Agents

An agent is the core unit of the platform: a deployable AI service that carries out a task using one or more skills, talks to a model provider through the platform's managed gateway, and is reachable over one or more channels. Every agent is deployed into a workspace, and runs under the security policies and guardrails that apply to that workspace and your organization.

Concretely, an agent bundles:

• Skills — the instructions, scripts, and tool dependencies that define what the agent does. Pick a skill from the catalog or generate one by describing it in plain English.
• Model provider and model — chosen per agent at create time from the set your platform offers. Credentials and endpoints are managed by the platform; you never handle model API keys.
• Channels — how the agent is reached: the built-in HTTP endpoint used by the console and by workflows, and optionally Slack.
• Environment variables and secrets — values the skill needs at runtime. Secrets are vaulted at deploy time and are never readable back.
• Policies and guardrails — an egress allowlist per agent, plus the organization and workspace security policies the platform applies automatically.

Agents you create in the console are built into container images and deployed by the platform. You can also deploy pre-built images from your own CI pipeline, or register agents that run entirely outside the platform. Once running, every agent can be tested from the console, observed through its Activity, Logs, and Usage tabs, and composed into workflows.

In this section