Coforge Limited has announced an expanded focus on helping Hi-Tech enterprises move beyond AI experimentation and individual use cases towards organisation-wide AI adoption.
The company is combining its next-generation AI operating system with Forward Deployed Engineers to help enterprises translate AI investments into measurable business results across engineering, operations and business decision-making.
For software companies, semiconductor businesses, electronics manufacturers and other Hi-Tech organisations, AI-powered features are increasingly becoming an expected part of the market. Competitive advantage is now shifting towards faster engineering, greater operational efficiency and the ability to make informed decisions quickly across complex product and business environments.
While many Hi-Tech companies are using AI to improve individual functions, connecting intelligence across engineering, product management, customer support, operations and enterprise workflows remains a challenge.
As organisations face increasing pressure to speed up product development, lower engineering costs, enhance customer experience and respond more quickly to market changes, Coforge is focusing on AI-led engineering, enterprise context, intelligent automation and autonomous execution.
Rajan Khattar, Executive Vice President and Global Head of the Hi-Tech Industry Vertical at Coforge, said, “The next phase of AI transformation will be defined by business outcomes, not AI features. 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 brings together Coforge Nuuron, a composable enterprise AI operating layer that connects business context, institutional knowledge, workflows and decision intelligence, with Momentuum blue, a specialised operating model that places small teams of Forward Deployed Engineers and AI agents within client environments.
Together, these capabilities are designed to help enterprises apply AI across critical business functions and move from pilot programmes to production-scale adoption. The approach aims to support faster product development, stronger operational performance, more informed decision-making and clearer pathways to growth.
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