Why hybrid deployment models are crucial for modern secure AI agent architectures – Source: securityboulevard.com

As enterprises embrace AI agents to automate decisions and actions across business workflows, a new architectural requirement is emerging — one that legacy IAM systems (even SaaS IAM!) were never built to handle.

The reality is simple: AI agents don’t live in just one place.

They operate across clouds, on-premises infrastructure, edge devices, and sometimes entirely disconnected environments. In this new landscape, hybrid deployment isn’t a deployment option — it’s an operational imperative for security, resilience, and compliance.

What hybrid identity means today

The term “hybrid” has evolved beyond just “on-prem + cloud.” In the agentic era, a hybrid architecture means:

• Public cloud platforms (e.g., Azure, AWS, Google Cloud)
• Private clouds and on-premises infrastructure
• Air-gapped or disconnected environments (DDIL, tactical edge)
• Multiple identity providers (IDPs) in use across different domains
• Cross-agent platform compatibility — AI agents running on frameworks like ChatGPT, LangChain, Azure Agent Foundry, N8N, and CrewAI

Identity for AI agents must be as distributed and dynamic as the agents themselves.

Why some things will always stay on-premises

Even as cloud adoption accelerates, there are mission-critical workloads and datasets that cannot — and will not — leave the premises. Why?

• Regulatory constraints (e.g., financial services, defense, healthcare)
• Data residency and sovereignty (especially in GDPR- and HIPAA-covered regions)
• Latency-sensitive systems (manufacturing lines, trading engines, logistics systems)
• Operational control and uptime SLAs for critical systems

In these environments, agents must run locally — often within secured infrastructure where the enterprise has full control over identity systems, policy enforcement, and data access.

This is where air-gapped architectures become essential.

The role of air-gapped architectures in agent security

An air-gapped deployment can be described as a disconnected, often classified, environment where no inbound or outbound API communication is allowed. These environments are critical for:

• Defense and national security systems
• Critical infrastructure (e.g., financial infrastructure, utilities, emergency response)
• Remote deployments (e.g., ships, satellites, border outposts)

AI agents running in these zones must operate independently, with no dependence on cloud-hosted IDPs, policy engines, or data providers. This introduces a new challenge: how do you give AI agents identity, access, and authorization in a disconnected runtime?

Maverics solves this with an air-gap-capable orchestration platform:

• Identity and access policies are packaged and deployed locally
• OAuth tokens are minted on-prem, bound to specific agents and scopes

All activity is logged locally, with optional export to secure SIEMs post-mission.

Hybrid agent workflows: real-world scenarios

Let’s take a look at some exciting use cases and scenarios using agents in distributed hybrid agent architectures can work in practice.

1. Global bank – on-prem core + cloud assistants

A multinational bank uses AI agents to help with customer queries and internal automation. However, core banking services — including balance transactions and fund movements — must run inside a private data center due to regulatory and latency constraints.

In this setup:

• Agents running in Azure handle intent classification and UI.
• On-prem agents handle secure operations, with identity orchestration providing identity continuity across environments.
• OAuth delegation and audit logs ensure traceability and zero-trust enforcement across the hybrid boundary.

2. Manufacturer – geo-constrained agent identity

A global manufacturer operates agent systems across plants in Europe, North America, and Asia. Due to data localization laws, human identities must remain in-region, and agent access must align with regional policy.

The company deploys:

• A global Identity Fabric with regional policy instances
• Distributed agent fabric that registers and tracks agent identities per region
• Local Maverics orchestrators that enforce policy and mint tokens at runtime

The result: agent-based automation that complies with regional governance, while maintaining enterprise-wide visibility and control.

3. Coast guard – tactical AI in air-gapped environments

A national coast guard deploys agents onboard ships that need the ability to operate disconnected from satellite or internet coverage — classic DDIL (Denied, Disrupted, Intermittent, Limited) environments.

They run:

• Maverics orchestrators on-ship, deployed in a cluster on a container with preloaded identity policies
• A local identity provider tied to the ship’s mission crew
• Agents that perform mission-critical tasks (navigation, resource planning, threat detection) under strict access control

The identity system runs entirely on board, with no cloud dependency, while maintaining full traceability for post-mission forensics.

Why this matters

We’re at a turning point.

AI agents will soon outnumber human users by 80:1 in enterprise systems. But without the ability to:

• Authenticate agents securely across environments,
• Assign policy over agents dynamically at runtime,
• Audit their behavior consistently,

—we will lose control of what’s happening at the edge of our networks and clouds.

Hybrid Identity Orchestration for agents is the only way to manage the complexity, scale, and sensitivity of these new workloads. That’s why Strata built Maverics Identity Layer for Agentic / Artificial Identities — to deliver the identity layer that works anywhere your agents run.