Earnings call transcript: Veeva Systems beats Q1 2025 expectations with strong revenue growth

Veeva Systems Inc. (VEEV) reported its first-quarter earnings for fiscal year 2025, surpassing analysts’ expectations with an earnings per share (EPS) of $2.24 against a forecast of $2.14. The company also reported revenue of $882.9 million, exceeding the anticipated $857.75 million. Following the announcement, Veeva’s stock saw a 1.02% increase in aftermarket trading, reflecting positive investor sentiment.

Veeva Systems demonstrated robust performance in Q1 2025, with both EPS and revenue surpassing expectations. The company’s strategic acquisitions and innovations in AI have bolstered its competitive position, particularly in the Commercial Cloud and R&D Cloud segments. Despite a slight dip in subscription margins due to increased service investments, Veeva’s overall trajectory remains positive.

• Market capitalization: $29.24 billion as of the latest data.

• P/E ratio: 32.4, with a PEG ratio of 1.24.

Veeva Systems’ actual EPS of $2.24 exceeded the forecast of $2.14 by 4.67%. The company also reported a revenue of $882.9 million, beating the forecasted $857.75 million by 2.93%. This marks a continuation of Veeva’s trend of outperforming market expectations.

Following the earnings announcement, Veeva’s stock rose by 1.02% in aftermarket trading, reaching $184.8. This positive movement reflects investor confidence in the company’s strong financial performance and strategic initiatives, despite a previous decline of 2.31% from its last close. Notably, the stock delivered a significant return of 12.76% over the past week, according to InvestingPro data. Investors seeking deeper insights can access comprehensive analysis through InvestingPro’s Pro Research Report, one of 1,400+ available reports that transform complex Wall Street data into clear, actionable intelligence. The platform offers additional ProTips—11 in total for VEEV—along with Fair Value estimates and expert analysis.

Veeva Systems is optimistic about its future prospects, with continued focus on AI-driven initiatives like Falcon. The company aims to capitalize on its deep expertise in life sciences to maintain its competitive edge. Future guidance remains strong, with anticipated EPS growth and revenue expansion in upcoming quarters.

CEO Peter Gassner highlighted the importance of Veeva’s strategic investments, stating, "Our focus on innovation and strategic acquisitions like Ostro positions us well for continued growth." He emphasized the potential of AI initiatives, noting, "Falcon represents a significant step forward in our commitment to agentic labor and operational efficiency."

During the earnings call, analysts inquired about the potential impact of AI initiatives on future revenue streams. Executives assured that while AI’s immediate financial contribution is limited, its strategic importance is significant, with expected long-term benefits.

Alexei Gogolev, Analyst, JPMorgan0: presentation, both of which are available on our website. With that, thank you for joining us, and I’ll turn the call over to Peter.

Alexei Gogolev, Analyst, JPMorgan8: Thank you, Gunnar, and welcome everyone to the call. We had a strong start to the year, delivering results ahead of our guidance. Total revenue in the quarter was $883 million, with non-GAAP operating income of $395 million. Our execution continues strong across the business, and it’s an exciting time for Veeva and for life sciences overall as we execute against a clear vision for industry AI. We’ll now open up the call to your questions.

Alexei Gogolev, Analyst, JPMorgan6: We will now begin the question and answer session. Please limit yourself to one question. If you would like to ask a question, please press star one to raise your hand. To withdraw your question, press star one again. We ask that you pick up your handset when asking a question to allow for optimum sound quality. If you are muted locally, please remember to unmute your device. Please stand by while we compile the Q&A roster. Your first question comes from the line of Joe Vruwink with Baird. Joe, your line is now open.

Alexei Gogolev, Analyst, JPMorgan4: Hi. Great. Thanks for taking my question this afternoon. I was hoping to go into a bit more detail on Veeva Falcon. This certainly seems more complex and consequential in scope. I think you call it disruptive in the remarks. Can you maybe expand on what this product is targeting and how you envision customers operating in drug development with maybe now this interplay between the Vault standard agents and Falcon?

