NTT DATA has unveiled a significant initiative focused on providing organisations with NVIDIA-powered platforms designed to establish a repeatable, production-ready model for effectively scaling artificial intelligence (AI) implementations. This comprehensive offering integrates NVIDIA’s advanced GPU-accelerated computing and high-performance networking capabilities with NVIDIA AI Enterprise software, which includes key components such as NeMo and NIM Microservices. The result is a full-stack agentic AI platform engineered for deployment across diverse environments, encompassing both cloud and edge infrastructures.

The architecture of this platform is meticulously crafted to span the entire AI lifecycle, from initial model training to the development of enterprise applications, all within a robust and governed framework. Abhijit Dubey, CEO of NTT DATA, commented on the evolving landscape of AI deployment, stating, “By integrating NVIDIA technologies into our enterprise AI factories, we’re giving clients a powerful and secure environment to adopt agentic AI with measurable returns from the start.” This statement underscores NTT DATA’s commitment to providing tangible value and secure operational environments for AI adoption.

NTT DATA asserts that this enterprise AI factory model directly addresses a critical challenge that has frequently hindered AI programmes: the difficult transition from a successful pilot project to a fully operational production system. The platform is specifically designed to standardise output, thereby significantly reducing both the time and cost typically associated with moving AI initiatives from a proof-of-concept phase to full operational deployment. This systematic approach aims to bridge the gap between initial experimentation and widespread enterprise application.

The practical application of these enterprise AI factories is illustrated through three early-adopter case studies. In the medical sector, a prominent cancer-research hospital is leveraging NVIDIA HGX platforms, in collaboration with NTT DATA and Dell, for advanced radiology analysis and rapid model evaluation, thereby enhancing clinical research workflows. Within automotive manufacturing, a global supplier has achieved a reduction in production setup time by validating workloads on bare metal before scaling them through an AI factory architecture built on NVIDIA infrastructure. Furthermore, in technology manufacturing, a US-based company is utilizing NVIDIA-accelerated simulation and 3D visualization to validate a next-generation battery production line prior to its physical deployment.

NTT DATA is strategically positioning these enterprise AI factories as a domain-specific delivery model. Underpinning this model is the NVIDIA stack, which serves as a common, foundational infrastructure that can be extensively customized sector-by-sector to meet specific industry needs. The technical integration specifically relies on two key NVIDIA components: NVIDIA NeMo, a powerful suite tailored for building agentic AI systems on GPU-accelerated infrastructure, and NVIDIA NIM Microservices, which offer pre-built, GPU-optimized containers equipped with APIs for deploying AI applications. Together, these components form what NTT DATA describes as a full-stack, production-ready AI agent platform. Additionally, NTT DATA provides pre-qualified Generative AI (GenAI) prototypes developed on this stack, aiming to further reduce complexity and accelerate time to value for clients developing sector-specific applications.

John Fanelli, Vice President of Enterprise Software at NVIDIA, reiterated the growing demand from enterprises for robust, scalable platforms capable of transitioning AI initiatives from pilot stages to full-scale production. He noted that NTT DATA’s AI factory offerings deliver the domain-specific solutions necessary for achieving production-grade enterprise AI. This initiative also highlights NTT DATA’s unique position as the only global IT services provider active across all three of NVIDIA’s partner tracks: Solution Provider, Cloud Partner, and Global System Integrator Partner Network. This recent announcement comes at a time when enterprises are facing increasing pressure to demonstrate clear financial returns on their AI investments, with governance and domain-specific performance becoming critical criteria for evaluating such investments. The AI factory model represents a concerted effort to systematize these crucial aspects.