Overview

A global professional services organization with thousands of developers building client-facing solutions struggled to realize consistent productivity gains from AI-assisted development. Inconsistent prompting techniques, fragmented workflows, and the absence of governance were limiting ROI and creating quality risks.More

A global professional services organization with thousands of developers building client-facing solutions struggled to realize consistent productivity gains from AI-assisted development. Inconsistent prompting techniques, fragmented workflows, and the absence of governance were limiting ROI and creating quality risks. Tech Mahindra partnered with the firm to implement an AI-powered SDLC accelerator that combines generative AI tools, workflow automation, and human-in-the-loop validation within a governed framework. The solution standardized AI-assisted development, improved development throughput by 10–12%, and accelerated software delivery while maintaining quality and compliance standards.

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Industry Challenge

This global professional services firm is one of the world's largest and most respected organizations, providing audit, tax, consulting, and advisory services to clients across every major industry. Behind its client-facing expertise lies a massive software engineering organization with thousands of developers supporting hundreds of internal and client-facing applications. As the firm accelerated its adoption of AI-powered development tools, it quickly discovered that unstructured usage was creating new challenges, inconsistent quality, governance gaps, and limited automation, that threatened to undermine the very productivity gains it sought.

Business and Community Impact

  • Improved development throughput by 10–12%
  • Accelerated software delivery timelines
  • Reduced manual effort through end-to-end SDLC automation
  • Increased developer productivity across lifecycle activities
  • Enabled faster issue resolution through automated debugging
  • Supported self-healing builds with automated retry mechanisms
  • Improved visibility through measurable SDLC productivity metrics
  • Reduced manual intervention across development workflows

Our Approach and Solution

Tech Mahindra's solution leveraged multiple AI models and code-assistance technologies to support engineering tasks across the entire lifecycle, from planning through deployment. A no-code, skill-based framework standardized AI-assisted development practices, enabling developers across teams and experience levels to use AI more consistently.

Custom enterprise workflows with human-in-the-loop validation ensured that AI-generated outputs met quality, security, and governance requirements before progressing through the delivery pipeline. This governed approach helped the firm scale AI-assisted development, streamline workflows, and improve development throughput while maintaining compliance.