Before we get started, I will read a quick disclaimer. During the course of today's presentations, we will make forward-looking statements, including statements regarding trends, our strategies, market size and opportunities, and the anticipated performance of our business, including guidance regarding future financial results. These forward-looking statements are based on management's current views and expectations and are subject to various risks and uncertainties. Actual results may differ materially. Please refer to the risk factors included in our most recent filing on Form 10-Q. Forward-looking statements made during today's presentations are being made as of today, November 5, 2026. If the presentations are replayed or viewed after today, the information presented may not contain current or accurate information. Veeva disclaims any obligation to update or revise any forward-looking statements. In the presentation, we will also discuss certain non-GAAP metrics that we believe aid in the understanding of our financial results.
A reconciliation to comparable GAAP metrics can be found in the appendix of today's presentation, which will be posted on our website. With that, I will turn it over to our founder and CEO, Peter Gassner.
Thanks, Gunnar, and welcome everyone to our Investor Day. I will start it out with our vision and values. This is our strategy on the slide. Start with our vision, which is what we are doing. We are building the industry cloud for life sciences. That is software, AI, data, and consulting to help the industry be more efficient and effective. We want to help our customers bring more of the right medicines and medical devices to patients around the world. We want to be essential to and appreciated by every company in life sciences. That is a high bar. It is what we are striving to do, and this is what energizes us every day. Our values are how we make decisions along the way.
The first is do the right thing. That is having the right honesty and integrity about actively knowing what the right thing is and doing it. Customer success has three parts.
That is for the people in the industry. They have to enjoy working with our people and our products. Second is for the companies in the industry. They have to get positive ROI out of our products and services. Third is the industry overall. Veeva has to be a positive force for the industry and help the industry grow. Employee success, that is for our team, has to be a place where our team can do their best work. Speed reminds us to do things quickly and correctly with high quality the first time. That way, we can retain that speed, that startup speed, even as we grow bigger. Finally, we are a public benefit corporation. That means we have a legal duty, yes, to our investors, but also to our customers, to our employees, and to society in general.
We have to balance the interests of all concerned, and that's a great thing to do here because what we're building is a long-term company that's providing a lot of value to the world and to our investors. Highlights you'll hear today. First, you'll hear about the golden age of life sciences, how the industry's really set to grow, and we'll grow along with that. You'll hear about our strong execution but also our innovation in new areas, for example, our AI solutions. We'll talk about industry AI specifically as a big opportunity, and yes, we'll also hear that we're on track for our $6 billion revenue run rate goal in calendar 2030. We are a strategic partner to the life sciences industry, a strategic technology partner, and it's a critical industry, a very resilient industry, and it's a big industry.
Well over $2 trillion, this industry, pharma and biotech, and it's growing at 6%, and I think it will continue to grow in the future as technology advances. It's a growing opportunity for Veeva as well. We view our opportunity as a $30 billion TAM, and that's up from $20 billion last year. That's largely because of AI. AI is a new technology. It's a new technology paradigm. It's probabilistic computing. It allows reasoning. It allows us to do things we haven't been able to do before, to help the industry in new ways with AI solutions that work with our applications and our data and our consulting, and that's why our TAM is growing by $10 billion, in fact, and we're really energized about that. How can we bring AI to bear to help the industry bring more of the right medicines to patients?
When I talk about the golden age of life sciences, I really break it down this way. First, AI is really enabling drug discovery, industry-specific models that know about biology. Of course, the frontier models are adding understanding of biology all the time into their models, so that's really, really going to help in the drug discovery area. Also, AI is empowering patients and doctors to be more informed about these very specific medicines and therapeutic areas, and how does it relate to them as a doctor or them as a patient? So doctors and patients getting more informed, that's going to mean more of the medicines and better medicines getting to patients. That means life sciences is going to create more value for the world, and I think the industry will grow along with that.
That's why I call this the golden age of life sciences, really enabled by AI in these multiple areas. In terms of our product offerings, our industry cloud for life sciences, we're organized around four clouds: the Development Cloud, Quality Cloud, Commercial Cloud, and Data Cloud. We have our business consulting that spans across all our offerings and helps our customers get value out of our products, because when you put our products in, you might need to change your business processes and measure what you're doing and do that change management. Then also Falcon, our agentic labor, and that runs across all of our different clouds. I'll talk a little bit about each area. But first, that's our product strategy, but what is our long-term strategy? What are we trying to do with these products? Where are we going?
