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Cognizant said the platform is part of its wider “AI Builder” strategy, which focuses on enabling enterprises to deploy AI applications
In sum – what to know:
Enterprise AI platform – Cognizant AI Factory unifies the full AI lifecycle across hybrid and multi-cloud environments, targeting the shift from pilots to production-scale AI.
Fractional GPU model – The platform uses Nvidia MIG-based GPU partitioning to improve utilization, cut costs by up to 60% and support concurrent workloads.
Infra-led partnerships – Built on Dell and Nvidia stacks, the offering combines infrastructure, software, and managed services into a single enterprise AI environment.
Cognizant has introduced a new multi-tenant platform, Cognizant AI Factory, aimed at helping enterprises move from pilot AI projects to full-scale deployment, as demand grows for infrastructure that can support production-grade AI workloads across hybrid and multi-cloud environments.
The firm noted that the new platform is built on infrastructure from Dell Technologies and Nvidia, combining compute, networking, and software into a single environment designed to manage the full AI lifecycle—from development and testing to deployment and operations.
The launch reflects a broader shift among enterprises seeking to operationalize AI while addressing constraints around cost, scalability and governance. “Enterprises everywhere are racing to operationalize AI, but too often run into barriers around scale, cost and governance,” said Sriram Kumaresan, global head of cloud and infrastructure services at Cognizant.
Cognizant also explained that the system supports deployment across private, public, and hybrid cloud setups, allowing organizations to control where workloads run and how they scale.
According to Cognizant, the platform includes pre-configured environments for testing, as well as pre-built pipelines intended to accelerate development and deployment timelines.
A central component of the platform is Cognizant’s fractional GPU technology, built on Nvidia’s Multi-Instance GPU (MIG) architecture. This approach allows multiple workloads to run on a single GPU by dividing it into isolated instances.
The model is intended to improve utilization rates and reduce infrastructure costs, particularly in enterprise environments where GPU demand is uneven across teams or workloads, the company said.
Cognizant said internal testing suggests the platform could reduce total cost of ownership by 50–60% and improve processing performance by up to 30%, while shortening deployment timelines from months to weeks.
The platform runs on Dell’s AI infrastructure stack, including PowerEdge servers, PowerSwitch networking, and PowerScale storage, combined with Nvidia’s AI software ecosystem.
The offering is structured as a managed service, with Cognizant providing orchestration, governance, and operational support across the AI lifecycle.
Cognizant said the platform is part of its wider “AI Builder” strategy, which focuses on enabling enterprises to deploy AI applications, including intelligent agents, while modernizing legacy systems.
The company is also applying similar approaches internally, using AI to refine its own operational processes before deploying them to clients.
