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Communications Mining is now part of UiPath IXP. Check the Introduction in the Overview Guide for more details.
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Communications Mining user guide

Last updated Aug 1, 2025

Pinning and tagging a model version

Note: You must have assigned the Source - Read and Dataset - Read permissions as an Automation Cloud user, or the View sources and View labels permissions as a legacy user.

Every time you train the platform on your data, that is, annotating any messages, a new version of the model associated with your dataset is created. As these models are large and complex, previous versions are not automatically stored in our databases, purely as the storage requirements would be incredibly large.

The latest version of the model will always be readily available, but users are able to pin a specific model version that they would like to save. They can also choose to tag pinned models with a Live or Staging tag.

Reasons for pinning a model version

  1. Pinning a model gives you determinism over predictions, particularly for when you are using Streams. This means that you can be confident of precision and recall scores for this version of the model, and future training events will not alter them.
  2. In the Validation page, you can view the validation scores for previous pinned model versions. This allows you to compare the scores over time, and notice how your training has improved your model.

Pinning a model version

To pin a model version:
  1. Navigate to the models page using the navigation bar.
  2. Select the pin toggle to save the current model version.



Updating the tag for a model version

To update the tag for a model version, proceed as follows:
  1. Select the arrow for Tags on any pinned model.
  2. Select Live or Staging, depending on the status of the pinned model in any downstream deployments.

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