Pega recently announced a number of enhancements to Pega Infinity, a software suite for process automation and optimization, demonstrating its commitment to low-code application development.
Called Pega Infinity ’23, the latest release was announced at the PegaWorld iNspire conference in Las Vegas earlier this month. Many of the new features are related to composable application development and deployment, generative AI, and reusability. The new features will be generally available in the coming months.
Low-code application development empowers business users to quickly conceive and implement applications. Its enterprise benefits are increasingly being measured by the quality of experience it produces across a variety of use cases.
“The next generation of low-code is a lot of things,” admits Ken Parmelee, Senior Director of Intelligent Automation Strategy at Pega. “And it has a lot of generative elements in it.” [AI] what we are announcing. “
generative automation
Some of the most notable improvements in Pega Infinity center around the use of generative AI models to meet many of the requirements for building low-code applications. Parmelee said: “You can generate a complete application or workflow. You can generate the underlying data model. You can generate the integration itself as part of it. You can also generate test data.”
Pega Infinity delivers these benefits through a series of what we call “boosters.” Booster relies on advanced machine learning techniques to find, generate and populate information for these use cases. “This means that the manual steps required during app creation and the creation of test data, etc. are greatly reduced, and the app can be created quickly,” he acknowledged Parmelee.
Configurability
Several updates have been made to Pega Constellation, Pega’s design system, to support configurable user experiences. In addition to providing users with what Parmelee called “common objects needed to build applications,” Constellation also has his API that allows users to use his Pega services in other environments, tools, and applications. will be able to access
Organizations can therefore incorporate the salient aspects of Pega tools into other application frameworks they employ. “For us and our customers, Constellation is an evolution that allows us not only to leverage the best experience itself, but also the existing design frameworks we use for our Pega applications,” he revealed. .
template
Constellation also provides a number of pre-built templates that address specific design principles for common use cases. Some of the pre-built properties of the template include various steps for building the application and building the underlying data model.
Users can customize this information to their liking and supplement it with generative AI capabilities. “Generating a generative data model allows us to create more detail about how this is laid out from the data side,” he commented Parmelee. You can also map the resulting data model to a data source.
reusability
One of the benefits of Pega Infinity’s composable approach is that low-code components are building blocks that others can use. Similar to the Data Catalog functionality, the platform includes a new Reuse Library for storing details of composable elements your organization relies on. Libraries make this information centrally discoverable and searchable. A user can publish low-code components to his Pega App Factory for reuse.
“The goal is to have one place where organizations can see all their shared assets,” Parmery said. Organizations can also reuse certain aspects of data governance as part of the platform’s composable methodology. “If there was a specific brand that had to be used, or a specific approval flow that had to be followed, you could build them as common components and I could add that to the application I’m building. We can take it in,” he added Parmelee.
self service
Low-code application development is essential to advancing the goals of the self-service movement. Enhancements represented by updates to Pega Infinity ’23 are calculated to further reduce the time it takes to build applications, deploy them to production, and increase the value you derive from your organization’s content and data.
Not surprisingly, generative language models play a fairly important role in these advances, especially when combined with reusable components in composable applications. Parmelee commented that these developments are part of a larger vision of “making the platform autonomous and capable of doing more self-optimization across tools.”
