Microsoft Agent 365 vs Sovereign AI Control Planes

TL;DR: Microsoft Agent 365 is strongest for inventory, identity, and data protection across a Microsoft-centered estate. For non-Microsoft agents, its reach depends on registry sync, the Agent 365 SDK, or Entra Agent ID, and enforcement is limited to where an agent touches Microsoft services or a configured gateway. A sovereign AI control plane enforces and records agent actions inside your own boundary, wherever the agents run. Most regulated enterprises weighing Microsoft Agent 365 alternatives end up using both.

Microsoft Agent 365 and a sovereign AI control plane answer different questions. Agent 365 is built to give IT one place to see, govern, and secure the agents in a Microsoft-centered environment. A sovereign AI control plane is built to enforce policy on what agents do, wherever they run, and to keep the enforcement and the evidence inside your boundary. For regulated enterprises with agents on other platforms, the useful question when weighing Microsoft Agent 365 alternatives is not which one is better. It is which questions each can actually answer for non-Microsoft agents.

This is a decision guide for regulated enterprise AI teams weighing Microsoft Agent 365 alternatives for their enterprise AI agents. It covers what Agent 365 does well, what changes for agents outside Microsoft, what a sovereign control plane is and where its limits sit, how the main Microsoft Agent 365 competitors and other AI agent platforms fit, and what to insist on for agent interoperability.

One disclosure: Prediction Guard publishes this blog and builds a sovereign AI control plane. Every statement about Agent 365 comes from Microsoft's documentation as it stood in mid-October 2026, and every statement about Prediction Guard's limits comes from its own published guidance.

What Microsoft Agent 365 Does Well

A fair comparison starts with the strengths, and Agent 365 has real ones. Microsoft's overview describes it as the ability to observe, govern, and secure the agents in an organization, and in practice that means:

• One registry. Administrators see agents in a single inventory in the Microsoft 365 admin center, with adoption, activity, and health.
• Identity for agents. Each agent gets an identity in Microsoft Entra, and Conditional Access can evaluate its access the way it evaluates a person's.
• Data and threat protection. Microsoft Purview adds data loss prevention, auditing, and eDiscovery for agent activity, and Microsoft Defender adds threat detection.
• Reach beyond Microsoft. Registry sync connects Amazon Bedrock, Google Vertex AI, Salesforce Agentforce, Databricks Genie, Anthropic Claude Managed Agents, Oracle Generative AI Agents, and Snowflake Cortex, and an SDK extends agents built on other stacks.
• Simple licensing logic. Microsoft's licensing FAQ says Agent 365 is licensed per user, not per agent, and offered both as a standalone add-on and as part of Microsoft 365 E7, which Microsoft's license overview lists as including it. Packaging and prerequisites change, so confirm them with Microsoft before pricing a comparison.

For an organization whose agents live mostly in Microsoft 365, Foundry, and Copilot Studio, that integration with identity, data protection, and the admin center is a genuine advantage, and a standalone control plane does not replicate it.

What Changes for Non-Microsoft Agents

How far Agent 365 reaches depends on which of three paths a non-Microsoft agent takes, and the paths differ in what they can do:

Microsoft's connected platforms documentation, updated in October 2026, is candid about the limits of registry sync: synchronization is manual, removal of an agent from the source platform is not guaranteed to reconcile in the registry, and observability coverage varies, with Oracle and Snowflake marked "coming soon." Collecting observability data from connected platforms is part of Microsoft's Frontier preview program. Three further details matter for regulated teams:

