With this release, we’ve added the ability to do page-level Bates auto-linking in Storybuilder, preserve legal holds information after database deletion, and more — read on for more information about the features coming out this month! If you would like to learn more about the features in this release, join us for a live training session.
User-facing features in this release:
- Page-level Bates auto-linking in Storybuilder
- Preserve Legal Holds information after database deletion
- Freeze predictive coding model
- Visual Improvements
Page-level Bates auto-linking in Storybuilder
Storybuilder users can now auto-link specific pages of a document when citing evidence in a Draft or Deposition. Drafting using evidence often requires granular citations to connect specific, relevant aspects of the evidence to the argument or analysis. Using this new feature, you can cite the relevant page number of the document, either by typing the Bates number of that page or by adding the page number after the Begin Bates, which adds a document reference and creates a bookmark on that page.
Learn more in our article about Storybuilder Drafts.
Preserve Legal Holds information after database deletion
Legal holds associated with a database are now automatically preserved when that database is deleted. When a database with legal holds is deleted, the database is converted into a Legal Holds matter, which is accessible to Organization Admins and Legal Holds Organization Admins on the Legal Holds tab of the Organization page.
When deleting a database, the warning that explains the consequences of deletion has been updated to explain that the legal holds associated with the database are preserved. The warning now reads "All existing legal holds will be preserved and accessible to Organization Admins and Legal Holds Organization Admins from the Legal Holds tab of the Organization Admin page."
Learn more in our article about Legal holds matters.
Freeze predictive coding model
Users with Admin permissions on predictive coding models can now freeze a model. Freezing a model stops all updates on the model, even when activity on the project, such as reviewing additional documents, would typically trigger a model update. When a model is frozen:
- Prediction scores for documents do not change
- Performance metrics for the model do not change
- You cannot edit a model, other than changing its name
Here are a couple situations where freezing a model can be useful:
- You are doing quality control (QC) work or reviewing a sample of unreviewed documents for validation and want the scores to remain consistent while review work is being applied to documents.
- You want your generated prediction scores and performance metrics to remain unchanged after reaching a certain threshold dictated by a discovery agreement with the opposing party.
Learn more in our article about interpreting a predictive coding model.
Visual Improvements
- In the Updates section of a predictive coding model, the button now says Update Models to better reflect that selecting this button triggers an update for all predictive coding models in the project.
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Do you have feedback about:
- this release document? Submit your feedback
- the features in this release? Email feedback@everlaw.com