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The Assets page gives you a unified view of all AI assets in your workspace, organized across four tabs: Agents, Tools, Deployments, and Models. The summary cards at the top vary per tab, while the table columns and controls are shared across all tabs.
Control Tower Assets view showing Agents tab with total cost $0.59, 140 runs, 8 active agents, and a list of agents with cost, run count, and error metrics.

Control Tower Assets

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Asset Tabs

Use the tabs at the top to switch between asset types:
  • Agents: AI agents built or connected in your workspace
  • Tools: Tools available to your agents
  • Deployments: Deployed configurations of your agents
  • Models: LLM models in use across your assets

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Summary Cards

Each tab displays four summary cards at the top. All cards include a sparkline overlaying the current period against the last period.
  • Total Cost: Total spend for all agents in the selected period
  • Total Runs: Total number of agent invocations
  • Active Agents: Number of active agents out of the total (e.g. 0 / 7)
  • Top used Agents: Ranked list of the most-invoked agents, with cost and request count

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Asset Table

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Columns

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Status Icons

Each asset name is prefixed with a status icon indicating its activity level:

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Trust Levels

Each asset can be assigned a trust level to communicate its production readiness to your team. To set it, click anywhere on an asset row to open the detail panel, then use the Trust level dropdown.

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Tags

Tags are set manually per asset via the Asset Detail Panel. They are also visible in the Overview table and can be used for filtering. Click anywhere on an asset row to open the detail panel. In the Details tab, scroll to the Tags section. Click Add tag to add a new tag, or click × on an existing tag to remove it.
Animated walkthrough of adding a tag to an asset in Control Tower.

Adding a tag to an asset from the detail panel

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Department

A dedicated department dropdown is available at the top of the Asset Detail Panel. Click anywhere on an asset row to open it, then select a department directly from the dropdown.

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Table Controls

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Column Selector

Click Columns to show or hide specific columns. This lets you focus on the metrics most relevant to your workflow.

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Sorting

Click Sort to sort the table by any column, ascending or descending.

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Filters

Click Filters to narrow the asset list. You can filter by tags, department, status, and other attributes.

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Asset Detail Panel

Click any asset row to open its detail panel. It contains two tabs:
  • Details: Shows source, status, model, owner, creation date, last activity, tags, and department. Tags and department can be edited directly from this panel.
  • Overview: Shows performance metrics for the selected asset

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Asset Capture via Third-Party Framework

Assets in Control Tower can be populated automatically when you instrument your code with OpenTelemetry and send traces to Orq.ai. Each trace carries information about which agents, tools, and models were invoked. Orq.ai extracts these and registers them as assets without any manual configuration. Orq.ai currently supports asset capture from OpenAI Agents, LangGraph, and Vercel AI SDK traces. See the framework documentation for setup instructions and examples:

OpenAI Agents

Instrument OpenAI Agents with OpenAIAgentsInstrumentor and send traces to Orq.ai for automatic asset registration.

LangGraph

Instrument LangGraph agents with setup() from orq_ai_sdk.langchain to capture traces and automatically register assets in Control Tower.

Vercel AI SDK

Use experimental_telemetry with the Vercel AI SDK to capture agents, tools, and models in Control Tower.