• Credentials. Microsoft's documentation states that every currently supported platform requires a key-based credential, such as an API key, secret, or private key, which Agent 365 stores as encrypted connection data within Microsoft 365, and that keyless options such as workload identity federation or role assumption are not currently supported for connected platforms. The Bedrock, Vertex AI, and Salesforce setup steps involve access keys, secret keys, or consumer keys. A security review will want to weigh that, and to recheck it, since authentication options can change.
• Evidence. Microsoft's documentation on observability data handling says Agent 365 stores observability data in the tenant's default geography for 30 days, after which it is automatically deleted. That describes the observability service's own data. It does not say how long audit records in Purview are kept, which follow Purview's retention settings, or whether the observability data can be exported before deletion, which is a question to put to Microsoft. The same page says Agent 365 does not currently support Advanced Data Residency and is not yet classified as a Core Online Service under Microsoft's product terms, though it runs on services that are and Microsoft says it is working toward that classification.
• Tool enforcement. For MCP servers registered in Azure API Management, Agent 365 can block or unblock a server on the v2 and AI Gateway tiers and block individual tools on the AI Gateway tier, which Microsoft documents as preview. Enforcement runs in the gateway, tool-level control needs a static list of allowed tools, and Microsoft notes that Agent 365 does not automatically route agents through a customer-hosted gateway. The agent has to be configured to use the gateway's MCP endpoint, and direct access has to be restricted separately.

None of this makes Agent 365 the wrong choice. For agents outside Microsoft, its reach is strongest in inventory, identity, and visibility. Enforcement is available where an agent touches Entra, Purview, Defender, or a configured API Management gateway, deeper controls come through SDK integration, and everything else depends on the source platform.

What a Sovereign AI Control Plane Is, and What It Is Not

A sovereign AI control plane places runtime enforcement and audit-evidence generation inside your boundary, on infrastructure you choose. The word "sovereign" describes where enforcement and evidence live, not who built the agents. Implementations differ in their supported protocols, identity models, policy controls, and deployment options, so buyers should evaluate those capabilities individually. The category sits on one side of a distinction drawn in gateway versus control plane: routing traffic is one thing, and making and recording policy decisions is another.

Prediction Guard is one implementation of that model. Its published description covers a Kubernetes-based deployment that runs on-premises, hybrid, air-gapped, or in your cloud, with an MCP tool proxy that uses delegated, per-user OAuth with no shared service credentials. Its Admin Console is where access, token limits, tool scope, and model kill switches are set, and its agent operations capabilities stream decisions, tied to an agent identity, to the SIEM a team already uses.

The limits are worth stating just as plainly. According to Prediction Guard's own guidance:

• It enforces on traffic that routes through it. Communication between agents that never crosses the model boundary is not observable by the control plane, as its agent sandboxing guide says, while agent-to-agent calls that are routed through it are logged centrally, as its guide to composable AI architectures notes.
• Access controls govern which agents, users, and applications may call which MCP servers or models, but per-invocation authorization at the tool server is not yet generally available, and dedicated controls for multi-agent privilege escalation are planned.
• Token-based usage limits apply per API key today, and human approval gates for high-risk tool executions are on the roadmap, as its blast radius guide states.

A sovereign control plane is also not an identity provider or a workflow system, and you run it, which means infrastructure and operations work that a hosted service takes off your hands.

Side by Side: Six Questions That Decide It

Both products move quickly, so treat the cells as documented behavior as of mid-October 2026 and confirm against current documentation.

Microsoft Agent 365 Alternatives and Competitors: Four Kinds of AI Agent Platforms

Microsoft Agent 365 competitors and alternatives fall into four groups, and most regulated estates end up using more than one. This is positioning, not a feature audit, so check each vendor's current documentation and put the evaluation question for the group to each one.

These groups overlap and combine. An Agent 365 deployment for Microsoft data, a cloud platform for the agents built there, and a sovereign control plane for cross-platform enforcement is a coherent stack, not a contradiction.

Choose by Situation: Where Your Enterprise AI Agents Run

Choose Agent 365 when most of your enterprise AI agents run in Microsoft 365, Foundry, or Copilot Studio, Entra, Purview, and Defender are already your security backbone, a central inventory with visibility into agents elsewhere meets your need, and its evidence and retention model, including the 30-day observability window, meets your requirements or you have confirmed how to retain what you need.

