Veeva Systems Inc. Wells Fargo 21st Annual Healthcare Conference

Yeah, sure. Sounds good. I'll give you a brief overview of Veeva. Veeva, we're building the industry cloud for life sciences. That means applications and agents and data and consulting, specifically for the life sciences business. Our business is spread across two primary areas: R&D and commercial. R&D is a little bit of the larger portion of the overall business, and within each of those areas, we have suites of products and software products and data products and agents. That includes in areas like R&D, clinical, quality, regulatory, safety, and then in commercial, a number of different areas from core CRM, commercial content, a number of data products that we call Data Cloud. We're helping to make the industry more efficient in how we operate.

We're a public benefit corporation, so we serve the life sciences companies, the people in them, but also we're trying to advance the overall industry. We're relatively early on our journey. Each quarter, we make more progress in terms of building the industry cloud and the adoption of that. We're excited. We have a lot of opportunity and runway, particularly now with our focus on building agents for the industry.

Yeah. Our vision is broad. It is this industry cloud, and that means building these suites of applications that all work together. The core enterprise software, the core data, and business consulting, that all works together. The major shift that's happened over the last couple of years is now this agentic layer, which is super exciting, and I think this is a core part of Veeva's advantage, a structural advantage in having the foundation that we have in the core enterprise applications, but also the agentic labor that will work interoperably with the core applications. We're just in the early stages of building that out. We've announced a broad AI strategy, AI in all of our applications. We call that Veeva Vault AI.

You've probably heard us talk about something called Veeva Falcon, and Veeva Falcon is the agentic labor that actually does work, and that works very closely with the core application. I'm excited about continuing to expand out the industry cloud, these suites of applications, but also AI enabling the industry. We're in the early days, but super promising, just really over the last several months, seeing the excitement and progress with the product, but also excitement and demand from the customer side.

Yeah. That is right. We gave a 2030 revenue target about two years ago, and that is a $6 billion target. AI is largely incremental to that. When we gave that target, it was largely the existing products that we had and with maybe some additional growth of products, and primarily life sciences. Think about it as life sciences, core enterprise applications. Things like agents and Veeva Falcon would be incremental to that. Also, areas of our business, like in horizontal markets that we are entering, that is also incremental.

I alluded to our overall AI strategy, and I will reference that again because we think about monetization very differently in different parts of our AI strategy. There is Veeva Vault AI, and again, that is AI in the core Veeva Vault applications. It is in every Veeva Vault application there is across CRM and commercial content and regulatory quality, clinical safety. Every area will have Veeva Vault AI enabled in the application, and that is AI to help the users of the applications, help them go faster, make better decisions, summarize things faster. It is making users more efficient. In most cases, that will be more consumption-based, based on just token usage. As we increase adoption and utilization, we will expect to see additional monetization there. Then there is Veeva Falcon, and Veeva Falcon is the agentic labor. It is the layer that actually does the work.

In a sense, it replaces humans and users, and that's the user of the application, and we expect in those cases it to be more outcome based. So based on, let's say, number of documents processed, as an example. A specific business transaction I could also anticipate in Falcon we may have more enterprise license agreements. We may shift to a model that's more based on ELA. That is something we're still early days, we're working that out. Part of what we're doing with early adopters is establishing value for the products. Our main focus, maturing the products, establishing the right value proposition, and then we think the right licensing model will follow. We may end up having, in all likelihood, multiple licensing models based upon the specific use case, based upon the type of AI that a customer's using.

Yeah, we get questions all the time of what use cases we're looking to solve for with things like Falcon. The reality, as Paul mentioned, is that it's going to be very use case specific. There are certainly areas where we can help drive more efficiencies and potentially reduce some of the labor that's being done or used for some of these processes. But there's an element of getting things through the process faster, and that means getting to market faster. So there's both the cost arbitrage element, but there's also the ability to monetize and get to market faster. I think our focus in the interim with AI is really about getting AI out the door in the hands of customers delivering value. If we can deliver on that, we're confident in figuring out the licensing model, and the revenue should follow thereafter.