VelocityAI: Accelerating the Digital Transformation Journey with GenAI-Enabled Automation

Boosting productivity, collaboration, and efficiency in software development

A global provider of smart/green building solutions needed to accelerate its software development lifecycle (SDLC) while reducing manual effort in coding and quality assurance. GlobalLogic leveraged components of our Velocity-AI SDLC offering – CodeBuddy and qaCompanion – to automate code generation, unit test case creation, code optimization, and QA processes. This AI-driven solution eliminated repetitive tasks, leading to a ~15% increase in productivity and significantly reducing development time. Ensuring more than 80% code coverage, the automation enhanced software quality while empowering developers to focus on high-value innovation.

Challenge

The client needed a more efficient way to streamline software development and testing across multiple technologies. Manual coding, testing, and documentation processes were time-consuming, prone to errors, and delayed project timelines. To overcome these challenges, the company sought an AI-powered solution to automate development tasks, improve accuracy, and free up engineers to focus on critical software enhancements.

Value Created

GlobalLogic implemented CodeBuddy and QaCompanion, two of our VelocityAI-powered SDLC solutions, which:

• Automated repetitive tasks: Eliminated manual effort in code generation, test case creation, and optimization.
• Cut development time: Accelerated software delivery by streamlining coding and testing workflows.
• Enhanced code quality: Enabled early detection of memory and performance issues, reducing defects before deployment.

Integrating AI-driven automation in this way reduced bottlenecks, accelerated feature releases, and empowered our client’s developers to focus on innovation.

Impact

GlobalLogic collaborated closely with the client’s development team to seamlessly integrate AI-driven automation into their workflows. Agile feedback loops and continuous enhancements refined the process, ensuring sustainable efficiency gains. As a result, developers could focus on innovation, while AI-powered tools handled repetitive coding and testing tasks, improving both productivity and software quality.

AI-driven automation boosted productivity, reduced development time, and enhanced software quality, enabling faster innovation in smart building solutions.