Vultr, the world’s largest privately-held cloud computing platform, today announced the launch of Vultr Sovereign Cloud and Private Cloud in response to the increased importance of data sovereignty and the growing volumes of enterprise data being generated, stored and processed in even more locations — from the public cloud to edge networks and IoT devices, to generative AI. The announcement comes on the heels of the launch of Vultr Cloud Inference, which provides global AI model deployment and AI inference capabilities leveraging Vultr’s cloud-native infrastructure spanning six continents and 32 cloud data centre locations. With Vultr, governments and enterprises worldwide can ensure all AI training data is bound by local data sovereignty, data residency, and privacy regulations.
A significant portion of the world’s cloud workloads are currently managed by a small number of cloud service providers in concentrated geographies, raising concerns particularly in Europe, the Middle East, Latin America, and Asia about digital sovereignty and control over data within their countries. Enterprises meanwhile must adhere to a growing number of regulations governing where data can be collected, stored, and used while retaining access to native GPU, cloud, and AI capabilities to compete on the global stage. Fifty per cent of European CXOs list data sovereignty as a top issue when selecting cloud vendors, with more than a third looking to move 25-75% of data, workloads, or assets to a sovereign cloud, according to Accenture.
Vultr Sovereign Cloud and Private Cloud are designed to empower governments, research institutions, and enterprises to access essential cloud-native infrastructure while ensuring that critical data, technology, and operations remain within national borders and comply with local regulations. At the same time, Vultr provides these customers with access to the advanced GPU, cloud, and AI technology powering today’s leading AI innovators. This enables the development of sovereign AI factories and AI innovations that are fully compliant, without sacrificing reach or scalability. By working with local telecommunications providers, such as Singtel, and other partners and governments around the world, Vultr is able to build and deploy clouds managed locally in any region.
Vultr Sovereign Cloud and Private Cloud guarantee data is stored locally, ensuring it is used strictly for its intended purposes and not transferred outside national borders or other in-country parameters without explicit authorisation. Vultr also delivers technological independence through physical infrastructure, featuring air-gapped deployments and a dedicated control plane that is under the customer’s direct control, completely untethered from the central control plane governing resources across Vultr’s global data centres. This provides complete isolation of data and processing power from global cloud resources. To further ensure local governance and administration of these resources, Vultr Sovereign Cloud and Private Cloud are managed exclusively by nationals of the host country, resulting in an audit trail that complies with the highest standards of national security and operational integrity.
For enterprises, Vultr combines Sovereign and Private Cloud services with “train anywhere, scale everywhere” infrastructure, including Vultr Container Registry, which enables models to be trained in one location but shared across multiple geographies, allowing customers to scale AI models on their own terms.
“To address the growing need for countries to control their own data, and to reduce their reliance on a small number of large global tech companies, Vultr will now deploy sovereign clouds on demand for national governments around the world,” said J.J. Kardwell, CEO of Vultr’s parent company, Constant. “We are actively working with government bodies, local telecommunications companies, and other in-country partners to provide Vultr Sovereign Cloud and Private Cloud solutions globally, paving the way for customers to deliver fully compliant AI innovation at scale.”
