Release notes
info
For the list of changes and fixes covered in this release, see the Changelog.
For information on upgrading from previous versions, see the
Migration guide.
6.2.0
2026-01-23
Follow this link to download the zipped distribution files for:
- UI source code
- UI build
- Source files to build the module
- Sample bookmarks
- Offline documentation that can be served by the module
- Maven repository required to build the project and run the tests. The Atoti Server 6.1.15 Maven repository files can be downloaded from here.
Summary
Improvements
- Improved adjustment workflow
- Improved performance for bulk adjustments
- Enhanced performance for task initiation and retrieval
Improvements
Improved adjustment workflow
The adjustment process has been improved to deliver greater efficiency and transparency:
Immediate Adjustments:
- Users with the appropriate permissions can adjust cells instantly, accelerating the workflow and reducing delays.
Contextual Visibility:
- Adjustments and related commentary are displayed alongside the underlying data, in the process task drawer, enabling users to review changes and their impact without losing context.
Streamlined Sign-Off:
- Users now have the option to adjust data and review Sign-Off tasks directly within the dashboard, without the need for navigating through the tasks screen, reducing unnecessary navigation and clicks.
These enhancements allow users to work more efficiently, make informed decisions faster, and maintain a clear view of all changes within a single interface. This means less time navigating between screens, quicker decision-making, and a clearer understanding of how adjustments affect your data—all in one place.
Improved performance for bulk adjustments
We have introduced several optimizations to enhance the performance of bulk adjustment operations, resulting in faster processing and improved efficiency when executing large volumes of adjustments.
Enhanced performance for task initiation and retrieval
We have optimized the application to significantly reduce the time required to initiate and fetch tasks, even as the volume of application data grows.
This improvement ensures that scaling your operations will not compromise speed or usability.