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Agents

An agent is a standing automation. It wakes up on a schedule or when something happens in one of your systems, works through its instructions against live data, and notifies your team through your channels when its notify condition is met.

Where chat answers one question and a report delivers the same structure on a schedule, an agent decides. It looks at the current state of your data, judges it against the rules you wrote in plain language, and acts only when acting is warranted.

Creating an agent

Agents are built in chat. New agent on the Agents page opens a conversation with the agent builder, which drafts the full configuration from your description: trigger, data access, instructions, and notification rules.

A new agent starts as a draft. Drafts never run, never schedule, and do not occupy a plan slot; they exist so you can review the configuration before anything is live. Activate the draft to make it real. An unfinished draft stays on the Agents page with a link back to the conversation it was built in, so you can resume where you left off, or open its page to activate or delete it directly.

Editing works the same way afterwards: refine the agent in conversation, or adjust individual settings on its page.

Triggers

An agent runs when one of its triggers fires:

  • Manual. Run on the agent's page starts a run immediately, useful while testing.
  • Schedule. The same schedule builder as reports: daily, weekdays, specific days, or monthly, at fixed times or intervals, timezone-aware.
  • Events. Notifications from a connected system (filtered by event type, so a reservation change fires the agent but nothing else does), or a signed webhook URL you can call from any external system.

An agent can be paused at any time. A paused agent keeps its configuration and history but ignores its triggers until resumed.

Instructions, data, and tools

  • Instructions are plain language: what to examine, how to judge it, and what to produce. There is no rule syntax to learn.
  • Apps. An agent can only reach the connections you attach to it, and within each app only the access you grant. Attaching nothing means the agent works purely from its instructions and reports.
  • Reports can be attached as data sources. A report gives the agent deterministic, structured numbers to reason over, the same figures your team sees, instead of re-deriving them ad hoc.
  • Workspace. By default each agent has a Python workspace for real computation, and can use document skills to produce Excel, PDF, Word, or PowerPoint output.

Notifications

Choose which channels the agent delivers to and, optionally, a notify condition such as "only if something needs attention". Without a condition, every run notifies. Channels are delivered independently; one failing channel never blocks the others.

Permissions and approvals

Every capability an agent could use is governed by a per-agent policy, visible and editable on the agent's Permissions tab:

  • Auto-run: the agent may use the capability without asking.
  • Needs approval: the run pauses and an approval request appears in the workspace's approvals inbox (and in channels marked for approval requests). Approve to let the run continue; deny or let the request expire to stop it.
  • Out of scope: not covered by the access granted to the agent, so it cannot be used at all.

The Permissions tab also shows the effective permissions: what the agent can actually do once your rules, the app's granted access, and workspace policy are combined.

Runs and history

Every run is recorded step by step: what the agent queried, what it concluded, and what it sent. The agent's History tab and the workspace-wide Activity feed list all runs; opening a run shows the trigger that started it, the full step trace, its duration, and the outcome of each delivery. A running agent can be cancelled mid-run.

A run ends in a clear terminal state: success, failed, cancelled, budget exceeded, or limit reached when a spend limit blocked it before it started.

Budgets and cost

Agents are bounded at two levels:

  • Per run: a step budget and a time budget stop a single run from spiraling.
  • Per month: every agent has its own euro spend cap (10 € by default) on its Usage tab, alongside the workspace-wide limit. One runaway agent stops itself, not the workspace.

Agent runs use AI credit; the builder's work when creating and editing agents is covered by the plan. See Limits & cost controls for how caps behave when reached.