Choose a sovereign AI control plane when you need enforcement and not just visibility on non-Microsoft agents, evidence must be generated and kept inside your boundary under your own retention rules, your agents call models and tools across clouds or on-premises, and your team can run the infrastructure.

Run both when some agents work on Microsoft 365 data and others need policy enforcement and evidence on model and tool traffic. Use Agent 365 for inventory, identity, and Microsoft data protection, use the control plane for enforcement and evidence, and join the two with shared agent identifiers.

Agent Interoperability: What to Insist On

Agent interoperability runs in two directions, and vendors usually answer only one. The first is ingestion: can the platform see and list agents from other systems? The second is portability: can your policy and your evidence travel with the agent wherever it runs? A registry answers the first, and enforcement and exportable records answer the second. Open standards help with both. Microsoft's own multi-agent guidance recommends MCP for tool and data access and the Linux Foundation's A2A protocol for cross-platform agent messaging, and OpenTelemetry's Gen AI conventions, still in Development status, give telemetry a common shape. Standards only help if the control point can see the traffic they describe, so it is worth knowing which protocols and which paths a vendor's enforcement actually covers. Six questions are worth putting to any vendor, Microsoft and Prediction Guard included:

1. Can it enforce on agents it does not host, or only list them?
2. Which credentials must you hand over, and where are they stored?
3. Where is evidence generated and retained, for how long, and can you export it in a structured form?
4. Which capabilities are in preview, and what does preview mean in your contract?
5. What happens to enforcement if the vendor's service is unreachable?
6. How does it treat agent-to-agent traffic that does not pass through it?

For a fuller evaluation approach, see this decision framework. For what a defensible record looks like, whichever product generates it, see this guide to audit log implementation.

The Decision Comes Down to Three Things

For regulated enterprises, the decision comes down to three things: where agents run, where enforcement must happen, which is the core of operational control of agents, and where audit evidence must remain. Agent 365 can be the right foundation for a Microsoft-centered estate. A sovereign control plane can address enforcement requirements across other environments. Where both sets of needs exist, the two approaches can complement each other.

Frequently Asked Questions About Microsoft Agent 365 Alternatives

1. What are the main Microsoft Agent 365 alternatives?

They fall into four groups: cloud-native AI agent platforms such as Amazon Bedrock AgentCore and Google Gemini Enterprise Agent Platform, identity and workflow layers such as Okta for AI Agents and ServiceNow AI Control Tower, assessment and risk platforms such as Credo AI and IBM watsonx.governance, and sovereign control planes such as Prediction Guard and other self-hosted options. Most regulated estates use more than one.

2. Does Microsoft Agent 365 work with non-Microsoft agents?

Yes, through three paths. Registry sync provides read-only inventory for agents on supported platforms, the Agent 365 SDK adds identity and observability for agents you build on any stack, and Entra Agent ID for third-party agents adds identity and Conditional Access. Enforcement beyond that depends on the source platform or on a configured API Management gateway.

3. When does a regulated enterprise need a sovereign AI control plane instead of Agent 365?

When enforcement and audit evidence must stay inside a defined boundary, when agents run across several platforms, or when the controls have to apply to model and tool traffic rather than only to inventory and identity. A sovereign AI control plane places runtime enforcement and evidence generation on infrastructure you choose.

4. Can you run Agent 365 and a sovereign AI control plane together?

Yes. A common pattern uses Agent 365 for inventory, identity, and Microsoft data protection, uses the control plane for enforcement and evidence on model and tool traffic, and joins the two with shared agent identifiers.

5. What should you ask any vendor about agent interoperability?

Ask whether it can enforce on agents it does not host or only list them, which credentials you must hand over and where they are stored, where evidence is generated and retained and whether you can export it, which capabilities are in preview, what happens to enforcement if the service is unreachable, and how it treats agent-to-agent traffic that does not pass through it.