionality, and speed up test preparation. Cross-platform consistency was ensured across web, mobile, and API layers.

As part of our automation strategy, we incorporated AI-driven tools to support test case generation and maintenance. AI was used to streamline repetitive tasks, suggest coverage improvements based on code changes, and enable test healing for evolving UI components. This helped the team stay agile and reduce maintenance overhead, especially in areas with frequent updates or complex workflows.

Results

Our QA team played a key role in delivering a stable and scalable healthcare platform. The shift to automation enabled us to support rapid development while improving test coverage and speed.

Automated regression testing replaced 700-800 hours of manual work. Nightly runs helped catch critical issues early and kept releases on schedule. Cypress allowed us to automate complex scenarios and uncover defects that manual testing missed.

API testing improved test data management and backend reliability. Synchronizing test logic across platforms ensured full coverage and consistent performance. We also implemented testing for client notifications, including email and SMS.

AI-powered tools supported the automation process by helping generate and maintain test cases. Intelligent analysis identified high-impact areas for testing, while self-healing mechanisms ensured that tests adapted quickly to UI changes. This helped the team reduce maintenance effort and stay ahead of regressions in fast-moving codebases.

700+

hours saved with automation

20%

decrease in QA costs

40%

fewer critical bugs in production

8x

issues uncovered using AQ