Alexei Gogolev, Analyst, JPMorgan8: Hey, Joe. This is Peter. I’ll pick that one. Yeah, there’s a lot of things to unpack there. What you’re seeing is sort of the next chapter of Veeva in our industry cloud. We used to talk about applications, data, and consulting to make the industry more efficient and effective. Now we’re talking about software, AI, data, and consulting, right? Falcon specifically is at the agent layer, and that’s agentic labor. Fully replacing jobs that people used to do. People who used to do these jobs using our applications now will deliver the agentic labor to do that. It’s a big new area for Veeva. That is something we haven’t done before, and that’s why it’s disruptive. Those agents have to become users of our applications, which means our applications have to become very good in operating at a headless manner.

At the same time, we have agents inside of the Vault applications. That’s Vault AI inside of the applications. That’s where when people are actually using the application, because there’s definitely things that people still need to do in our applications, that’s where the AI agents can help them do it more efficiently. Much like you might use ChatGPT or Gemini at your work. Okay, that helps you do it more efficiently. For life sciences, because it’s kind of specific what they do and some of it is a bit standardized due to regulations and just efficiency concerns, some of those jobs or slices of people’s jobs, our agents will just do those for them. That’s never something that we set out to do when Veeva started. Why? Because there was not technology available. There was not probabilistic technology available to do this.

There was no AI that could do this. Now there is. That’s why you see Veeva leaning into this new market.

Alexei Gogolev, Analyst, JPMorgan6: Your next question comes from the line of Brian Peterson with Raymond James. Brian, your line is now open.

Brian Peterson, Analyst, Raymond James: Hi, you guys. Thanks for taking the question. Maybe just to follow up on that. As we think about pharma appetite for AI applications more broadly, I’m curious what areas you think they’d lean into first, and how we should think about the transition from traditional SaaS applications to AI and pharma. Peter, I’d love to just get your perspective on that. Thanks, guys.

Alexei Gogolev, Analyst, JPMorgan8: I would say it’s not that they’re thinking mainly about transition from applications into AI applications. What they’re really leaning into is this new technical architecture, we call it the MAP architecture, of models, agents, and applications. The applications that they get from Veeva, they’re looking for them to be more efficient, to have AI in there and help the users. What they really want to get to be is an agentic biopharma, so that agents can do a lot of the work. The humans can do the more higher value work. Of course, to do that, they leverage models like Anthropic or Gemini.

To put it in perspective, I don’t know the exact number I should off the top of my head, but let’s just say there’s 100 million documents collected from clinical research sites around the world every year, having to do with clinical trials. They have to be checked for quality, and they have to be sorted into the right places. That’s work that agents can do. It’s difficult, specific work, but we can make agents that are very specific on that. Agents that take in a bunch of free text via email or other channels and have to sort it out to see, is this a product complaint? If so, how to handle that and categorize that. No, this is a adverse event. This is an issue with a medicine making somebody potentially ill. Okay, well, what is that illness? Is that a headache or a throbbing headache?

How serious is that? Is that involved in a clinical trial? What drug is that involved with? We will make agents to do that and to those very standard things, and this is an area where I’m enthused because Veeva can lead. This is where, just like for cloud applications, you get the very specific industry-specific cloud applications could add tremendous value if you went to the last mile and solved the thing. In industry-specific agents, agentic labor, we may be able to go the last mile and make specific agents that just do the thing for life sciences, because we’ll go to that last mile and make it work. We may make agents that are better safety case processors and more reliable than humans. That’s a heck of a lot of work, but we have a structural advantage to do that because we’re deep in life sciences.

We have the consulting in life sciences, and we have the applications that those agents can use. It’s the same reason why Claude is getting very good at Claude Code, because they have the agent, the coding agent, and they have the model, and they have two layers. We don’t have a model we use, but we have applications and the agents. That is a structural advantage, and I do want to emphasize again the consulting, because a lot of this is about change management.

Alexei Gogolev, Analyst, JPMorgan6: Your next question comes from the line of Ken Wong with Oppenheimer. Ken, your line is now open.

Alexei Gogolev, Analyst, JPMorgan5: Brian, I wanted to touch on the R&D business real quick. It looks like a really strong start to Q1, potentially kind of outpacing the full-year guide by a couple of points. Yet only raised the full year by $5 million. Can you provide some co