PegaWorld iNspire 2023: Pega 101: An Introduction to Pega

Whether this is your first PegaWorld or your 30th, there's plenty for you to learn in this introduction to Pega's industry-leading platform for AI-powered decisioning and workflow automation.

Learn about the incredible technology that powers our intelligent automation, customer service, and one-to-one customer engagement solutions, which drive unprecedented value for our clients around the world.

This session will take place on both Monday and Tuesday.

Transcript:

- Good morning, everybody. My name is Ben Baril. I'm the director of the office of the CTO here at Pega. I've been with Pega for 15 years. I've been to over 10 live PegaWorld sessions. I've presented this exact breakout multiple times, including a couple of times virtually than I'm gonna try to forget about. But I have to tell you, I am more excited than ever to talk to you all about Pega and introduce you to Pega and do this one-on-one session. But before I dive into it, let me pass it over to my good friend and co-host Anu Shah.

- Thank you, Ben. Hi everyone, my name is Anu Shah, senior manager of specialist solutions consulting. That's a mouthful. I've been at Pega for over 13 years now, and I've seen the evolution of our technology from Pega 4.x to Infinity '23, which I think is our most exciting release yet. And over that time, my team and I have been able to work with some of the world's largest organizations to help innovate solutions. And I'm gonna share some of that experience here with you today. Experiences that include discussions with your organizations and our clients about the current challenges facing your business. And things are hard right now. There's high inflation, interest rates are rising, and many people are struggling and living paycheck to paycheck. And that, in turn, is reducing their spend with your businesses. And complex forces are driving further disruption in this environment. There's employment challenges. The pandemic led to a highly decentralized workforce. And there was a great resignation combined with wage inflation leading to large skills gaps within organizations. At Pega, with one of our customers, when the pandemic hit, the call center couldn't come in and the claims processors couldn't come in. Claims were paper-based, and we had executives processing those claims themselves. We are seeing supply chain challenges. There's huge risk when you're single sourcing your goods and services. And those goods and services could be materials or it could be your engineering resources or your call center resources. So organizations are looking to multi-source and reduce that risk. And we're also seeing multi-shoring, and that's when organizations are moving from manufacturing in a single country to multiple countries. And that's reducing your risk due to acts of God and the acts of politicians. And your organization needs to be agile. There's also the rising importance of ESG. And expectations around sustainability are really increasing for many organizations. So one customer we worked with recently, my team worked with the customer, and they were really looking to optimize KPIs around reducing their carbon footprint. They weren't looking at direct profit. So what they were looking at doing was leveraging our low-code platform and workflow optimization combined with artificial intelligence to reduce their transport waste. So ultimately your business has no choice but to optimize, to become more efficient as well as responsive to the customer's needs. And to be responsive, organizations are really looking to better align and become more autonomous across their operations, their service, and their engagement. Analysts like Gartner and Forrester are finding organizations investing in a few key areas right now. And as you heard earlier today from Rob, hyper-personalized and proactive engagement is one key area. And it's a really a radical rethinking of how you engage with your customers. No longer are we segmenting and saying every 18 to 24-year-old is the same individual. We're really looking at those people and as your customers as a unique person at that moment in time on their channel of choice. And this really means moving from segmented and reactive to more personalized and proactive. And to do that, you really need AI-powered decisioning and the ability to respond to them in realtime across all of their channels. Organizations are also looking for more connected and holistic experiences for their customers. And this is about shifting from selling and taking a product-centric approach to a more customer-centric approach and creating an experience around your customer that spans those organizational silos and creates an experience like delivering holistic care in healthcare. And it's more about delivering that experience like we see now with our healthcare insurance versus the old way of just providing a product or delivering mobility as a service instead of just a car. And to do this, you need powerful workflows to take those disconnected tasks and create an end-to-end experience. Lastly, I'm really seeing leaders looking to really reduce the manual work within their organizations as they hyper-focus on efficiency and effectiveness. And to do this, you need to leverage artificial intelligence as well as workflow automation. And I'm seeing organizations across the globe, look at leveraging generative AI, maybe as a job aid to their employees, or leverage AI to determine if, for example, a claim needs to be straight-through processed if they know it will be approved anyways, reduce that manual load. So the disruptive forces affecting your business, they're plentiful, and they're coming at you fast. As we heard today, generative AI is a major disruptor in our world right now, and it's disrupting even Pega's business. No longer are there multi-year digital transformation projects that can ever just be considered done. Organizations are struggling with that approach. So we're finding and we're recognizing that change is near constant. As humans, we adapt and we change, so businesses need to also. And that's where Pega's low-code platform can really help you create an organization that's built to constantly and continuously change.