Veeva's been here for almost 20 years, and we got a long runway ahead if you look at our next 20 years or so, our foreseeable future. We want to complete the industry cloud. A lot of these applications are young, they have to get more robust, and we have to keep them current all the time. That's job number one, complete that industry cloud, connect those applications together. We also want to connect the industry out to their customers, out to research sites, regulators, doctors, patients, health systems, contract manufacturers. The life sciences industry does not live in a silo. It's part of a connected workflow that's get out to all these other organizations. We view that as our job to do that, to enable that connectivity. Finally, deliver AI, industry-specific AI for the industry.
Not just create it, deliver it, connect it with our applications, connect it with our data, and help the customers get value, real value out of these applications, and make it sustainable, compliant, and validated over the long term. So it's delivering AI, not talking about exploring with AI, delivering AI over the long term. The whole Veeva team is very clear on this strategy for life sciences, these three things: complete the industry cloud, connect the industry, and deliver AI for the industry. Let's start with Development Cloud. This is a lot of different applications in here, organized in clinical operations, clinical data management, regulatory, and safety. We have some very mature applications, TMF, over 500 customers, some new applications, labeling, which we're just introducing, have very few, zero customers as of yet.
They're in all levels of maturity, but our goal is product excellence on each one. So we have dedicated product managers, dedicated strategy teams, developers, support people, consultants that know these areas, services people that know these areas. We like to get specific and solve these problems. We're providing this important technology blueprint for the industry here in Development Cloud, big undertaking that nobody else has really tried before. We started this roughly 15 years ago with this idea that we're going to make this, and now it's coming to fruition. Still has a long way to go, but we're really happy with the progress, and all built, of course, on our Veeva Vault Platform. If I dive down into one area, I want to talk about this Veeva Clinical Network. That's part of connecting the industry. This is connecting research sites to sponsors, to biopharma companies.
For research sites, we have our SiteVault suite of applications, and the research sites also have their electronic health record system. Sponsors, they're running clinical trials. They are clinical operation systems, our clinical data management systems, and we're providing the connectivity there. For example, in SiteVault, we have our brand-new eSource application, collecting the data from the EMR, from the directly entered data in the sites directly into our EDC. That's eSource, that eliminates paper, reduces costs, and increases speed. It takes a big partner like Veeva to connect these industries, research sites, and sponsors seamlessly. We're really excited about this. People have tried this for a long time. They haven't been able to do it, but why do I think we can do it?
One, we're attacking it comprehensively at the sites to automate their work, at the sponsors to automate their work, connecting the dots together. Also, we have the trust, both of the sites and the sponsors, because we've been doing this for a long time, and we've earned that trust. The industry wants this to happen because they know that this means they can run more clinical trials. Also, we have Veeva Study Suite, and this is really going to unlock a great opportunity in the CRO channel, because smaller biotechs, oftentimes, they may outsource the trial. They cannot operate the technology themselves, not just the technology, the whole business process of running a trial, so they may outsource this to a CRO.
What we're going to do with Study Suite is offer a very easy method for the CROs to offer the full suite of applications to a sponsor and run that trial with our technology, pass it through to the small biotech. This is an area we haven't focused on. We believe this is well over a billion-dollar opportunity just in the EDC, the eCOA, the RTSM area. This is actually a billion-dollar opportunity because almost half of the trials are outsourced, and that's an area we just hadn't focused on yet. So, we're really going to focus on this area, and the nice thing is that many, many of the CROs use our Clinical Operations Suite already, and our clinical data applications are integrated right into our Clinical Operations Suite, which fits right into the eTMF of the small sponsors.
This is really set up for success, and we're hiring a dedicated team to go after this. Couldn't be more excited. Also, this plays into our great partnership that we announced with IQVIA recently around their selecting our Clinical Operations Suite. So, really excited about what we can do here. It's time for Veeva to really deliver through this channel. All right, let's talk about Quality Cloud, a super exciting area. There's really three parts of Quality Cloud. Quality assurance, that's where we've been for a long time. Our flagship applications there are QualityDocs and QMS, and we have other applications like Training, Validation, and Batch Release. Then quality control, brand new area for us. This is LIMS, what's called QC LIMS. This is where you're testing the medicines as they're being manufactured, after they're manufactured, to make sure they meet the specifications.
