Pegasystems: Leveraging a decade of AI expertise to elevate application development with GenAI

In a joint interaction, Deepak Visweswaraiah, Vice President, Platform Engineering & Site Managing Director, Pegasystems, and Stephen Bixby, Senior Vice President, Product Development, Pegasystems, speak about the cutting-edge GenAI innovations at Pegasystems, specifically focusing on the Pega Infinity platform. They discuss how tools like Pega GenAI Blueprint and Pega GenAI Coaches are redefining enterprise workflows and empowering businesses with AI-driven decision-making capabilities. The leaders also address Pega’s cloud-first transition, highlighting challenges and opportunities in this space, and how Pega’s industry-agnostic platform is tailored for sectors like healthcare, financial services, and manufacturing, ensuring real-time customer engagement through AI-powered insights.

With the recent enhancements to Pega Infinity, how do you see Pega’s GenAI  tools like Pega GenAI Blueprint and Pega GenAI Coaches redefining enterprise workflows in the next few years?

Stephen Bixby: The GenAI explosion, including tools like ChatGPT, has been a game-changer for us at Pega. Over the last 18 years, we’ve built a model-driven architecture that captures business intent using natural language, rather than code. This approach aligns perfectly with large language models, allowing us to create applications without complex coding. GenAI has significantly accelerated the process of building applications for developers. For end users, we’ve developed tools like Pega GenAI Coaches, which guide them by providing real-time insights, external information, and suggestions, enhancing their experience. This demand for digital transformation is pushing enterprises to modernise legacy applications, and tools like our Pega GenAI Blueprint are making it easier to transition these outdated systems into modern, cloud-native workflows.

Deepak Visweswaraiah: To add to Steve’s points, AI isn’t new to Pega. We’ve been using AI-driven decision-making, predictive analytics, and other AI technologies for over a decade. With GenAI, we can now enhance application development even further. Our customers, especially large enterprises with legacy applications, can rethink and modernise these systems efficiently, without huge upfront costs. With Pega, they can generate blueprints, preview how modern applications will function, and streamline the ideation process. Additionally, our platform’s GenAI features empower developers to be more productive, and tools like Pega GenAI Coaches help employees be more efficient. We’ve embraced GenAI quickly due to our long-standing AI-driven architecture, which allows us to deliver these innovations across the platform effectively.

As you mentioned, Pega has been instrumental in modernising and automating many legacy enterprises, playing a major role in this space. However, in India, approximately 60-70% of businesses are MSMEs, and there has been a significant rise in startups. What is Pega’s traction in these markets, specifically with MSMEs and startups?

Deepak Visweswaraiah: To be transparent, our primary focus is on large global enterprises. We don’t actively sell into the Indian market as such. Many large enterprises have GCCs in India, and we’ve invested heavily in supporting them. Many Pega applications are built by teams in India, and the ecosystem is significant here due to our strong partner network. These partners have made substantial investments in India, and we collaborate with them to help large enterprises develop applications and improve business processes, particularly with the growing GCC community over the past 12 to 24 months.

Stephen Bixby: Additionally, a number of Pega partners in India are entrepreneurial system integrators (SIs) who implement Pega solutions. We also have a product called Pega Launchpad, aimed at companies looking to build SaaS cloud offerings. Launchpad serves startups, entrepreneurs, and small businesses wanting to create B2B SaaS applications. In that space, we do work with startups and smaller enterprises.

Pega Cloud’s strong ACV growth is notable. What challenges and opportunities have emerged during Pega’s transition from perpetual licenses to a cloud-first model?

Deepak Visweswaraiah: The challenges we faced during our transition to a cloud-first model are quite similar to those other companies have experienced. Moving to a cloud-native SaaS offering requires significant changes in the operating and pricing models. We’ve successfully navigated most of this journey and are close to completing it. The main challenge lies in transitioning existing software. For new projects, it’s straightforward to deploy them on the cloud. But with legacy systems, we have to decide whether to lift and shift them directly or modernise them to take advantage of newer technologies. This varies depending on the client. Sometimes it’s best to leave certain applications as they are, while in other cases, we recommend lifting and shifting, followed by modernisation, or even combining multiple applications for a more modern approach.

Stephen Bixby: I agree. Many software companies have taken this path, and it’s working well for Pega and our clients. When I talk to clients using Pega Cloud, the conversations focus on the software’s functionality. But with clients running their own infrastructure, the discussions revolve around infrastructure issues. Moving to the cloud allows businesses to focus on what matters most—delivering value through applications rather than managing the tech stack.

Deepak Visweswaraiah: Absolutely. There’s also the point about building infrastructure within private clouds and continuously optimising costs and performance. This is an important value we continue to offer our customers.

How does Pega tailor its solutions for industries like healthcare, financial services, and manufacturing, and what role does GenAI play in these sectors?

Stephen Bixby: The Pega Plus platform is industry-agnostic, offering a single platform for various sectors like financial services, healthcare, and government. We do provide accelerators and starter applications specific to these domains, such as FedRAMP for government clients in the US, which ensures the highest level of cloud security with AWS GovCloud.

Deepak Visweswaraiah: Pega has a strong presence in verticals like financial services, telecom, manufacturing, and automotive. This is driven by our deep industry domain knowledge. Essentially, Pega’s platform is a base layer that remains agnostic to the industry. We have application engineering teams that build industry-specific solutions on top of the platform. For example, in the contact centre space, we offer a customer service application that leverages the platform’s full capabilities. Similarly, our Customer Decision Hub helps businesses decide which offerings to propose to their clients using an AI-powered engine. In financial services, we offer specialised applications like CLM KYC and smart disputes for fraud detection. While Pega provides these applications, many clients build their own solutions on top of our platform, creating hundreds of use cases tailored to their needs. Overall, our platform remains industry-agnostic, with strong traction in key sectors.

Could you elaborate on the updates to the Customer Decision Hub and how they enhance real-time customer engagement through AI-driven insights?

Stephen Bixby: The Customer Decision Hub (CDH) is a standout product, offering the best real-time interaction management solution on the market, but it’s quite niche. It identifies the next best action for any given individual, making it a one-to-one customer engagement tool. Instead of targeting a segment of people based on broad criteria like age group or salary range, CDH focuses on individual-specific actions. Managing such a precise system can be challenging, so we’ve created an interface that helps marketers view, simulate, and understand changes in real-time. I’m particularly excited about the CDH blueprint, which will allow users to simulate various scenarios and better grasp how Pega’s one-to-one approach works, similar to how Pega GenAI Blueprint automated workflows.

Deepak Visweswaraiah: Traditionally, if I wanted to market a product like a water bottle, I’d probably buy a list of 40,000 people and send them the same email. CDH changes that approach by tailoring marketing to different individuals. For example, one person might like the bottle because of its colour or size, while for someone else, it’s just about needing water. CDH helps identify how to market the product to different profiles and leverages AI to maintain brand voice across various messages, whether it’s emails or banners on a website. We’re also using GenAI to create treatments, such as text and sometimes imagery, although AI image generation still needs improvement before it can be widely adopted. This tool sparks creative ideas for marketers, who can then refine them with their creative teams.