- Which, thanks, Anu, is why you heard Alan say yesterday that Pega's tagline for the last 20 years is build for change, right? It's not a coincidence that we chose that as the tagline because Pega is the low-code platform for AI-powered decisioning and workflow automation. Our clients, all of you or hopefully all of you after this conference, trust us as an essential part of your digital platforms, building agility into your operations so that you can work smarter, unifying experiences and adapt to change. Now, I'll talk a little bit about some of the specific industry solutions and what we do in each of your industries in a minute. But I want to talk at a high level about the areas that we solve for for complex organizations like yourselves at an enterprise level. So we solve for these five outcomes for the world's largest and most demanding organizations. Now let me be clear. I'm not saying that each of you are demanding, but the reality is that your customers are demanding. And so you need to react to that. And your customers are me and Anu, right? We are the, you know, digital natives, right? The TikTok generation, the instant gratification generation. From my perspective, this presentation has gone on too long. But hang tight, I've got some cool stuff to show you. We've got a couple of demos as well. So what do our clients do with us? You heard this morning during the keynotes from Virgin and Rabobank, right? They personalize engagement, right? This is the idea of taking that hyper-personalization and presenting the exact next best action, or opportunity, or offer to your customers, driving up massive amounts of increased revenue like you see from Vodafone and 100 million in pounds of profit that they generated by increasing their click-through rate by three times, right? They accelerate acquisition and onboarding. Such a critical part of the customer journey, right? That first moment of truth that you have with your clients is when they onboard. What kind of an experience is it that when you, you know, I onboard with a new cell phone provider, and I get a bill that I'm not expecting, right? Bill shock, that's terrible, right? I'm already looking for another provider after just signing up. They automate customer service, increasing net promoter score and cutting costs in the call center. They streamline operations, right? Automating workflows for mission-critical, sometimes life-critical applications. And finally, where it all started is we resolve exceptions, preventing things from going wrong very often or just, you know, managing them when things go bump in the night. And so as you can see here with some of the references that we have, our clients are delivering value across all of these areas at enterprise scale and stability. Now, I said that I would come and talk about some of the industry examples of what we're doing with each of your industries. And I will tell you, if you didn't visit the Innovation Hub yesterday, take a chance to go down there and visit it today and go to your specific industry areas to talk with folks who can really dive into each one of these solutions. I'm gonna highlight three of them that I find, you know, the most interesting or maybe just my favorite, my personal favorite. So if I think about in the financial services sector where we work on personalizing engagements. We work with some of the world's largest banks to display realtime offers on their website that gets hundreds of millions of page views a day in subseconds. And these offers are hyper-personalized to the individual at the moment they are going to the website based on their history with that organization, based on all the other marketing information we have about them. And that is just skyrocketing the acceptance rate. I know that when I go to website, right? If I see an ad for something that is completely irrelevant to me, I basically just turn off, right? I'm not interested in the rest of the content there. But if I see something that actually is like, oh yeah, that's interesting, I'm gonna click on it, right? I'm gonna be interested. In the automating customer service, right? It's not something you might think about when you're thinking about government, right? But what is renewing your license at the DMV or applying for a fishing or hunting license? It's a customer service interaction. And some of the world's, the governments in the United States, Canada, and around the world work with Pega to streamline those customer service interactions, ultimately improving citizen satisfaction and employee satisfaction because we're making it easier for people to get what they want done as quickly as possible. And finally, in the manufacturing space, one of the most interesting, and I think coolest combinations of technology bringing together the internet of things, realtime AI sort of at the edge along with our workflow automation capabilities, we're able to predict and automate the repair schedules for heavy machinery and farming equipment so that we keep them working and out of repair for as little as possible, right? We're actually able to prevent a machine from breaking down because we can do these small little repairs before things go really wrong. So that's a little bit about some of the use cases from an industry perspective. Like I said, go check out more examples in the Innovation Hub. Now we're gonna dive into what about our technology enables us to have these kinds of outcomes, Anu.

