Evaluate process compliance, DevSecOps, and infrastructure to uncover gaps. We also suggest test architectures, testing strategies, and Target Operating Model (TOM) of a Quality Management Office (QMO). The assessment of your current state is supported with build blocks / road maps that address gaps in your QE organization. We also help you build a roadmap to create a true bi-modal IT approach.

Often organizations use multiple tools for various testing activities, while we can’t say it is incorrect practices, but it poses complicated tracking and cost of maintenance. Our Tools Study and consulting service focus to optimize the tool licensing cost, tools utilization, tools integration and optimial number of tools by consolidating / sunsetting.

Test automation has undergone a significant evolution over the years, continually adapting and repositioning its approach to meet the changing needs of the industry. It began with the simple “record and run” method, where testers would record their actions and replay them to automate tests, the focus shifted to framework-based automation, the next major shift was towards “shift-left” automation, which emphasized integrating testing earlier in the development lifecycle, the industry is increasingly adopting AI tools to accelerate testing. AI-driven test automation leverages machine learning algorithms and advanced analytics to enhance test coverage, improve accuracy, and reduce the time. The adoption of AI in test automation helps reduce dependency on specific talent and tools.