Red Hat has planted some artificial intelligence in its Process Automation middleware and made allowances for the increasing importance of business analysts and cloud native.

The latest release will allow customers to embed “predictive analytics into their decision management applications to create intelligent, automated systems that help them better interpret and respond to changing market dynamics.”

This will come in the shape of models expressed in Predictive Model Markup Language, which can be trained elsewhere, then imported into Red Hat Process Automation.

These will be implemented within a Decision Model and Notation decision model, the vendor said, so that users have “greater visibility into how an automated system reached a given conclusion.” This means “more explainable AI” and, more importantly depending on your point of view, satisfies the requirements of GDPR and similar regulations which require that automated decisions be explainable.

Red Hat also said the platform now supports a “micro-frontend architectural approach” via an updated app builder component. This will allow users to “decompose client-side interfaces for process- and decision-based business applications”. Which should make it easier to exploit containers and microservices.

The company says this will make life smoother given the increasingly influential role of business analysts alongside traditional developers, with each group getting “tooling tailored to their specific needs and expertise” while retaining “the governance and oversight required by IT, and take advantage of cloud-native architecture.”

Other changes include the introduction of Level 2 OpenShift Operators, which will simplify deployment and management of process automation on Red Hat’s OpenShift platform. The new release also includes a “preview” of high availability support for the business central component on OpenShift.