- Thanks, Ben. So Ben discussed the outcomes we achieve, the industries we service, and the value we create. But how do we really do this? And we do this leveraging our center-out business architecture. And that avoids two key mistakes. The mistake of starting in your channel or starting in your backend. And center-out, you've heard about, Alan spoke of it yesterday. The way I think of it is it allows you to worry less about your workflows because you just need to create things once in the center, and you worry less about what comes next. What data source, what acquisition, what channel, and you can focus on your core processes. So by way of example, I was recently on a trip with friends, and we were trying to check into a flight, and we got an error. So we immediately pulled out a laptop and went to the web. And we expected a different experience on the web versus mobile. But that's not what the experience you wanna have for your customers, right? So let's start and talk about center-out, and let's start in the center. And there's the muscle of case management. And I think of this as digitizing that yellow manila folder and making it digital. And we marry that with the brain and that's a central brain used to make decisions. And that brain, it's included business rules since Pega was founded 40 years ago, but it now includes text and speech analytics, complex event processing, and, of course, our world class decisioning and predictive and adaptive analytics. And now in Infinity '23, I'm sure you've heard by now, we're including generative AI. And we're really excited by that inclusion into this brain. The importance of the brain is that it's central, and it delivers the same decision and the same action across all of those channels. And with your process and logic defined in the center, you need to connect up to your channels. And we do this leveraging our digital experience API or DX API. I think of the DX API as really enabling a channel versus creating an entire project and team around that channel. And the UI can be Pega or it can be in a technology like React. Ben will talk more about it in a few minutes. But the thing to remember is that allows the user experience to respond and update automatically as the process and the data change. There's no coding, which allows for consistent experiences for your users. And once you have those channels defined, you need to get access to the data. And we heard about accessing data earlier today in one of the keynotes. And there's a lot of complexity in that data. As you have legacy systems, you're making acquisitions, there's data from different sources to, for example, create a view of your customer or your account. And what we do is we create something called live data. And that's a data virtualization layer that lives between your process and your data. And it allows for the dynamic and conditional retrieval as well as the normalization of that data. And what that allows you to do is modernize or access different data source without affecting your processes. And then critically, any center-out business architecture has to be able to incorporate the variations in your business. Often you're spanning products, and your spanning geographies, and you don't want to recreate those processes as you accommodate those variances in your business. So our patented Situational Layer Cake allows you to scale your workflows across those dimensions without copying and rewriting. And the important thing I think about when I think of the Layer Cake is because of the way we're architected, it allows you to get to market faster. And all of this tech is built on an architecture that's really future-proof. So it allows you to rapidly innovate, scaling your workflows, and taking the really good ideas that people have to allow them to build solutions very quickly.

- Okay, that's really cool. And I hear, you know, we've been talking about some of the technology that drives Pega. We're talking about allowing people that you already have to build applications, right? We've talked about citizen development, and low-code, and some of the other keynotes and breakouts. I can see some people getting a little bit nervous that we're just gonna give, you know, access to everybody to build applications. They're gonna build stuff that's gonna burn down their databases, and there's gonna be, you know, shadow IT on the loose. How do we manage all of that?

- That's a really good question, Ben. So let's talk about the types of applications we support and how we allow governance of those applications. So you allow creators some autonomy, but you also provide governance within the class of applications within Pega. And I believe our platform is the only platform, low-code platform for handling your full spectrum of use cases that you need to develop within your organization from the simplest departmental workflows to the most complex customer-facing applications. And Pega really may be overkill for some personal apps, so we can handle that. But what we do focus on is governed low-code for citizen development. Think of this first class of applications in the orange there as applications created by the business but with strong IT support. And we allow you to do things, take actions like application intake where the business can request an application. We can also assign experienced coaches once you request that application to help you develop it and co-develop and provide some best practices and mentorship. We have guardrail and compliance support, and we have unified DevOps. And we allow for all of this capability through what call the App Factory. There's a booth in the Innovation Hub dedicated to the App Factory if you're interested in learning more. But what it does is it really eliminates that proliferation of applications without IT support. And I think of this App Factory as a little bit like the App Store for your enterprise apps. And we have some of you, including Deutsche Bahn and Ford doing this sort of development and developing these sorts of applications today. And then as that application increases in complexity and criticality, we also support fusion teams. And those are teams that are business and IT together working on applications of that increased complexity and scale. And these teams are combined, and they allow you to deliver applications quite rapidly. And then we also support mission critical applications. And these are built by professional development teams, but with strong business analyst support. And we do this for some of the largest organizations in the world, including the likes of Verizon and Lloyds Bank. But what is unique about the platform is that when you take a departmental or citizen-developed application, and maybe you need to deploy it across a region or across a product line, so it increases in complexity and criticality, we allow you to graduate that application and manage it differently within your organizations. Other software forces you to rewrite. And if you notice what I've been talking about in all three classes of applications, you're also expecting the business to be involved. And I believe that our low-code approach really allows for the knowledge of the business to be better represented and supported by this technology. And business really needs to be involved in workflow creation for organizations to be agile.

