Enterprises worldwide are set to benefit as Infosys and Intel deepen their AI collaboration, combining compute power with Infosys Topaz to move projects from pilots to production.
Infosys and Intel have announced an expanded collaboration to help enterprises move artificial intelligence (AI) from pilot projects to production at scale. The partnership combines Infosys Topaz Fabric, a multi-layer AI services suite, with Intel’s compute platforms to deliver secure, scalable and cost-efficient AI solutions across industries.
The collaboration will focus on co-innovation in the design, optimisation and benchmarking of AI workloads across Intel® Xeon® processors, Intel® Gaudi® AI accelerators and Intel® AI PCs.
The companies emphasise “right-sized” AI architectures that balance performance, security and total cost of ownership, enabling predictable outcomes for mission-critical use cases such as IT operations, developer productivity and automation workflows.
Infosys Topaz Fabric provides a composable ecosystem that unifies infrastructure, models, data, applications and workflows. When integrated with Intel’s open hardware and software stack, the combined solution aims to advance open standards across the edge-to-cloud spectrum.
It also supports advanced AI agents capable of accessing enterprise data, coordinating tasks and operating with built-in controls, making AI deployments more secure and reliable in complex and regulated environments.
Commenting on the matter, Salil Parekh, Chief Executive Officer of Infosys, said: “We are enabling enterprises to unlock AI value at scale, securely, cost-effectively, and with clear business impact. This aims to help our clients institutionalise AI at the core of their operations and transform their AI journey.”
Lip-Bu Tan, Chief Executive Officer of Intel, added, “Working closely with Infosys allows us to bring the power of Intel’s AI hardware ecosystem to enterprises globally. Together, we are delivering performance-optimised, energy-efficient, and open AI solutions that clients can deploy wherever their workloads reside.”
