Published Release Notes

Text analytics models editing and versioning

Pega Platform™ now supports editing and updating training data for text analytics models.

Pega Platform also supports the versioning of text analytics models. When you update the model, Prediction Studio creates an updated model version. You can then switch between the model versions.

Upgrade impact

In versions of Pega Platform earlier than 8.3, the training data for text models was stored in the database. In Pega Platform version 8.3 and later, the training data for text models is stored in Pega Repository. You cannot build new models without setting the repository. After the repository is set, all text models are automatically upgraded and will work normally.

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

After a successful upgrade, set the repository in Prediction Studio before building or updating any Natural Language Processing (NLP) models.  In Prediction Studio, click Settings > Text Model Data Repository.

For more information, see:

• Increase the accuracy of text analytics models by adding feedback data (8.3)
• Updating training data for text analytics models

Ability to support advanced device features with Pega Infinity Mobile Client

Pega Infinity Mobile Client™ now provides a development kit that you can use to make mobile apps support advanced device features that are typically available to native applications, for example, an embedded laser scanner or a projector module, and integrate functions of external software solutions, for example, a cloud-based file storage.

For more information about enhancing mobile apps with device feature support, see the documentation for the development module in the latest Pega Infinity Mobile Client distribution package on Digital Delivery.

Text analytics models migration

Pega Platform™ now supports the exporting and importing of text analytics models. For example, you can export a model to a production system so that it can gather feedback data. You can then update the model with the collected feedback data to increase the model's accuracy.

Upgrade impact

In versions of Pega Platform earlier than 8.3, the training data for text models was stored in the database. In Pega Platform version 8.3 and later, the training data for text models is stored in Pega Repository. You cannot build new models without setting the repository. After the repository is set, all text models are automatically upgraded and will work normally.

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

After a successful upgrade, set the repository in Prediction Studio before building or updating any Natural Language Processing (NLP) models.  In Prediction Studio, click Settings > Text Model Data Repository.

For more information, see:

• Increase the accuracy of text analytics models by adding feedback data (8.3)
• Exporting text analytics models
• Importing text analytics models

Support for the JSON Web Token Bearer grant type for accessing external APIs

You can now access external APIs by using the new OAuth 2.0 JSON Web Token (JWT) Bearer grant type, in an OAuth 2.0 authentication profile. To use the JWT Bearer grant type as a client assertion, source the JWT from an active SSO session, a token profile, or a property reference. You can use JWTs that you obtain during an OpenID Connect SSO in connectors, to achieve user impersonation flows, such as the On-Behalf-Of (OBO) flow. The OAuth 2.0 type authentication profile now also supports authentication of client applications by using Private Key JWTs.

Instances of the OAuth 2.0 provider are now deprecated. As a best practice, use the new, unified authentication profile configuration instead.

For more information, see Configuring an OAuth 2.0 authentication profile.

Upgrade impact

After an upgrade to Pega Platform 8.4 and later, Authentication Profiles can take advantage of the new JWT based OAuth 2.0 grant type and client authentication features. To take advantage of this and other new security features, you must update any existing Authentication Profiles formats must to use those in Pega Platform 8.4 and later.

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

Since these features are available only for profiles created in Pega Platform 8.4 and later, clients must open and then save existing 'Authentication Profile' instances to ensure that the configuration is compatible with the latest authentication formats.

Connect to Amazon SageMaker models in Prediction Studio

Make the most of your custom Amazon SageMaker models in Pega Platform™ by connecting to the models in Prediction Studio. You can then run the Amazon SageMaker models as part of your decision strategies.

For more information, see Enrich your decisioning strategies with H2O and Amazon SageMaker predictive models (8.4).

Import H2O models to Prediction Studio

Make the most of your custom H2O models in Pega Platform™ by importing them to Prediction Studio. You can then include the H2O models in your decision strategies.

For more information, see Enrich your decision strategies with H2O and Amazon SageMaker predictive models (8.4).

Support for auditing adaptive model decisions

Pega Platform™ now stores all adaptive model scoring data so that you can identify the source of each decision, such as the exact model version that was used for scoring. With this feature, you can ensure that your application is auditable, transparent, and in compliance with regulatory requirements related to using adaptive models.

For more information, see Configuring the Adaptive Decision Manager service.

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.

New text analytics APIs for Intelligent Virtual Assistant

Pega Platform™ now provides text analytics APIs that separate Intelligent Virtual Assistant and text analyzers into independent modules. This solution prevents integration issues when you change your text analyzer configuration.

For more information, see Text analytics APIs.