Enterprises aspire a robust quality engineering strategy to achieve significant milestones enroute their digital transformation. However, uncertainties like shrinking timelines, fragmented automation approach and lack of a unifying test strategy cause delays. Quality engineering with a platform embedded approach shapes an enterprise to maximize agility and improving operational efficiency. With an AI-first approach, Infosys Quality Engineering Platform provides end-to-end testing services and capabilities for digital enterprises and technologies.

Integrated with the platform is cloud quality assurance coupled with data quality engineering and generative AI capability that helps in driving hyperautomation across software testing lifecycle (STLC) phases. With the ability to validate host applications under test including package applications, the Infosys Quality Engineering Platform provides plug and play integration capabilities with Infosys Innovation Network and third-party testing tools. The platform helps in efficient planning, design, and execution to achieve business goals faster and with accuracy.

Looking for an intelligent end-to-end testing solution?


How Infosys Quality Engineering Platform helps enterprises:

  • Enables hyperautomation – Powered by prebuilt frameworks and assets that aid jump start automation across different layers like UI and data
  • Collates cognitive abilities – Brings together cognitive capabilities using digital brain and provides actionable insights to users
  • Provides an ecosystem for support services – Has services for data provisioning and test environment management, making third party tool integration easy
  • Aids end-to-end service delivery – Provision for request creation, demand management, resource allocation, estimation, and results
  • Works on persona-based approach – A platform for different personas: developer, QE engineer, business user, and program manager

Challenges & Solutions

CI/CD engine harnessing the power of hyperautomation, test orchestration, low code QA frameworks and automation accelerators for functional and non-functional testing across cloud transformations, digital transformations, and package implementations

Predictive analytics, generative AI, and machine learning leading to deriving insights from real time project data enabling multi-persona participation in agile testing

One-stop-shop marketplace for tools, workflow-based demand management capabilities from project initiation, demand forecasting, estimations, and tracking. Service-based plug and play integration of testing frameworks and tools across multiple technology stacks

Reporting solution for real-time tracking of performance across quality engineering organization and strategic insight metrics for improved decision making