That's a very serious thing, because these medicines, people are ingesting these medicines, they're injecting these medicines. They have to be correct. It's critical. It can be life and death. So, this LIMS is a very, very important application, a big new area. Then we've also just introduced and are working with a few early adopters, our environmental health and safety application as well. So in quality, all these applications are important. Some of them very mature, like QMS, some are very early, like LIMS, and, for example, environmental monitoring. That's where you're measuring in the manufacturing environment, the quality of the environment that you're manufacturing in. We haven't even released that one yet. It's a lot of runway to go here. But one thing I want to talk about is, this is a very significant opportunity. We have over 600 customers.
Today, it's over $600 million revenue run rate, and we have plenty of room to grow there, because we're just getting started with the LIMS. We want to modernize LIMS for companies of all sizes, put it in the cloud. Never been done before, right? I think we're going to have a better LIMS than anybody has seen before. Then we want to connect up in a Quality Network, the contract manufacturers to the biopharma companies. That's also never been done before. So that's what we call the Quality Network. That's what we're just introducing now, this idea of connecting the contract manufacturers, sometimes called CDMOs, they may run our QMS, they might run our LIMS, and connecting them to the biopharma. Oftentimes today, this is done by email. It might be done by phone call, attaching PDF documents. It's just not the right way to do it.
We think we can really automate this area, and this is a critical area for life sciences, because manufacturing is getting more complex all the time with these different types of medicines, more complex medicines, and it's getting more important to control your supply chain all the time. Which countries are you manufacturing in? You have to be very nimble, and quality is critical. You cannot keep manufacturing if you don't have records of maintaining your quality. It's an absolute must to have. AI is not changing this. It might make it more efficient, but the idea of testing your medicines is going to be here forever. All right, Commercial Cloud, actually the area where Veeva got started with our CRM application, but it's a lot more. Commercial Cloud is much more than CRM these days. Yes, we have our CRM suite with Agentic CRM.
We have Patient CRM there, which I'm really excited about. Ostro and Crossix, of course, for our PromoMats, content, and our medical suite. So again, a lot of applications all built on the Vault Platform that connect together. But let me just call out one thing, and that's our CRM product. That's where we really are moving the industry from our Veeva CRM, built on salesforce.com, to Vault CRM, built on our own platform. And I would say we're halfway through that. It's not a game. It's really serious for the industry. We're halfway through that adventure, and it's going well. We're winning this one. We have over 200 customers live on Vault CRM, including five out of the top 20 biopharmas. 14 out of the top 20 have selected us. So, it's really going well.
I'm really pleased with the execution of our product team, our services team, and our partners. And I think, yes, we will win back some of the customers that went a different way through being authentic and being their partner in other areas, and through delivering customer success and product excellence. We've always been in this for the long-term game, and I'm happy that we're at the halftime of this one. We're at the halfway mark. We won't finish all the migrations until the end of 2029, but I'm quite confident in where we're at and where we're going. All right, let's talk about our data products, Data Cloud. So we have three product lines in here, OpenData, Link, and Compass. They're all going quite well, and they're all connected together. OpenData, that's reference data about doctors, hospitals, healthcare systems, the affiliations.
Link, that's the deep data about healthcare scientific experts and key accounts, the deep, deep data about the doctors and the healthcare scientific experts that really matter. Compass, that's our performance data, patient, prescriber, and national data for the U.S. This is a marathon, this data network, and it's something that we're very proud of. It actually utilizes the underlying data that we source from many, many different places. That underlying data, which we call the Compass Data Network, powers Crossix and Compass and parts of Link and parts of OpenData. We're sort of really leveraging that underlying data network. This is a long, hard game, but we're really happy with the progress, and we're making good progress. I've talked about our products, but also let me talk about our services, because Veeva is not just a product company. We have very high-value services.
Almost 20% of our revenue comes from services. That's either from our consulting and our professional services. This is what knits it together for the customers. We're doing work for them because they don't quite have the staff to do it. Sometimes we're providing very specialized consulting skills that bring them a point of view that they don't have and bring them change management that they need. All different types of services. In business consulting, it's getting more strategic, and it's growing quite rapidly, and that's becoming even more important with AI, because AI does change your business processes. It has to change what your people do. Our tech-enabled services, we call those AI-enabled services now.
