Appian Corporation Class A Common Stock Citi’s 2026 Global TMT Conference

Thank you for having me. Great to be here. Great.

Yeah. Appian has been in business for 27 years, and what we do is we automate complex business processes. That's a lot of words, so I'll give you some examples. We automate fraud prevention for financial institutions, mortgage or health insurance applications for healthcare and financial services companies, a variety of public sector use cases. One of my favorites is we run inventory of ammunition for one of the branches of the U.S. military, so that's as mission-critical as it gets. What these use cases have in common is a few things. Number one is they tend to be cross-functional. They tend to be mission-critical, and accuracy is very important. They frequently involve the customer in addition to the company itself, and accuracy is exceptionally important. The other question that usually comes with that is, okay, well, what does Appian replace?

The answer is, there is always something in place. Sometimes it is just a paper process that becomes automated for the first time. Other times, it is a homegrown application that is now having trouble scaling or simply cannot keep the functionality what the business needs. Or it could be a rudimentary automation tool, a third-party automation tool that, again, cannot meet regulatory requirements or security requirements or accuracy requirements. Appian steps in and replaces it. The answer, whatever it is that customers use us in order to have greater flexibility, greater agility, lower cost, and in many cases, direct revenue outcomes for using us, and that has been our story for the quarter century now.

Yeah. We are seeing a very strong demand environment, and it is really driven by our AI capabilities. Appian has been out there for multiple years now talking about AI as this powerful technology. It has tremendous benefits, but it needs a framework to actually operate at scale. We talk about this as AI in Process, and now you have heard a number of terms that have emerged for this idea, whether you talk about an agent harness or talk about orchestration layer. It is this idea that AI needs something in order to be effective and accurate at scale.

Because we have been out there, consistently talking about AI in this context, and because our product actually delivers AI capabilities and functionalities and strong returns while adhering to accuracy and performance requirement that our customers need, which are highly regulated industries in the public sector, we are seeing the demand grow. We are seeing strong pipeline that is converting, and I liken that to a wave. We have a wave of demand coming our way, and then it is our job to surf that wave or rather convert that demand into actual revenue, and we are doing a great job.

Happy with execution, continuous improvements in sales productivity, and you combine existence of demand with ability to close it, and that's been the story of Appian for the last couple of quarters and the story behind our acceleration that you mentioned on our cloud revenue in particular over the last couple of quarters.

Yeah. So front and center for us right now is a use case or a functionality that we call DocCenter.

Okay. DocCenter is AI-enabled document processing at high accuracy and already a part of your process.

So you're not separately processing your mortgage applications in one silo and then feeding it into some process. It's all integrated in a single process and with high accuracy and ability of AI to reason and send for your next action, whatever it needs to be. The great thing about document processing is that it's a very horizontal use case. Every enterprise is drowning in documents of some sort. So it applies in every one of our verticals. It applies in every one of our geographies. And more importantly, everybody has more than one use case. So an example that comes to mind for me is a health insurance company here in the U.S. that implemented its first DocCenter use case in June.

They already need to buy incremental AI usage just to satisfy their use case, and they're talking to us about the next couple of use cases that will only further drive the need for their spending on our platform. I think about DocCenter as kind of the tip of our AI spear, and that's probably a multi-year cycle because, again, doc processing is such a pervasive use case across enterprises and certainly in our industries.