Armada and Nscale Collaborate to Enhance Global AI Infrastructure for Enterprises

Armada and Nscale Join Forces to Advance Sovereign AI



In a significant step towards transforming AI infrastructure, Armada and Nscale have formalized their collaboration by signing a letter of intent (LOI). This agreement aims to deliver both large-scale and edge AI capabilities tailored for public sector and enterprise clients worldwide.

Nscale, headquartered in Europe, stands at the forefront of AI infrastructure development. The company is responsible for deploying some of the largest supercomputing clusters globally, boasting a comprehensive platform that encompasses power supply, data centers, computing resources, and essential software. Meanwhile, Armada, based in San Francisco, specializes in providing real-time distributed intelligence via its innovative modular data centers, referred to as Galleons, and its proprietary Armada Edge Platform (AEP).

This strategic partnership will enable both companies to offer sophisticated edge AI technologies across various global sites. By leveraging available land and power at these locations, they plan to provide solutions that feature modular data center infrastructure, GPU computing capabilities, application software, and dedicated customer support for users in both the private and public spheres.

The collaboration between Nscale and Armada promises to combine rapidly deployable turnkey infrastructure with extensive sovereign cloud deployments. This integration allows customers to establish secure, compliant AI infrastructures even in areas lacking existing facilities, significantly faster than the traditional data center construction process.

One of the most compelling aspects of this initiative is the implementation of a hub-and-spoke model. While Nscale's large-scale data centers provide a robust economic foundation and significant capacity, Armada's deployments, such as its Leviathan megawatt Galleon, will extend sovereign capabilities to edge locations, facilitating a widespread reach in new geographical territories.

Josh Payne, CEO and Founder of Nscale, emphasized the growing demand for operational AI from both enterprises and governments. He stated that fulfilling these demands requires infrastructure that is scalable, distributed, and ultimately sovereign. By partnering with Armada, they aim to present clients with a flexible infrastructure ideal for deploying advanced AI workloads wherever necessary, without sacrificing performance or security.

Dan Wright, Co-Founder and CEO of Armada, echoed these sentiments, highlighting that the accelerated adoption of AI calls for infrastructure that can extend beyond centralized clusters on Earth and beyond. He noted that one of Armada's distinguishing features is its ability to facilitate sovereign AI deployment promptly and at scale. Collaborating with Nscale will further enable them to penetrate new global markets, thus supporting clients who require high-performance computing solutions in sovereign environments.

Together, Armada and Nscale aspire to establish a replicable model for global AI infrastructure deployment. By merging vast sovereign cloud services, modular computing, and distributed operations, they will empower organizations to hasten their AI adoption while maintaining stringent standards for security, compliance, and scalability.

About Armada


Armada is recognized as a pioneering full-stack edge infrastructure firm that supplies computing, storage, connectivity, and AI/ML facilities to some of the most remote and challenging industrial settings on the planet. It supports various sectors, from energy to defense, enabling organizations to operate at the very edge of technology without compromise.

About Nscale


Nscale is dedicated to constructing a worldwide hyperscale AI infrastructure. With its innovative, vertically integrated AI solutions and modular data center designs across Europe and North America, Nscale provides the essential computational foundation needed for enterprise-level AI training, fine-tuning, and inference at scale.

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