- Awesome, so we've shown you a little bit of the technology at a high level. We'll go a little bit deeper, but I thought it'd be interesting for you all just to see a quick demo of building an application. We'll talk you through what's happening throughout this video. There we go. All right, so we're gonna kick off by building an application, right? We're gonna create an auto loan application. We'll give it a name, and we'll, sorry, we'll leverage a couple of existing assets to start, right? So it's the not copy-pasting that Anu mentioned. We'll build starting from an enterprise layer and reuse things like the loan fulfillment and data types. We'll give our application a name, and then we're gonna start defining the stages and steps of this process, much like you would if I asked you to define an application on a Whiteboard today, right? If you need to find some more complex logic, you know, routing decisions, things like that, you can do so in a familiar modeling tool. Looks very much like Vizio if you ever use that back in the '90s and 2000s. Next, we'll decide and define who's gonna work on this application, what specific channels each of those individuals or personas are gonna work on and set that up really defining the requirements for your application as you build it. Now every application needs a data model. So let's configure some simple fields, a couple of calculated fields maybe. Like you can see we're gonna do a loan to value ratio calculation. Pretty easy to set up. We'll just say use this expression, and we've got that taking advantage of the powerful rules engine that's built into Pega. Now our user experience is a prescriptive user experience with a Constellation UX. And you basically just define what fields you wanna have show up in what order, and we'll build out the forms for you, taking advantage of our design system, or we'll talk about later. You can use the DX API to surface that into your design system. And to ensure your business runs efficiently, obviously, we need to have a couple of SLAs. You're gonna define the goal and deadline time, and say, "Hey, notify a manager if this is late," or "Take this action if I need to escalate." We'll leverage our world class rules engine that I mentioned earlier to do a little bit of intelligent routing to route the work to the specific user or work queues based on business rules or even artificial intelligence. And finally, we'll specify some decision tables that you can model to adjust how your workflow runs, like skipping an approval based on the loan value.

- [Anu] Thanks, Ben. And once you have all of that defined within your workflow, you typically want to get access to your data. And when you define a workflow, you typically start with simulated data. And we can leverage our low-code integration wizard to then connect to live data sources to, for example, get make, model, year in a loan app in auto loan. And then we map that data visually to our objects within our workflow. And this is an example of our integration wizard in action. And once you have access to that data, you often want to augment your workflow and create adaptive models to predict, for example, the probability of this loan being approved and leverage that to make decisions like straight-through process the loan if there's a high probability for approval. And maybe combine that with a business rule like it's a low, under a certain threshold or the LTV is good. And once you've defined the AI within your workflow, you often want to channel enable your workflow on mobile. And we allow you to quickly author your mobile app including drag and drop for navigation as well as branding. And we can automatically build a native app on iOS or Android, and even enable that app to be available offline, for example, when you have clients in rural areas. And no system is complete without the ability to explore and analyze all of the work flowing through your system. So we allow you to easily create visualizations to better understand the business and the work flowing through, and even personalize those insights particular to a user so you can create reports for yourselves.

- Awesome, so that was just a quick demo of building an application. Obviously, there's a bunch of different things that we didn't cover. And if you wanna see more about how applications are built, go down to the Innovation Hub, look at the booths, grab somebody from a news team and ask them to build a demo for you if you want. That's what our team does in part. So we've got a couple more slides, about 84 more slides and then another, no, I'm just kidding. We've got a couple more slides, and then we're gonna show you another video that's gonna do a very similar thing, but we're going to supercharge it with generative AI and see how fast that is. Now we did our video, let's talk a little bit about what's inside our center-out business architecture. You heard Anu talk about the architecture, what's inside it, how does it work, let's go a level deeper.