We're really enthusiastic about that because we can do more things at a fixed cost, and we can do things using AI more efficiently than we have before, so that makes our people more productive. Actually, I think what I see is that's going to enable more uptake of our applications because, all things considered, if our applications provide a certain unit of value, if you can implement them twice as fast at half the cost, it's more likely that you'll move to them. So we're really enthused about what we're doing, the value we're delivering both in consulting and services, and that's why you see it growing at Veeva because it's getting better. We're getting better in this area all the time. It's getting more valuable, and that's a great thing for our future.
Also, our people, our consultants, and our services are great funnelers of ideas and keepers of relationships. I just want everybody to know, yes, we are a technology company, but I cannot imagine Veeva without our consulting and our services. It wouldn't be Veeva. It's a very special part of Veeva, and our customers feel that. It makes us very, very durable. All right, now let's talk about AI, Veeva AI. What we're talking about here is industry AI for life sciences. When we look at our architecture for AI, it's really about Veeva. We have our Falcon agents, agentic labor, and then we have our Vault applications, and then we work with foundational models such as Anthropic, and they all work together. Our Falcon agents use the models for reasoning, they store the data, they run the business rules in the applications.
Our applications are meant to be able to be controlled by end users or by agents, and we want to be very good at controlling the models with our agents and teaching the models about our applications. This is the new enterprise architecture, the MAAP architecture. It is not just about applications anymore. You have got models, agents, and applications, and in our case, the agents are Falcon, the applications are Vault, and what we are creating is what we call a strong link between our agents and the applications. So our agents are pushing our applications to get better, and we are putting in features for agents, and our agents are learning about our applications and becoming better agents. So we are creating that very strong link, and our customers feel it.
Wow, the Veeva agents and the Veeva applications, they just fit together, and it just works for us." That is basically our strategy. So, two things we will sell. We sell Vault AI, and that is to help our users get better use out of our Veeva Vault applications, and we sell Falcon agentic labor. That is to do the work. So Vault AI helps you do the work. Falcon agents do the work for you. I will talk about Vault AI first. So this is where we are helping you do the work. So think of Vault AI, we are all familiar with ChatGPT, right?
That can answer a question about the world. It sounds like a very simple thing, but man, is it powerful, because many times, you are not searching for something, you actually want the answer, and that is what Vault AI is for the Veeva applications, the Veeva Vault applications.
First of all, it is directly in your Vault, no third-party bolt-on things, and it is secure, and it understands the security because there are very secure things, very sensitive things involved. You can use it to answer questions with our standard agents, custom agents that customers create themselves, and user agents that shortcuts and assistance that end users can create, because end users know how they do their work. They want little shortcuts and assistance to help them do their work. So Vault AI is available today, and it is getting better. It is getting better every release, and it is a long-term effort for us, and we really feel good about our strategy.
One thing we are doing is a very innovative pricing model for Vault AI. So what do customers want from AI, from industry-specific AI or enterprise AI? First, they want AI that works, for sure. It adds value.
They want it to be optional. They do not want to be forced into buying AI, sort of paying some kind of AI tax. They do not want that. If the AI is valuable, they should buy it. If it is not, they do not want to buy it. And the cost has to be predictable. And so that is what we are delivering in our Vault AI pricing. First, Vault AI is optional. Our applications will work great without AI. If you add AI, you will get more value, and we are committed to making them high value. And the pricing is very predictable. It is 10% of your Vault subscription fee for that Vault, and it is unlimited use.
I like that. We like that because we are going to be very efficient with tokens because it is in our best interest. And by the way, that is in the interest of the best of the world too.
You want to not use the foundation models where you don't have to. You want to use that in deterministic computing, pre-calculate things where you can so you can be faster and more efficient with the world's computing resources. I really want to thank our customers for working with us on this pricing model. We just introduced it a month or so ago, and I couldn't be more excited about it, and so are the customers. We've got this, and we're going to keep going on Vault AI and make it better every release. We're actually on a two-week release cycle for Vault AI. Our applications, because they're deterministic computing, have to be validated, et cetera. They're on like a four-month release cycle, all the testing and validation that goes into it. Vault AI is on a two-week release cycle. It's getting faster, very fast.
