An AI agent control plane is the governance layer that manages agent identity, permissions, and execution. It sits between foundational models and enterprise systems to ensure every automated action is authorized, mediated, and validated.
The Control Plane for AI Agents Is Now Open
We’re opening Guild to everyone today.
AI agents are already in production. They review code, triage issues, update systems, and automate workflows across the enterprise. As adoption accelerates, the problem changes. It is no longer whether agents are useful. It is whether you can control them once they start executing actions in your systems.
Most teams can’t.
Agents are built across different frameworks, connected to different tools, and deployed without a consistent governance model. There’s no reliable way to see what they’re doing, control what they can access, or reuse what already works. What starts as helpful automation quickly becomes difficult to manage at scale.
At this point, it becomes an infrastructure problem.
A New Layer in the Stack
Now, for the first time, there is a control plane for AI agents. As agents move into production, this layer sits between models and enterprise systems, governing how autonomous software runs.
Guild is that layer. It’s what’s been missing - and this is a significant development for managing the complete agent lifecycle.
With Guild, agents do not operate directly on your systems. Every execution runs through Guild, where identity is enforced, access is controlled, and every action is recorded and traceable. This is what makes agents safe to run in production.
Guild defines the control plane for AI agents.
Guild includes a governed runtime for executing agents, ready-to-run starter agents, a Managed Agent Center for internal reuse, and an Agent Hub for sharing capabilities across teams and organizations.
What Control Requires
Running agents in production requires:
- A defined identity for every agent
- Centralized control over what systems each agent can access
- Visibility into what actually happened, not just outputs
- The ability to update and roll back safely
- A way to reuse what already works
Guild provides these capabilities in one place.
From Single-Player to Multiplayer
Most agents today are one-off tools built for a single workflow. That model doesn’t scale.
Production systems are multiplayer. They depend on shared infrastructure, governance, and reuse.
Guild turns agents into shared systems. Teams can publish, version, and reuse agents through the Managed Agent Center. Agent Hub extends that beyond the organization, making capabilities discoverable and reusable across environments.
What works in one place can work everywhere.
That’s how capabilities become shared infrastructure.
What You Get in the Open Beta
The Open Beta includes the Guild control plane, starter agents, Agent Hub, integrations, and developer tools for building or bringing your own agents.
You can start with agents like:
- Ticket Processing: triages Jira and GitHub issues and routes them to the right owner
- Code Review: reviews pull requests and posts feedback
- Slack Bot: turns Slack conversations into structured work
- Tech Support: answers questions using internal documentation
These agents are versioned and governed by default. You can deploy them, fork them, adapt them, or bring your own agents and run them through the same control plane.
Guild integrates with systems teams already use, GitHub, Bitbucket, Azure DevOps, Jira, Linear, Slack, Notion, Zendesk, TestRail, New Relic, Google Compute, Google Docs, and Google Logging. Agents can securely access these services through OAuth, with permissions enforced at the control plane level. All access is mediated through the control plane, so permissions are enforced consistently, and API keys are not exposed.
If a system isn’t supported out of the box, you can extend Guild by registering custom APIs as tools or building agents with the SDK and CLI.
How Teams Use Guild in Production
Deploying an autonomous agent into production is easy; managing it at scale is where infrastructure breaks down. When agents transition from isolated scripts to critical production infrastructure, visibility and control become paramount. Here is how modern engineering and operations teams use Guild's control plane layer to solve real-world governance challenges.
Use Case: Operations Teams Running Ticket Triage Without Visibility
- The Scenario: An IT operations team deploys a Ticket Triage agent to parse, categorize, and route thousands of incoming Jira issues across three primary corporate development projects.
- The Governance Problem: Operating without a control plane layer leaves the team blind to the agent’s autonomous choices. There is no reliable mechanism to audit why a ticket was misclassified, no trace of edge cases where the model failed, and no way to guarantee data boundaries. If the agent accidentally accesses a restricted project, there is no infrastructure-level gate to block it.
- How Guild Solves It: Guild introduces rigorous agent access control and runtime observability. Every triage decision is recorded in Guild's session logs, capturing the input context, model calls, and routing output in real time. Permissions are clamped at the control plane: the agent is restricted to the explicit projects it has been credentialed to access through workspace-scoped permissions.
- The Outcome: The operations team gains a complete, forensic audit trail. When expanding operations to a fourth project, credentials are safely granted at the Guild infrastructure level rather than embedded inside the application code, preventing privilege escalation and ensuring safe, predictable scaling.
Built for a Multi-Model World
Models will change. The control layer can’t.
Guild works across models, vendors, and frameworks. Teams can use OpenAI, Anthropic, Google, or other providers without changing how governance is applied. Every call flows through the control plane, giving teams visibility and control as the underlying intelligence evolves.
Governance Is the System
Security is built into the system.
With Guild, agents run in controlled environments. Credentials are scoped and mediated. Organizations are isolated. Every action is recorded with full context, so teams can monitor behavior, usage, and cost in real time. This is the baseline for running agents in production.
The Ultimate Infrastructure Solution
AI adoption is already happening. What’s missing is the infrastructure to manage it. With Guild, this layer now exists.
Guild is the control plane that brings structure, visibility, and governance to how agents are built, deployed, shared, and used.
If you’re building agents, you’re going to run into this problem. You can start using Guild today at guild.ai. Let us know what you think.
Frequently Asked Questions
Without a control plane, autonomous agents present severe security and scalability challenges. Ungoverned agents create security risks by directly exposing system credentials, lacking centralized access boundaries, and creating fragmented, unauditable tools that cannot scale safely.
Agent governance operates through three mechanisms: verifying unique agent identity, enforcing access control via secure OAuth connections to third-party tools, and maintaining a real-time audit trail of every prompt, tool call, and system interaction.
Agent frameworks are the development layer used to build, prompt, and define an agent's logic. Control planes are the infrastructure layer that wraps around those frameworks to centrally manage live deployment, security compliance, and activity tracking across an organization.
Monitoring is achieved through centralized logging, tracing, and observability features. The control plane tracks every agent execution and forwards performance, cost, and usage metrics directly into platforms like New Relic or Google Logging.
Monitoring is achieved through centralized logging, tracing, and observability features. The control plane tracks every agent execution and forwards performance, cost, and usage metrics directly into platforms like New Relic or Google Logging.
Security features include credential management, where agents use mediated OAuth connections rather than direct API keys, and workspace isolation, which confines agent sessions to prevent horizontal security breaches.
Control planes provide vendor neutrality by decoupling the governance layer from the AI models. Organizations can switch or deploy multiple underlying LLMs without modifying the established security, identity, or compliance rules.
One control plane.
The complete agent lifecycle.
The complete agent lifecycle.
Get a working agent in under 10 minutes.
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