Coforge announced an expanded focus on helping Hi-Tech enterprises move beyond AI experimentation and isolated use cases to operationalize AI across engineering, operations, and business decision-making. By combining a next-generation AI operating system with Forward Deployed Engineers (FDEs), Coforge helps convert AI investments into measurable business outcomes.

For software companies, semiconductor firms, electronics manufacturers, and other Hi-Tech enterprises, AI powered features have become the price of entry for the marketplace. The new competitive differentiators are engineering velocity, operational efficiency, and the ability to make faster, more informed decisions across increasingly complex product and business environments. Industry-wide, Hi-Tech organizations are leveraging AI to improve individual functions, but many enterprises struggle to connect intelligence across engineering, product management, support, operations, and enterprise workflows at scale.

As Hi-Tech companies face growing pressure to accelerate product development, reduce engineering costs, improve customer experience, and respond quickly to market shifts, Coforge is helping build those capabilities through AI-led engineering, enterprise context, intelligent automation, and autonomous execution.

“The next phase of AI transformation will be defined by business outcomes, not AI features,” said Rajan Khattar, Executive Vice President and Global Head of the Hi-Tech industry vertical at Coforge. “Technology companies already understand how to build AI. The challenge now is operationalizing it across engineering, operations, and customer-facing functions in ways that improve productivity, accelerate innovation, and create sustainable competitive advantage.'

Coforge's approach combines Coforge Nuuron, a composable enterprise AI operating layer that connects business context, institutional knowledge, workflows, and decision intelligence, with Momentuum blue, a specialized operating model that embeds small teams of Forward Deployed Engineers and AI agents within client environments.

Together, these capabilities help enterprises operationalize AI across critical business functions and accelerate the transition from pilot programs to production-scale adoption. The result is faster product development cycles, improved operational performance, more informed decision-making, and accelerated paths to growth.