In today’s hyperconnected and data-driven world, organizations are at the tipping point of an AI-led technological revolution that brings unprecedented efficiency and innovation to their doorsteps.
Organizations need an AI-ready foundation to leverage these massive technological advancements. They need a future-proof infrastructure solution to test and prove an AI workload and then scale it to production, ensuring alignment between total cost of ownership and return on investment.
The global AI infrastructure market, valued at over $60 billion in 2025, is projected to reach $499 billion by 2034.
Enter AI Factories
Enterprises today have two options: one is to onboard to a cloud-provided AI infrastructure, and the second is to build a private AI stack. Though the former option has a lower investment to start, it poses a challenge to scale a proven use case due to cost and security constraints. And the latter option, to deploy a private AI stack, has become increasingly cost-effective due to advancements in technology and an evolved understanding of how to design and deploy private AI factories.
AI Factories are purpose-built, next-generation environments meticulously designed to engineer intelligence with unprecedented speed and precision. Without them, traditional infrastructure quickly becomes a bottleneck, unable to meet the growing appetite for speed, volume, and reliability required for enterprise AI innovation. These sophisticated hubs manage the entire AI lifecycle, from vast streams of raw data ingestion to the intricacies of model training, fine-tuning and high-volume inference. By seamlessly converting complex enterprise data into actionable insights, AI Factories unlock new pathways for automation, strategic decision-making and breakthrough innovation, redefining what it means to compete in the digital age.
AI Factory implementation
HCLTech recognizes that successful AI Factory deployment extends beyond infrastructure provisioning to encompass comprehensive orchestration of technology, processes and business outcomes. Drawing upon decades of expertise in infrastructure management and cognitive automation, we enable enterprises to navigate the complexities of AI Factory deployment through a structured, outcome-driven methodology.
Central to this approach is our comprehensive AI stack, spanning high-performance computing infrastructure to AI models, data platforms and applications. This full-stack capability positions HCLTech uniquely among global service providers to address the multifaceted challenges of AI Factory implementation, from initial assessment and architecture design through deployment and ongoing optimization.
Strategic collaboration with NVIDIA for AI Factory excellence
HCLTech's strategic collaboration with NVIDIA represents a cornerstone of its AI HYPERLINK "https://www.hcltech.com/ai"F HYPERLINK "https://www.hcltech.com/ai"actory strategy. This partnership combines deep industry expertise with cutting-edge AI infrastructure technologies. It integrates NVIDIA AI Enterprise software, including NIM microservices and advanced AI frameworks, with HCLTech's AI platforms to deliver comprehensive AI Factory solutions.
The collaboration leverages NVIDIA's complete AI Factory stack, from advanced GPUs to high-performance networking solutions like NVLink and InfiniBand, orchestration tools such as Run:ai and Mission Control and comprehensive AI software platforms. This integration enables enterprises to achieve unprecedented AI token throughput, optimize inference workloads and scale AI operations efficiently across distributed environments.
For AI Factories, this translates to enhanced operational resilience, improved energy efficiency per token generated and accelerated innovation cycles. Organizations benefit from validated reference architectures that reduce deployment risk, comprehensive lifecycle management that ensures optimal performance and continuous optimization that maximizes return on AI infrastructure investments.
Comprehensive AI Factory services and capabilities
HCLTech's AI Factory approach explored multiple dimensions of enterprise transformation through its global AI Labs network, spanning London, Noida, Munich, Santa Clara, New Jersey and Singapore. These centers provide AI Factory consulting services, enabling organizations to assess AI readiness, design optimal architectures and progress rapidly from proof-of-concept to production-scale AI Factories.
The company's AI Foundry offering delivers system integration and managed services specifically designed for AI Factory environments. It combines compute infrastructure, AI model optimization and operational management for sustained intelligence manufacturing. This includes specialized capabilities in AI workload orchestration, GPU cluster management and inference optimization essential for efficient AI Factory operations.
Furthermore, HCLTech addresses the evolving needs of AI Factories through its comprehensive service portfolio, encompassing infrastructure assessment, capacity planning, security implementation and performance optimization. Strategic partnerships with cloud hyperscalers and infrastructure providers enable flexible deployment models, from on-prem AI Factories for data sovereignty requirements to hybrid cloud configurations that balance performance with scalability.
Manufacturing intelligence at enterprise scale
As AI Factories become essential infrastructure for competitive advantage, enterprises require partners capable of delivering comprehensive solutions that span the entire AI Factory lifecycle. HCLTech's integrated approach combines proven infrastructure management methodologies, deep AI expertise, and strategic technology partnerships to successfully deploy and operate enterprise-grade AI Factories.
Through its collaboration with NVIDIA and comprehensive ecosystem partnerships, HCLTech empowers organizations to manufacture intelligence at scale, transforming vast data resources into actionable insights that drive business value. For enterprises ready to adopt AI Factory infrastructure, HCLTech provides the strategic partnership, technological excellence and operational expertise necessary to convert AI investments into measurable business outcomes that deliver sustained competitive advantage.