Yes, we are using AI to create Vault AI. Now, let's talk about Falcon, and this is a whole different thing. Agentic labor, that is not something we've done before. That's something we started doing this year in 2026, and we're making super rapid progress. It's a big, important initiative for Veeva, and I want to stress that it is different. The Falcon team is completely self-contained and reports directly to me. These are not applications, these are not data, this is not consulting. This is agentic labor. It's something we haven't done before, and of course, we couldn't have done it without the core underlying AI technologies. Falcon agents. First of all, I talked about that strong link with the Veeva applications. Now, the licensing model for Falcon agents is different. It is what you consider there's a license fee for the agent.
It doesn't have to do with the number of tokens. It's for that capability for that agent, and that agent is going to have a different price. Obviously, if that agent is working for a top 20 biopharma versus an emerging biotech, it's a different price, but it's one flat annual agent license fee, and we provide all the computing and the models. This is a completely new motion for Veeva. That's why it's a self-contained team. For example, the development cycle is different, right? Every two weeks, we're going on agents. The pre-sale cycle is different. We're not giving demos of these agents doing work. We're doing the work on the copy of the customer's production database, showing the customer the results of the work and the potential savings. It's a whole different pre-sales and support motion and validation motion.
What is the same is that product excellence is the goal, and we'll keep at these agents until they get better and better and better. We want these to be standard agents for the industry to take care of a lot of the standard work so that the people in the industry can work around these agents and do higher value things. Of course, this is early. We don't even have. We barely have some customers live in a few areas. I'll talk about that, but it's very, very early. I think this has potential for rapid adoption. If we get this right, this could be faster adoption than our applications. Why? There's no application to implement. There's no integrations. There's no data migrations.
This is, if it works, if it adds value, helps you reduce cost, you can start adopting it, and it will go pretty quick. It is a business sale very directly. This is not a technology or IT or an integration sale. It is not like that. Falcon agents are a totally new thing. I think they could go faster, but I do not want anybody to get too over their skis on this. We have to make these things work first. That is what is the same. We have to make this work for our early adopters. Our focus right now is totally not on the revenue for Falcon agents. The revenue will be there if we deliver these things, absolutely.
It is for customer success with our early adopters so that we can improve these agents and make them great. These are the areas that we are starting, clinical, regulatory, safety, and commercial.
We will get into quality as well. We are not doing that yet. Let me give a couple of examples of agents that we are further along on. One we are probably furthest along on is our MLR agent in commercial. Part of that came through our acquisition, a small acquisition earlier this year. We already have customers live, early adopters live, and that is where we are doing the MLR process, medical, legal, and regulatory review in AI so that humans can do just the review and final approval, but not all the work that goes into it. Then clinical intake. That is where there is millions of documents exchanged between research sites and biopharma in the process of running clinical trials.
They all have to be collected, they have to be organized in the right place, tagged with all the right metadata so that they can be put in the right place in the trial master file and checked for quality. That is a tremendous effort, and it is hard. Clinical intake is an agent that will do that work, intake those documents, figure out what they are, file them in the right place, tag them with the right metadata, check them for quality, and let a human know if they find an issue. We are working with early adopters there as well and making great progress. The pipeline for these agents is actually building. I am really happy about where we are, but we got to get customers live, we got to sign some larger deals, and we got to get going.
In orange here, I put the agents that we are developing, and some of them, as I mentioned, we have early customers live on. There are also many more we are considering, and I put those in black here. There will be many more to come. This is a whole new sprout for Veeva, Falcon agents, agentic labor. In some ways, it feels to me like, okay, when in 2011, we were starting Veeva Vault, our own applications on our own platform, this is a whole new thing for life sciences. It is our next step for the industry cloud.
Now, what we are trying to do here, we often talk about, we are trying to simplify the industry, standardize it, and connect it out with the regulators, the sites, the patients, the doctor. We need to enable customer success for all of our customers, whether a very large company or an emerging biotech.
The way we do that is through product excellence and delivering. This is what we're trying to do. We work hard at it every day. Emerging biotechs, boy, they are critical for the industry. There are hundreds of them, and they are where a lot of the innovation is done because they move fast, they have an idea, they run these clinical trials. Some of them make it, some of them don't. Some of them go out of business, some of them get bought, some of them grow up to be huge companies, but they're critical, critical for the industry, for the health of the industry, and for getting better medicines to patients. Now, about three years ago, we started a new product line, which is Veeva Basics. This has turned out to be a real winner for Veeva.