- Thanks, Ben. So you just on the video, our low-code platform means you can define your data, your people, and your processes in a single palette. So we have this visual metaphor for defining your workflow and all of the components comprising it. And let's talk about this in the context of an HR process for screening candidates. The workflow and the process itself is defined in terms of stages and steps. And that's it. This reflects how you think of solving a problem. The stages represent milestones in your case such as collecting a resume, or screening a candidate, or the interview process. And the steps really represent a single task. And that task can be assigned to a system or it can be assigned to a person or a group of people. And we call that a queue or in Pega speak, you'll hear it called a work basket. And this can be the particular task of performing a phone screen or reviewing a single resume. And then you wanna specify the people involved and who play a role in that, the personas, as well as the channels that they access the application through. So you may have someone like a HR representative, or a recruiter, or the candidate, those might be the personas. And then you may have mobile, web, HR portal, or an email as the channel is available to those people. And then we allow you to capture the data that's made available to these roles, or collected from them, or sourced from and sent to other applications. And this is all in a visual metaphor that really allows both business and IT to better understand your workflows, whether they're simple or complex. And then once you define your core workflows that we just talked about, including the interfaces, the data sources, the logic, we can add automations and AI throughout. And some of those automations may be sending out a notification, or it could be leveraging robotics and RPA to send data to or get data from systems where there's not an API available. Then we also want to often add AI-powered decisions to the workflow to predict your outcomes and drive efficiency or effectiveness of your task. For example, in the context of the HR application, we may wanna predict the screening outcome for this candidate. Are they going to get through the screening process or not, and we can predict this based on all of the other cases that have come through the system before this one. And this may save you a lot of time maybe if you're hiring during peak hiring season or the holidays. And in my current role, I'm seeing a lot of organizations around the world look at leveraging AI within their workflows to create efficiency and effectiveness. Some examples include predicting if an asset transfer, an incoming fund transfer request is going to be NIGO or not-in-good-order. And if it is, maybe they wanna do a proactive outreach to that customer to see if they need help before they abandon ship. We're also seeing AI used to prioritize the next best claim to work on and predict the urgency and priority of a particular claim. In turn, reducing fines for SLA breach to the business or straight-through process a credit card dispute if it's highly unlikely to be challenged by the vendor or represented, and if it's a low dollar amount, further saving that manual work. And nobody else can do this in a single platform without stitching together various technologies.

- Awesome, and so once you've built your application and your workflows, you need to enable true composability in order to easily integrate these or activate these in the channels you desire. And that might mean, you know, in the worker channel, right? Using our design system or embedding it into an existing application such as, you know, Salesforce or perhaps your customer service desktop. We introduced the DX API or the Digital Experience API and low-code capabilities to take advantage of it, which enable workflows to be run headlessly and plugged into multiple different form factors easily. The Digital Experience API is a meta-driven API much like GraphQL for the geeks in the audience like myself. So the workflow actually tells the user experience, the front end, what fields, inputs, and validations need to be there. And then you can use whatever latest, greatest technology, React, Vue, Angular, whatever comes up next to actually render those fields onto the screen independently of the workflow itself. So one great example is building out a customer service workflow that's been automated in Pega and then easily exposing that into a Salesforce system so it looks seamlessly. So, you know, your agents are using Salesforce, you don't wanna replace that, that's fine, but you wanna have the power of Pega, and we enable you to do that very quickly and easily.

- [Anu] And when you have those channels that Ben talked about enabled in your workflows, there's often a slight change or a variation in a particular channel. Maybe you wanna hide a user interface field or brand something differently. And that leads right into what building for reuse means in Pega. So the platform really allows you to define your commonalities and specify what's different. So define what's common and specify what's different and only what's different. Organizations often create an enterprise layer as your common baseline to contain definitions of things like security, SSO, and common objects like what a customer is. You may even have standard case behaviors. And then your organization, maybe it's home lending, can create a lending layer for common loan process flows, integrations, data objects, maybe even user interfaces for common lending actions. But there may then be variations for the type of mortgage you are dealing with. And these different loan types may use the common integrations and data objects to find but have those unique case types. And then if you're a global organization, you may have different geographies, and they may have differences due to regulatory language or process variances. And the way we have this layered architecture approach allows, I think, two key benefits. The first is you can have consistency across your operations because you're doing it the same way in those lower layers. And the second is speed and agility. So you're avoiding the copy and paste of applications as you're deploying different products, different geographies, and that really gets you to market more quickly. So by way of example, we had a major insurer with 55 claim systems across 60 countries leading to complexity, lack of standards, and lack of consistency, as well as significant business risk. Using the Situational Layer Cake, they built a global claim system that consolidated that complexity into a single system while still allowing them to provide differentiated experiences in regions or across different lines of business.

