The control plane for AI agents. Built for enterprise.

Yes. There are full session traces for every agent run. Every LLM call, tool invocation, and decision is logged and inspectable in real-time.

Credentials are centralized at the organization level. OAuth connections, API keys, and service credentials are scoped per-endpoint, resolved at runtime, and never exposed to agent code.

Yes. Usage dashboards attribute token consumption and cost to specific agents, users, and models. You can also set per-agent spend thresholds to prevent costs from surprising you.

If agents are running in your org and you can't answer "who owns this, what can it access, and what happens when it breaks" — this page is for you. Whether you're in platform, security, or engineering leadership, the controls are the same.

Guild provides full audit trails, scoped credentials, session tracing, and immutable logs for every agent action. Everything an auditor needs to answer "what happened and why." We expect to complete our SOC 2 certification soon.

Enterprise AI agent governance is the runtime enforcement of policy, identity, and audit parameters on autonomous systems operating within production environments. It is distinct from standard passive monitoring or traditional human access control. Effective enterprise governance is anchored by four primary infrastructure primitives: a unique, verifiable per-agent identity tied to a human owner (Know Your Agent protocols); scoped credentials that limit agent permissions to specific tools, endpoints, and arguments rather than blanket API keys; short-lived, time-bound access windows that automatically rotate to eliminate long-lived token exposure; and complete, unalterable audit trails that capture every input, model decision, tool call, and output payload.

Traditional DevOps and identity management platforms are architected around deterministic software systems—applications where a specific code input yields a completely predictable, linear execution path. Autonomous agents break this paradigm because their operational logic is non-deterministic, generative, and stateful over prolonged reasoning horizons. Legacy security tools like standard cloud IAM or traditional API gateways can monitor that a login occurred, but they cannot evaluate the security compliance of dynamically generated prompts or catch recursive, token-draining logic loops. A dedicated agent control plane is required to actively sit outside the agent's code execution path, applying real-time policy filters and runtime circuit breakers to regulate non-deterministic behavior before it impacts enterprise data stores.

Guild is engineered to be completely model-agnostic, framework-agnostic, and vendor-agnostic by design. Instead of binding your corporate agent infrastructure to a single cloud ecosystem or a specific LLM provider's proprietary management platform, Guild operates as a neutral mediation layer that sits between your runtime applications and downstream AI models. It natively supports integrations across OpenAI, Anthropic, Google, and any OpenAI-compatible custom open-source endpoint. This architecture allows enterprise engineering teams to switch model providers, route specific tasks to compact efficient models, or adjust regional endpoints instantly through a central dashboard without needing to rewrite a single line of your agents' core application or framework code.