Building Sovereign AI: Controlling Data, Agents, and AI Traffic
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About this webinar
Sovereignty doesn’t stop at the model
You can now run frontier AI entirely inside your own environment, even one that never touches the public internet. This session shows how to keep the agents, tools and model traffic built on it inside that boundary too.
- Run Gemini privatelyGoogle Distributed Cloud brings Gemini on premises, in connected or fully air-gapped mode.
- Govern the agent layerkagent runs agents and MCP tools as managed workloads; agentgateway controls every model, tool and agent call.
- Keep costs in checkMeter every token, set budgets per team or agent, and suspend idle agents with Agent Substrate.
Resources from the webinar
Go deeper
Blog
From Sovereign Models to Sovereign Agents
Solo.io and Google Cloud on running kagent and agentgateway on Google Distributed Cloud.
Read the blog Open source · CNCFkagent
The Kubernetes-native runtime for agents and MCP tools, with declarative deployment and tracing.
Visit kagent.dev Open source · Linux Foundationagentgateway
One point of control for agent-to-model, agent-to-tool (MCP) and agent-to-agent (A2A) traffic.
Visit agentgateway.dev PlatformGoogle Distributed Cloud
Google Cloud and Gemini running on premises, connected or fully air-gapped.
Learn about GDC Open sourceAgent Substrate
Suspends idle agents and restores them on demand, so reserved hardware isn’t wasted.
View on GitHub Blogagentgateway on any infrastructure
Run Solo Enterprise for agentgateway on VMs, bare metal and edge, with no Kubernetes required.
Read the blogBring your agents inside the boundary
Talk to Solo.io about deploying kagent and agentgateway in sovereign, regulated or disconnected environments.
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