AI Analysis Runs
AI agents can export data, run code against it in an isolated workspace, and produce findings plus downloadable files. The run page records what happened and the files produced.
What the workspace can and cannot do
Section titled “What the workspace can and cannot do”The workspace is a per-run virtual machine that is destroyed when the run ends.
| It can | It cannot |
|---|---|
| Read the data the run staged into it | Reach the internet, your devices, or the Breeze API — it has no network at all |
| Run Python, Node and shell scripts the model writes | Hold any credential, token or key |
| Write files you can download | Change anything on a machine, or survive the run |
Anything the analysis wants done comes back as a proposal. Proposals are text: turning one into a real action is the same approval you already use, with the same tier gate and the same audit record. The sandbox is not a way around approvals — it cannot reach a device even if it tried.
Configured agent access
Section titled “Configured agent access”An agent’s site, device-group, and device-tag restrictions apply to manual runs as well as automatic triggers. Partner and organization filters combine by intersection; non-overlapping filters permit no access. Scope is checked again when a queued run starts and before each tool call.
Agents with these restrictions currently require a single device target. Organization-wide runs are refused until their evidence and tools support the same restrictions. Scoped runs expose device lookup, device context, and device metric analysis tools; broader tools are refused until their scope handling is verified. Moving the device to another site during a run also stops further scoped tool calls.
Reading the run
Section titled “Reading the run”The run page is the audit surface. Besides the usual trigger and status, an analysis run shows:
- Files this run produced — name, kind, size, a text preview when supported, and a download. Files always download as attachments; Breeze never renders them.
- What ran in the workspace — every step in order, with the language, the exit code, how long it took, and links to the exact script and its output. This is how you check a finding rather than take it on faith.
- Compute — the sandbox’s own cost, tracked separately from the run’s model/token cost.
Files are kept for 30 days and then deleted. A ticket or report you attached one to keeps the record; once a file expires, it shows as expired rather than as a broken link.
Attaching a file to a ticket
Section titled “Attaching a file to a ticket”Open the run, find the file, and choose Attach to a ticket. Breeze links the file to the ticket as an attachment and adds an internal comment — by reference, not by copy, so nothing is duplicated. The success message appears after both steps complete. Because it’s a reference, the attachment expires along with the underlying file (see “Reading the run” above).
A report run can attach the same file the same way, also by reference.
Turning it on
Section titled “Turning it on”-
Your operator enables the feature for the deployment.
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An administrator turns on Allow sandboxed AI analysis for each organization that wants it, under Settings → Organization → Security.
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The organization’s AI policy must include the workspace capability. Until it does, runs are refused with a message saying so.
Each organization has its own daily compute budget and per-run limits, enforced before a run starts — an analysis that would exceed them is refused rather than truncated halfway.