Comparison
Cordum vs Galileo Agent Control
Control plane first vs observability-bolted-on: which architecture fits your AI agent deployment?
Galileo Agent Control launched 2026-03-11 as Apache 2.0 open source, with AWS, CrewAI, and Glean as launch partners. It bolts a control plane onto Galileo's LLM observability heritage. Strongest fit for teams already invested in Galileo for observability.
Cordum is a control plane built as a control plane. The Safety Kernel runs out-of-process behind gRPC + mTLS. The scheduler dispatches across capability-matched worker pools. The audit boundary is separable from the workload — designed to ship signed evidence to your existing SIEM rather than lock it inside a single vendor.
The decision turns on what leads: if observability is the lead, Galileo's integrated experience is real. If governance, audit boundary, and multi-tenant isolation lead, Cordum is built for that as the primary job.
| Evaluation Area | Cordum | Galileo Agent Control |
|---|---|---|
| Origin and shape | Built as a control plane from day one. Safety Kernel, scheduler, workflow engine, and CAP wire protocol form a coherent control plane stack designed for pre-dispatch enforcement and multi-tenant operation. | Built on top of Galileo's observability platform. Agent Control launched 2026-03-11 (Apache 2.0) with AWS, CrewAI, and Glean as launch partners. The control plane sits adjacent to the observability product and inherits its data model. |
| Trust boundary | Out-of-process. Safety Kernel runs as a separate gRPC service behind mTLS. Compromise of the agent does not compromise the policy decision. | In-process control library plus observability backend. Policy is evaluated alongside the agent runtime; the audit trail is in the observability store. |
| Scheduler and orchestration | Built-in scheduler with capability-matched worker pools, stale job detection, pending replayer, Redis-backed job state. Closer to Temporal-with-governance. | Inherits agent runtime from the underlying framework (CrewAI, LangChain, etc.). No native scheduler or worker pool semantics. |
| Wire protocol | CAP v2 protocol with SDKs in Go, Python, Node.js, and C++. Versioned, signed, language-agnostic. | Open-source control libraries; integrations expressed at the framework level rather than via a shared wire protocol. |
| Observability story | Structured run timeline with policy decisions, approval records, and evidence pointers. Designed to be exported to your existing observability stack (Datadog, Grafana, SIEM) rather than to lock data inside one vendor. | Strongest observability surface in the category — that is Galileo's heritage product. If you are already a Galileo observability customer, the integrated experience is a real benefit. |
| Multi-tenancy | Tenant overlays in policy engine: per-tenant deny lists, allow lists, constraint sets. Designed for control plane operators serving multiple isolated tenants. | Single-tenant orientation aligned with Galileo's enterprise observability customers. |
| Compliance evidence | Audit boundary separable from the agent runtime. Policy decisions, approvals, and state transitions are signed and exportable independently of the workload. | Compliance dashboards built on the observability data model. Strong UX for engineering teams already invested in Galileo. |
When to pick which
- Pick Galileo Agent Control if you are already a Galileo observability customer and want a single pane of glass for telemetry plus control.
- Pick Cordum if your buyer is a CISO at a regulated company, you need scheduler-with-worker-pool orchestration, you run multi-tenant agent fleets, or your audit data must ship to your existing SIEM rather than live inside an observability vendor.
- Use both when Galileo provides in-flight observability and Cordum provides out-of-process pre-dispatch policy enforcement.
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Frequently Asked Questions
Is Galileo Agent Control a direct competitor to Cordum?
They share the "agent control plane" label but ship different architectures. Galileo is observability-first with a control library bolted on; Cordum is a control plane first with audit data exportable to whatever observability stack you already run. The choice depends on whether your buyer leads with "I need to see what my agents did" (Galileo) or "I need to constrain what my agents can do, and prove it to an auditor" (Cordum).
When does Galileo's heritage observability become decisive?
When you are already a Galileo customer for LLM observability and the team values a single pane of glass. The data-model continuity is real. If observability is a green-field decision, weigh the lock-in tradeoff: Galileo's control plane is most useful inside Galileo, while Cordum's audit data is designed to ship to your existing SIEM / data lake.
Why does out-of-process matter here?
Trust boundary separation. Regulated buyers' auditors increasingly expect the policy decision to live outside the workload's process. In-process governance — whether Galileo, Microsoft AGT, or APort — can be bypassed if the workload is compromised. Out-of-process governance survives because the policy engine has its own identity, its own logs, and its own failure domain.
Can I use Galileo Agent Control alongside Cordum?
Yes. Galileo Agent Control on the worker side for in-flight observability and framework-level checks; Cordum's Safety Kernel as the out-of-process pre-dispatch policy decision point. The two layers govern different boundaries.
Out-of-process control plane that ships audit to your SIEM
See how Cordum's Safety Kernel runs as a separate gRPC service with audit data designed to leave the vendor.