- All right, thanks, Anu. So if the Situational Layer Cake is my favorite Pega feature, patented feature that we've had for about 40 years now, data virtualization or what we call Pega Live Data is my second favorite feature because ultimately, every application needs to interface with some data, right? We took these collection of integration patterns and made them possible through a concept that we call live data or data virtualization, right? Think of it as an abstraction layer from your existing systems of records. So regardless of data type, use case, your data is made available for the center-out design, helping you to get work done without having to copy that data into Pega or bringing it near to Pega to act on it. We'll push or pull that data when it's needed in what we call a declarative way, right? So you don't procedurally say like, "Oh I need to get data at this point." It just is available to you when you need it. And because it's been abstracted from the third-party system, that gives you a lot of flexibility to do things that you're gonna want to do with your data. You might need to compose your data from a bunch of different data sources. So you see there, I've got the account data record, right? I'm gonna get some of that information from my data lakes, I might get some of that from SAP, or whatever third party systems and build up a single logical account data model from data from different systems. You're able to transform your data, right? Change the case, do this, right? You might have a field called full name, that's the combination of first name and last name. You get it. Triggering events based on data that's changing in these third party systems. Having a configurable cache in a business rules engine so that you can be efficient with how the data is used, avoiding costly pulls to third-party systems that might slow down the experience for the people using those systems. Best of all, not only are the integrations defined once in a business friendly way using models, right? They can be reused multiple times, whether in a single application or across your entire enterprise, taking advantage of the Layer Cake that we just spoke about. And since it's been abstracted from the source and stored in Pega's rules, the underlying technology and those data systems might change, right? And like Anu said, you might acquire a company, have another data source, Pega doesn't really care, right? You just do that mapping. And with gen AI, the mapping is done automatically for you, and it it's not gonna impact your application. So we talked about the workflow capabilities often refer to Pega as like we do two things really well. You get work done, it's workflow automation, and we help companies make decisions, and that's our realtime AI. So I'll dive into a little bit about what makes our realtime AI real. Now we've been talking about artificial intelligence. You heard Rob earlier, right? This isn't your first PegaWorld. Rob comes up every year at the live PegaWorld and does these amazing presentations about artificial intelligence. I thought it was really cool that he called back to, I think, it was 2017 or 2019 when he mentioned GPT, which was not something that anybody had heard about, but because he is a PhD in artificial intelligence, he was on the bleeding cusp of that. But we've had AI in our product for a very long time, for over 10 years. And we use it to do all these great things, right? Use natural language processing to determine the tone of a conversation, either a voice conversation or a chat conversation, and dynamically change the scripting or the prompts for the agent in realtime as they're talking to somebody, right? Or being able to uncover repetitive manual tasks, taking advantage of the new process mining application that we announced just at PegaWorld this year, right? Uncovering areas where you're gonna be able to automate your applications even more. And now, of course, no presentation would be complete without talking about generative AI in 2023. So we've included over 20 new generative AI capabilities in Infinity '23, including capabilities to generate low-code applications, generate marketing treatments like you saw Rob show on the screen, which is like the coolest mind-blowing thing of combining gen AI with our own CDH brain and generating insights and summaries about your data, right? Being able to actually talk to your data. So let me pass it to Anu to talk about what makes our AI a little bit different from everybody else's and what makes it real.

