Nutanix has purchased Ryax Technologies to strengthen its GPU utilization and agentic AI return on investment capabilities for enterprise customers, according to an announcement from the company. The acquisition aims to allow businesses to build, operate and oversee agentic AI across any infrastructure by incorporating Ryax's advanced GPU utilization and smart scheduling technology into Nutanix's platforms. Financial details of the deal weren't disclosed.
The Ryax platform will be integrated into upcoming versions of Nutanix Kubernetes Platform and Nutanix Enterprise AI, providing two core architectural features: intelligent resource optimization and AI-aware smart scheduling. The intelligent resource optimization capability lets customers maximize their use of available computing resources like GPUs and CPUs to boost performance and cut waste. The AI-aware smart scheduling feature automatically positions AI workloads on cost-effective hardware to help optimize both performance and budget. Ryax, founded in 2017 and based in France, operates as an AI-driven compute orchestration and management platform provider. The Ryax Technologies team will remain in France and continue advancing the technology under Nutanix's ownership.
Nutanix Chief AI Officer Debo Dutta told CRN that once the integration wraps up, the company will roll out these sophisticated GPU utilization and smart scheduling capabilities that channel partners can deliver to shared customers. According to Dutta, the features will enable Nutanix and its partners to provide greater value by broadening the range of use cases supported throughout the Nutanix portfolio. Nutanix CEO Rajiv Ramaswami said in a statement that the Ryax acquisition "helps to directly answer the challenges enterprises face today with agentic AI infrastructure management." Ryax Technologies CEO Andry Razafinjatovo noted that his company's platform was designed to provide enterprises with seamless execution across hybrid infrastructure, managing back-end complexity so teams can deploy, scale and handle AI workflows from the first day.
Dutta explained that GPU scarcity and fragmented infrastructure have pushed many companies to distribute their compute footprint across private data centers, hyperscalers and neoclouds to locate available capacity. Agentic AI demands flexible architecture, straightforward operations and the ability to use infrastructure far more efficiently, he said. By merging Ryax with Nutanix's hybrid cloud platform, the company intends to help enterprises handle back-end complexity and smoothly deploy, scale and manage AI workflows regardless of where their infrastructure resides. Dutta also noted that enterprises frequently struggle to transition AI projects from experimentation into production because of the substantial infrastructure integration and manual configuration needed. The Ryax platform addresses these obstacles by automating the underlying infrastructure, data, hardware and code to help customers roll out AI projects more quickly, economically and reliably. Together, these capabilities are designed to help customers advance AI initiatives by improving infrastructure efficiency, managing costs, and making better use of available hardware.
The acquisition arrives as demand for smart scheduling and GPU optimization grows, with Ryax's capabilities positioned to expand Nutanix's portfolio and strengthen its competitive position, according to Dutta. Supporting agentic AI workloads while maximizing utilization of existing infrastructure is creating new opportunities for both Nutanix and its channel partners, he added. The deal marks a milestone in Nutanix's commitment to simplifying enterprise AI at scale, Ramaswami said. By combining Ryax's technology and team with Nutanix's hybrid cloud platform, the companies aim to further enable organizations to accelerate their agentic AI initiatives seamlessly, wherever their infrastructure exists. The integration underscores how infrastructure vendors are racing to solve the dual challenge of GPU scarcity and agentic AI complexity, betting that orchestration and efficiency gains may matter as much as raw compute power in determining which platforms win enterprise AI budgets.