HCLTech, a leading Indian IT company, announced on Thursday a collaboration with Red Hat to establish enterprise-ready AI infrastructure designed to assist organizations in deploying and scaling artificial intelligence within their operational frameworks.
This partnership is set to enhance HCLTech’s AI Factory ecosystem—a platform that brings together multiple technology partners to provide comprehensive AI infrastructure solutions for enterprise clients. This initiative comes as businesses globally are increasing their investments in AI while facing challenges related to scaling systems, managing expenses, and navigating complex deployments.
According to industry experts, enterprise AI is swiftly advancing beyond pilot initiatives and generative AI trials, moving towards integration with essential business functions. This evolution is fueling the demand for strong infrastructure capable of accommodating AI workloads across on-premise systems, cloud environments, and edge locations.
As part of the collaboration, the HCLTech AI Factory, in conjunction with Red Hat, will utilize Red Hat AI Enterprise to create a cohesive platform for deploying and managing AI applications throughout hybrid ecosystems. The solution aims to optimize infrastructure use, boost model efficiency, and lower inference costs through features such as model optimization, distributed computing, and centralized operations.
The companies noted that the platform will also incorporate a governed data layer featuring data lineage tracking and operational controls—functions that are increasingly critical as organizations seek improved oversight, compliance, and reliability in AI systems.
This partnership underscores a broader trend in the tech industry, where cloud services, infrastructure providers, and software firms are shifting toward the development of integrated AI stacks rather than isolated tools. As organizations broaden AI applications across customer interactions, software development, and internal operations, the need for production-ready infrastructure continues to rise.
“Organizations are progressing beyond trials to operationalize AI within their core functions,” stated Rampal Singh, highlighting that the HCLTech AI Factory with Red Hat is intended to assist enterprises in industrializing AI while translating investments into tangible business results.
Ryan King mentioned that this initiative would enable companies to deploy and manage AI workloads uniformly—from centralized data centers to edge sites—enhancing the value derived from AI-driven transformation strategies.
This collaboration aligns with HCLTech’s broader strategy to enhance its AI- and cloud-led services. The company has been expanding its partnerships and platform-driven offerings as clients increasingly seek ready-to-deploy solutions. HCLTech, which employs over 227,000 individuals worldwide and reported $14.7 billion in revenue for the fiscal year ending March 2026, views AI and hybrid cloud as major growth catalysts.
As competition intensifies for enterprise AI investments, analysts anticipate that collaborations among infrastructure providers, cloud platforms, and software vendors will significantly influence the development of scalable AI ecosystems.
In recent months, HCLTech has been actively expanding its AI partnerships. In March, it enhanced its collaboration with Google Cloud to accelerate the adoption of agentic AI, including developing AI agents based on Gemini models and structured strategies to scale implementations across sectors.
The company also expanded its strategic partnership with CrowdStrike to offer AI-driven Continuous Threat Exposure Management services, aimed at enhancing cybersecurity and risk visibility.
Beyond AI infrastructure, HCLTech has broadened its collaborations across various sectors. It recently teamed up with DP World Tour to improve digital fan experiences and expanded its relationship with MetLife Stadium as the Official AI Partner for the venue and its associated sports teams.
The partnership with Red Hat further solidifies HCLTech’s strategy of developing integrated AI ecosystems, as enterprises increasingly seek all-in-one solutions to transition AI from experimentation to large-scale application.