- Thanks, Ben. So Ben talked about AI throughout the platform and the exciting introduction of generative AI. But what sets Pega apart are two key things. Transparent, responsible AI and easier AI. And transparent and responsible ethical AI, this is where empathetic decisions are made, but with transparency in mind, and they can be tested to prevent ethical bias in those decisions. As you can see here, we are predicting the probability, we're 70% confident that we're gonna miss this SLA for this auto claim. And why are we, if you look at the graph in the middle, we're confident because of the driver's age, their tenure, the fact that there is a pedestrian involved and the age of the car. And those are heavily influencing that predictive value of 70%. And I'm seeing a lot of clients, my team specializes in AI within the workflow, dip their toes into AI and leverage a transparent approach for their employees as they learn to trust the AI. And we can also specify how confident we are in that 70%, which you can use to help with your automation. So that's one example, and it's a really cool way we can see AI. It's what we call a Prediction widget. Second, we make AI easier. I won't lie and say it's easy, but it's a lot easier. And we provide for a low-code approach to add predictions to your workflows. And in Infinity '23, I encourage you to look at the Process AI booth, but we're adding even more automation to, for example, leverage natural language processing, look at data within your cases, and predict the type of case to create within your system. So taking those two approaches, you can have these decisions, and you can combine adaptive decisions with business rules, do it in a visual canvas and do it in one place, impacting all of your workflows.

- Awesome, and I want everybody to focus on this chart here. I'm gonna show you the demo that I promised of generative AI building out the application. At one point, you're actually gonna see this chart, but we will, underneath, explain in English words the reasons, the top influencing factors, and that's all being driven by gen AI, and I think it's a cool feature. So we're gonna show you the demo. It's about two minutes. We're gonna take a break from talking 'cause there's cool music with the demo. Awesome, so I think that's a really cool demo. If you wanna see more of the gen AI features and dive a little bit deeper, you can do so at the Innovation Hub. And we've actually got a really cool generative AI demo on pega.com as well. So last slide. I wanted to talk, you know, we talked a lot about the software, the technology, the value that we're bringing to business, the driving forces. I just wanted to talk really quickly about the portfolio and then we just got a couple minutes left, but we can stay longer to answer any questions that you have. So let's start from the bottom up. Why don't you get us kicked off, Anu?

- [Anu] Thanks, at our foundation, we have Pega Cloud services, and this can be deployed in your private cloud or delivered as a service on Pega Cloud, leveraging AWS or the Google Cloud platform.

- [Ben] We've embraced the microservices architecture, taking advantage of the latest and greatest technology of Kubernetes, Elasticsearch, Cassandra, and Kafka to really orchestrate your platform and get it humming.

- And at the heart of our portfolio is the Pega Platform. And we're not stitching together different technologies. It's all in one product. So the low-code innovation factory provides that governance I was talking about earlier. We have robotics to allow you to retrieve data and send data when no APIs are available. We have process fabric, and that really allows users to look at work across all their systems in a unified place, whether it's Pega or not. Then there's Process AI, which allows you to operationalize your own models, or in a low-code manner, create adaptive models to learn from all of the cases coming before you. We have process mining, and that really analyzes the currently running application to understand what's happening right now in your systems and leverage AI to look for bottlenecks where things are slow, or where people are doing reworks and reworking. And then we also have generative AI, which allows you to use large language models to speed your application development as well as provide better experience for your users, your customers or employees.

- And built on top of the platform, we have some solutions like the Customer Decision Hub, which our business solution that you saw Rob talk about, Rabobank and Virgin Media taking advantage of, to offer personalized engagement for customers, providing, you know, tremendous value, taking advantage of the next best action advisor and our one-to-one strategy optimizer.

- And then there's Pega Customer Service, our AI-powered channel list solution for delivering an amazing experience at scale. And we have voice AI, digital messaging AI, and gen AI. And then Sales Automation, which was actually ranked number one by Gartner for critical capabilities to help streamline your sales process and allows for really truly guided selling.

- Finally built on top of all of that, we have our industry solutions, specific point solutions that we build on the platform like smart disputes and financial services that help some of the world's leading banks dispute fraudulent charges via Visa, Mastercard, and American Express. Our Smart Claims Engine in healthcare, which provides innovation by processing medical and dental claims, which are extremely complex if you've ever worked on them, including the splitting of claims, work routing, or taking advantage of AI to detect patterns in those claims for fraud and the like. So as you can see, we built these in layers, right? Pega loves layers, but the reality is that all these things build on one another. So that's the portfolio at a glance. Really appreciate everybody's time. We've got like 10 seconds left in the session, but we will stay to answer any Q and A that you may have, or you're welcome to go get lunch at the Innovation Hub.

- Perfect.

- Thanks, everybody.

- [Anu] Thank you.

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