Sovereign AI control is becoming a business continuity issue as autonomous agents take on essential enterprise workflows. Keeping data within national boundaries addresses part of the challenge, but organizations also need control over agent behavior, external dependencies and the economics of keeping those systems operational.
Regulated enterprises need more than access to powerful models and computing infrastructure. They need software and expertise that turn those capabilities into governed production workflows, according to Mick McNeil (pictured), founder and chief executive officer of Deliverance AI Ltd.
“It’s our view that the value and the criticality in terms of business continuity does not sit with the model choice. It sits with the layer that governs the models,” he said.
McNeil spoke with theCUBE Research’s Dave Vellante for the “Sovereign AI: From Strategy to Reality” video series, during an exclusive interview on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how enterprises can govern AI agents within their own environments, preserve model choice and link sovereignty requirements to measurable business outcomes. (* Disclosure below.)
Sovereign AI control starts with the operating boundary
Deliverance’s control plane observes agent activity, enforces policies and provides audit trails and a kill switch. Those safeguards help protect sensitive data and maintain operational control as agents execute enterprise workflows, McNeil explained.
“We partner with HPE; deploy a full-stack capability that’s storage, network, GPUs and all software; and go directly into the customer data center,” he said. “Only then, whenever they own the boundary around the agentic system, can they truly say that they have full control over the actions and the telemetry going in and out of that system.”
The requirements vary across government, defense, pharmaceutical and financial services organizations. Some customers need air-gapped deployments, while others accept selected external connections; those choices depend on their operating context and the risks they are prepared to take, McNeil noted.
“Our customers are the ones who own the keys to their infrastructure, plus the software on top of it,” he said. “That’s unquestionable and very explicit in how we go to market.”
Model options support workflow resilience
A customer-controlled environment still needs a strategy for dependencies outside its boundary. Deliverance’s routing technology supports frontier and open-source models, letting enterprises choose capabilities for individual workflows while planning alternatives if provider access changes, according to McNeil.
“When you purchase our products as a subscription — our operating system, the control plane — you buy the ability to deploy any model, frontier and open source,” he said. “Those mission-critical workflows have the ability to fall back to an open-source model if the frontier model gets restricted or to a different open-source model if your primary model is open source.”
Sovereign AI control also raises questions about what customers retain when a supplier relationship ends. Customers retain ownership of their agents, integrations, audit trails and accumulated learning, although transferring those assets between platforms remains a separate challenge, McNeil explained.
“Agents are becoming portable,” he said. “The market has not yet created the framework that enables all agentic organizations to port agents between different platforms, but we are leading in that thought leadership.”
Economics and expertise turn control into outcomes
Model routing also supports cost management by matching AI model capabilities and expenses to specific workloads. Deliverance assesses where agents can improve business performance, distinguishing productivity gains from measurable financial outcomes, according to McNeil.
“We deploy agents and AI at scale to defer future costs. That’s a very clear and impactful outcome on your [profit and loss],” he said.
Deliverance joined HPE’s Unleash AI partner program to bring its agentic operating system to HPE Private Cloud AI, co-developed with Nvidia Corp. Embedded engineers maintain the platform and build workflows, while strategic value advisors help customers prioritize opportunities based on return on investment, time to value and risk, McNeil explained.
“We’re about to launch a joint solution, which is HPE’s sovereign agentic knowledge engagement, that enables customers — within 90 days — to click and deploy a full-stack agentic operating system into their own environment in the most sovereign way,” he said. “For me, [enabling] enterprises to move quickly in a way that they trust the technology, trust the workflows [and] trust the agents is the key to growth and prosperity of enterprises around the world.”
Here’s the full video interview, part of SiliconANGLE’s and theCUBE’s coverage of the “Sovereign AI: From Strategy to Reality” video series:
(* Disclosure: TheCUBE is a paid media partner for the “Sovereign AI: From Strategy to Reality” interview series. Neither HPE, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)