Published Release Notes

Create predictions in Prediction Studio

Predict customer behavior and business events by creating predictions. To create a prediction, you answer a series of questions about what you want to predict. For example, you can create a prediction to determine the likelihood of customer churn.

For more information, see Create predictions in just a few clicks (8.4).

Sign and encrypt signatures and content with additional algorithms

You can now authenticate using JSON Web Token (JWT) token profiles to symmetrically and asymmetrically encrypt both signatures and content. All algorithms in the Nimbus JWT library are supported, including nested tokens. Custom key identifier headers (kid) are also supported. Use token profiles to securely propagate identities and transfer data between systems.

For more information, see Creating a processing JSON Web token profile.

For more information, see Creating a generation JSON Web token profile.

Improvements for test cases and assertions

The process of modifying test cases and assertions has been improved. Adjusting test cases to application changes is now much easier.

You now can:

• Select a page on which to run a tested rule.
• Change the class and rule of unit test cases.
• Create assertions that validate specific error messages on pages, properties, and activities.
• Automatically update decision result assertions with property changes made to a rule.
• Modify a rule's properties directly from decision result assertions.

For more information, see:

• Updating scenario tests
• Setting up your test environment
• Configuring page assertions
• Configuring property assertions
• Configuring decision result assertions

Automatic model training when mapping entities to case properties in Email Bot

You can now initiate automatic feedback to entity models in Pega Email Bot™, during manual mapping of email content to a case property.

To enable automatic feedback, you set the Work-Channel-Triage.pyIsRuntimeFeedback rule to true in Pega Platform™. By default this feature is disabled. Enabling this feature ensures that the email bot is more responsive by automatically copying detected entities, such as names, locations, dates, and ZIP codes, to case type properties of a case type.

For more information, see Email triage, Email channel NLP model and Enabling the NLP model training for the email channel.

Anypicker control is now available

The new Anypicker control displays a drop-down list of values that you can group into expandable categories for faster browsing. To save time and improve search accuracy, the Anypicker control filters the available values based on the characters that the user enters.

For more information, see Adding an Anypicker control.

Email bots now support multiple languages

You can now configure Pega Email Bot™ to perform text analysis, use training data and triage emails in multiple languages, for example, English, French, German, and Spanish. By detecting topics and entities from emails in different languages, the system can suggest the correct business case and provide an email response in the user's own language.

For more information, see Selecting languages for an Email channel and Enabling automatic language detection for text analysis.

Referencing Rule tool in Dev Studio

The Referencing Rule tool now runs in Dev Studio without the need for Adobe Flash Player. This enhancement integrates the Referencing Rule tool into your work environment, which improves productivity by reducing context switching.

For more information, see Finding rules by dependency.

PDF/UA support

PDF documents that you generate in Pega Platform™ are now in PDF/UA format. This enhancement improves accessibility for users who rely on assistive technology, such as screen readers.

For more information, see Setting PDF file versions.

Upgrade impact

With an upgrade to Pega Platform 8.4 and later, the underlying PD4ML library in Pega Platform changes from v3.10 to v4.x. Following an upgrade, most standard HTML-CSS conversions to PDF work seamlessly; however, if you use the following custom coding in their application to convert HTML to PDF, you may find that PDF generation works differently than expected or no longer works:

• Application layer Java in activities that directly link to the underlying PD4ML library
• A Rule Utility Function
• PD4ML tags in HTML fragments

For example, the following PD4ML proprietary CSS keywords are no longer supported in v4.x:

• pd4ml-page-break-border-top
• pd4ml-page-break-border-bottom

What steps are required to update the application to be compatible with this change?

After you upgrade to Pega Platform 8.4 and later and find your PDF generation works differently than expected or no longer works, you should consult the latest documentation available at pd[4]ml support site. You may also consider using the Compact CSS instead of the application skin for PDF generation; for details, see Creating PDF files by using a compact style sheet.

Custom activities protection

Case tags for improved case search

Pega Platform™ now supports enhanced tagging for case types so that you can search cases by tags. As a result, tagging is more consistent because you can define a set of suggested tags that users can add to their posts and cases. When users search for cases, they can apply several filters, for example, recently added or most frequently used tags.

For more information about tags, see Tagging cases in Dev Studio, Tagging cases in App Studio.