AIssisted™ Planning Release Notes

See AIssisted™ Planning Overview, for more information.

  • Daily data is now included in the Time Series Prediction Results Preview Report.
  • Persistent algorithm selection in the Driver-Based Prediction.
  • Accurate KPI card calculations in the Time Series Prediction Results Preview Report.
  • Fixed bugs.
  • Persistent algorithm selection: Your chosen custom algorithms in Time Series Prediction are now automatically saved, eliminating the need to reconfigure settings each time.
  • Easier scenario comparison: You can now clearly differentiate versions for scenarios created in the Data Preparation Wizard, making it easier to compare outputs and track changes.
  • Smarter interpolation warnings: Improved warning handling ensures that you are alerted only when it matters, reducing confusion and improving accuracy.
  • Safer preview experience: The Data Preparation Wizard results preview page is now locked for safer viewing, allowing you to review outputs without accidental changes.
  • Fixed bugs.
  • Enhanced Time Series Wizard experience: Step-by-step video tutorials now guide users through the process, making it easier than ever to get started.
  • New Python extrapolation service support: The Data Preparation Wizard now supports extrapolation via Python, helping to generate more complete datasets for downstream analysis.
  • Improved demo database: Updated demo datasets offer clearer, more insightful visualizations of the Time Series Wizard results.
  • Fixed bugs.
  • The outlier and interpolation algorithms from Python are now included in the Data Preparation Wizard with updated tooltips.
  • Improved the UI experience for the Time Series and Data Preparation Wizards.
  • Solved language issue with other English locales for the Time Series Algorithm Ranking Table.
  • Fixed bugs.
  • Optimized navigation and usability with a guided, step-by-step flow to streamline setup.
  • Faster scenario setup with smart automatically applied default values and relevant context-based information.
  • Cleaner interface and quicker access to key actions.
  • Improved results visualization and KPI insights for more agile, informed decisions.
  • Redesigned to reflect users' feedback and provide a more intuitive experience.
  • Bug fix for splashing behavior that resulted in large cubes and splashing errors.
  • Improved pre-processing and services performance in the Time Series Prediction Wizard with parallelization and zero filter removal.
  • Added more meaningful error message and bug fixes in the Data Preparation Wizard.
  • Fixed various bugs, including the variable setting bug in the Time Series Prediction Wizard that resulted in the Error 400.
  • Increased performance in Time Series Prediction Wizard for time savings of almost 50%.
  • Added more realistic demo scenarios with updated databases containing data throughout 2025.
  • Increased performance in the AIScheduler function, ensuring scheduled jobs are only run once.
  • Improved the prompt for scrolling through the settings on the Time Series Overview page.
  • Fixed bugs.
  • Improved visualization of the training accuracy for the Time Series and Driver Based Prediction.
  • Fixed bugs.
  • Added support for localized versions of English.
  • Updated all sample databases.
  • Fixed bugs.
  • Improved the view for the Detailed Results report in the Classification Wizard.
  • Fixed bugs.
  • Improved efficiency and transparency in the Source Preview report and in the Accuracy reports of the Driver Based Prediction and the Time Series.
  • Updated the Driver Analysis result pages and the Classification Wizard result page to show selected elements.
  • Fixed bugs.
 
  • Improved efficiency and transparency for the Time Series and Driver Based Prediction reports.
  • Improved prediction results for the Time Series and Driver Based Prediction Wizards due to updated database scripts.
  • Improved the error messages with status icons for all Overview pages of the wizards.
  • Fixed bugs.
  • Enhanced the analysis reliability.
  • Enhanced the Data Preparation stability.
  • Improved efficiency and transparency for the Data Preparation and Driver Analysis reports.
  • Fixed bugs.
  • Improved the demo scenarios.
  • Enhanced population of accuracy on base level predictions for the Driver Based Prediction.
  • Updated the AI Transform sample job for demo data.
  • Fixed bugs.
  • Updated the results reports for the Time Series and Driver Based Prediction Wizards.
  • Fixed bugs.
  • Improved performance in the Time Series Wizard.
  • Added a video for user guidance when searching for detailed results on the results page of the Classification Wizard.
  • Improved the warnings in the Data Preparation Wizards for Trend & Seasonality functions.
  • Fixed bugs.

Updated March 2, 2026