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All plans Start with one CT or MRI workflow and one Dataset Version your team can use. The workflow in this guide runs on Team and Enterprise, from a workspace and agent token through annotation and review to a Dataset Version. A Community deployment cannot run it today. It has no supported way to issue an agent token: tokens are created in the hosted app on Team and Enterprise, and its stack does not include the Nitsor dashboard. Its run plane is off and it runs no data-plane Workers, so it cannot build or read a Dataset Version. Compare the plans to choose who will run Nitsor and how your team signs in.

Describe one workflow

Describe the recurring task and the release or quality decision it feeds. Identify where people need to reconstruct an annotation, a review or the version used for training. Write down the following before setting up the project. You can describe each item without disclosing scan data, credentials or storage locations.

Keep the first project small

On Team and Enterprise, register one series from your bucket, bind a two-stage pipeline, have one annotator and one reviewer work it, create one Dataset Version and read it through the HTTP API. The Python reader is not on PyPI. Dataset Version downloads from a self-serve customer connection need a signer that Nitsor sets up with you. A mask workflow also needs write access. Community cannot complete these steps today. Use documentation and demo data to define the workflow. Use your own data and people to check that the workflow meets your team’s requirements.

What you set up

Talk to us

Request a walkthrough with a description of your workflow. For Enterprise deployment, SSO, billing or support terms, contact sales. Do not send credentials, patient or customer scan data, storage locations, or confidential strategy or contract material through the contact form. A description of the workflow is enough.

Next step

Follow the Quickstart, then Register a source for your first project.
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Last verified2026-09-30