Google Distributed Cloud Offers On-Premises AI Solutions for Data Sovereignty

Addressing Data Sovereignty Challenges

Enterprises and governments with stringent compliance and sovereignty requirements often struggle to adopt the latest AI innovations due to the need to keep sensitive data on-premises. These organizations manage jurisdictional risks from shifting regulations and intellectual property protection, economic independence concerns regarding reliance on foreign infrastructure, and geopolitical risks requiring safeguarding critical local services.

The Rise of Hybrid Cloud for AI

A survey of over 1,400 senior IT leaders revealed that 48% prioritize infrastructure with data residency, controls, and compliance with local data security laws. However, staying entirely on-premises no longer means missing out on innovation. Research indicates that 52% of organizations now use a hybrid cloud approach for AI, balancing the public cloud's power with the sovereignty benefits of local environments.

Introducing Google Distributed Cloud

Google Distributed Cloud (GDC) was introduced to bring Google Cloud services directly into customer data centers or edge locations. This allows organizations to maintain control over data residency and access while utilizing advanced AI. Previously, building in-house AI systems was too slow and costly for those with strict data rules.

Deployment Models and AI Capabilities

GDC offers two deployment models: an air-gapped solution that operates fully disconnected without internet connectivity, and a connected model that provides an integrated, Google-managed software lifecycle on existing hardware. GDC provides a complete on-premises AI solution, including AI-optimized infrastructure, a choice of Gemini or open models, and cost-effective inference services, enabling secure AI agent development with data control.