HGS Selects Rackspace Technology for Private AI Infrastructure Powered by AMD

Deployment gives HGS greater control over AI compute, while expanding its ability to deliver private and sovereign-ready cloud solutions to enterprise customers

Rackspace Technology, a global enterprise AI infrastructure and solutions provider, today announced that Hinduja Global Solutions (HGS) (listed on BSE & NSE), an intelligent experiences partner, has selected Rackspace to provide the private cloud, AI compute infrastructure, powered by AMD, supporting its strategy to deliver AI-powered intelligent experiences for enterprise customers. The 3-year deployment will begin in December 2026 and will give HGS greater control over AI economics, security and compute while expanding the solutions it can offer enterprise customers in the US and UK. HGS is part of the multi-billion-dollar Hinduja Group, one of the world’s largest diversified business groups. The deal also marks the first announced GSI customer deployment under Rackspace’s multiyear AMD compute agreement.

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As AI reshapes the business process services industry, providers are moving beyond traditional outsourcing models to deliver more technology and AI-enabled services. That evolution requires infrastructure capable of supporting AI alongside existing business-critical workloads, with dedicated compute, operational expertise, deployment flexibility and the performance and control enterprises require.

“AI is forcing a fundamental reset of the business services industry,” said Phil Fersht, CEO and Chief Analyst, HFS Research. “Competitive advantage will increasingly come from providers that can combine deep process expertise with the AI infrastructure, compute and operational capabilities needed to deliver at scale. The HGS and Rackspace relationship is a strong example of how services firms can bring together domain expertise and technology execution to build the foundation for the next generation of AI-enabled services.”

“As HGS expands its AI capabilities, we recognize that production AI requires us to think differently about the infrastructure beneath our applications,” said Venkatesh Korla, Global Chief Executive Officer of HGS. “Working with Rackspace gives us control over the cost, security and performance of our AI infrastructure, and adds private and sovereign-ready cloud capabilities that broaden what we can deliver to customers.”

The multi-year Rackspace and AMD agreement covers an initial 30 MW footprint of dedicated AMD compute across Rackspace’s global data centers from late 2026 through 2028. The agreement established AMD as a strategic technology partner for the silicon layer of Rackspace’s governed enterprise AI stack, expanding the compute options available to customers as their AI requirements evolve. The HGS selection and deployment demonstrate how that investment translates into infrastructure for enterprise AI workloads.

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“AI is pushing enterprises to reconsider where critical workloads run and how much control they retain over their infrastructure, data and economics,” said Gajen Kandiah, Chief Executive Officer of Rackspace Technology. “HGS shows what production AI requires: dedicated compute, private cloud and managed operations working alongside public cloud. We built our governed enterprise AI stack for exactly this, and the AMD agreement gives customers a clear path from capacity to production.”

By adding Rackspace’s private cloud, data center, and AI infrastructure to its technology and managed services capabilities, HGS is expanding its offerings stack for enterprise customers. The infrastructure will help HGS bring secure, real-time customer context into frontline interactions and digital channels, enabling more personalized and responsive experiences at critical moments. It also strengthens HGS’ ability to support organizations looking for greater control over their data, AI environments, and regulatory requirements.

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The deployment reflects continued investment by Rackspace in a governed enterprise AI stack, bringing together dedicated AI compute, private cloud infrastructure and managed operations to support enterprise AI at production scale. The deployment also demonstrates the role private cloud and dedicated AI infrastructure can play as technology and business services providers evolve their operating models for an AI-driven market.