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The Job queue (Foundry → Jobs in the dashboard) is the live view of every job for your organization, across every service. Each row is one unit of work — training an object, preparing a video, transcribing it, extracting its steps — and the queue shows where it is in its lifecycle.
Foundry is available to select customers only, and the Job queue is visible to organization admins and managers. Contact us to request access.

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Job types

Every row carries the service it belongs to. Object training and procedure extraction are requested by a person; the rest are enqueued automatically as an upload or a capture moves through the pipeline. Where each of these runs, and what leaves your infrastructure, is in Services and data residency.

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Job lifecycle

Every job carries a status. As a runner picks up the work, the status advances: A job that was claimed but stopped reporting progress — a runner losing power mid-training, say — is automatically requeued so another runner can pick it up.

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What each job shows

Selecting a job opens its detail panel, which includes:
  • The object or capture being processed, with its thumbnail
  • Live progress and the runner currently handling it, while in progress
  • Where the data went: the provider that did the work and whether anything left your infrastructure
  • For object training, the view mode, training mode, and any objects to avoid

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Training parameters

These apply to object training only. They’re chosen when tracking is enabled on an object and describe how the object is handled in the real world, which helps produce an accurate reference object: View mode Training mode See Tracking settings for full guidance on choosing these.

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Managing a job

From the queue you can stop and requeue a job that’s in progress, handing it back for another runner to claim. That’s the “my Mac is wedged, give me my job back” case, and it’s the one mutation your team needs day to day. The runner honors it on its next check-in and hands the job back cleanly rather than dropping it mid-write. To retry a failed job, or dismiss one that’s no longer wanted, ask us. Training jobs are long-running, so that part of the queue is designed to be checked in on rather than watched. The capture services are quick by comparison — a transcript is usually minutes, its steps seconds — so those rows tend to be finished by the time you look. The Foundry app on the Mac can post a notification when its jobs finish.