These are based on our core Veeva Vault applications, but they're simplified and standardized, and we deliver the complete process for biotechs in a validated manner with no implementation needed. I often explain to people that when a customer uses Veeva Basics, they're not only using our products, they're using our industry standard process. There is no configuration, no implementation. This is just amazing for small biotechs, and we have almost 200 biotechs now using it. Last week, we had on Brian Radecki. He's the CEO of Rapa Therapeutics, and he joined our company call, which is an internal company call where we often have customers, we might have a patient talk about the impact we're having. Brian talked to us, and it was a great reminder of, what are we doing? What is the impact are we doing, and who are we doing it for?
We thought it was such a great reminder to us that we wanted to share it with you, our investors, so that you know what we're doing. We'll show now Nitsa and Brian.
We have our first ever Veeva Basics customer on the company call today. I'm thrilled to introduce Brian Radecki, Co-Founder and CEO of Rapa Therapeutics. In 2017, starting right from his kitchen table, Brian co-founded Rapa with Dr. Dan Fowler, based on the research Dr. Fowler had been doing for the last 30 years at NIH on T-cell therapies. They're now in phase II clinical trials with some very promising treatments for cancer and ALS. Their approach uses the natural power of the immune system to reprogram itself. They take cells out of patients, reprogram them without genetic engineering, and put them back into the patient. Pretty advanced stuff that's actually having quite a big impact, and we'll hear from Brian on that in a minute.
They're a team of just 20 people doing really big things, not only in the science, but operationally, including establishing a full-scale R&D and manufacturing operation all themselves. You'd think with such remarkable execution, Brian really knew the ropes in biotech and pharma. Actually, when he started Rapa as CEO, he had no experience in biotech or pharma. His last role had been at the real estate and information technology firm, CoStar Group. He'd spent 30 years in that industry. Also, what a great lesson on what's possible in life. Brian, first, if you could tell us a little bit about ALS. We hear about it in passing, but maybe you really don't deeply understand just how devastating a disease it is and what the prognosis looks like.
If you could talk a bit about that and how it's going with your novel therapies for cancer and ALS.
Yes. Nice to meet everybody, I guess, virtually. ALS, going back to how the company was founded, I spent 25 years in commercial real estate. I met Dr. Fowler through a friend of mine. He was at NIH for 30 years working on various cell therapies in Building 10, which is their most experimental place. After a few years, we decided to spin his lab out into Rapa Therapeutics. We use rapamycin as part of the epigenetically reprogramming process, hence the name Rapa Therapeutics. We started it as a cancer company, which we can talk about in a few minutes. Shortly thereafter, my best friend was diagnosed with ALS. ALS is a disease that there is no blood test for it. It's a process of elimination. They thought he had a slipped disc in his back. They were talking about surgery.
Through that process of going through with him, it took two or three years before they could diagnose him, and by the time they did, he was pretty much end stage. At that point, even though we didn't have a product for him, we decided to add ALS to the cancer program. They're two separate products, which we probably won't get into today. We've been running phase I, phase II, we just finished, and we're now working on a phase III trial with FDA that we will get started on next year. The phase II trial has a lot of support. We actually got $33 million from NIH to help fund that. We've applied, and we're hoping that we'll make the next round when it comes in December.
But we've seen some amazing results where patients with a less than 50% slow vital breathing capacity, that was dropping at 3% a month, have stabilized, and some have even increased. Now we've got some of these study patients out two to three years. So some pretty spectacular results for an industry that I think it's the most devastating disease because most patients live three to five years, but it takes three or four years for them to get diagnosed, and they just don't have enough time with their family, right? There's only two real drugs approved that have been around for like 50 years, and they, I think, add a couple weeks to the patients. Recently, there's been some other genetic things that people have worked on, but they're in small populations of like 100 people and stuff like that.
So that's how we got into ALS and a little bit about the ALS disease. As far as cancer goes, it's a much more simple story in that Dr. Fowler was working on 15 different types of cancers at NIH over 30 years. That's kind of how the company got started. For me personally, when I met him, my father died of cancer. Almost 50% of my family members, including brothers, sisters, aunts, uncles, have all passed away from cancer. So, something where I retired from CoStar after 25 years, and I was sitting on a couple public company boards and doing different things. When I met Dr. Fowler, all of a sudden I was like, "Okay, this is something I really want to do. I'm very interested in this, especially with my family history." So, that's kind of how the company got started.
We have two products, one for cancer and one for ALS, and we epigenetically reprogram them in a different way.
It's incredibly humble to say it's a simple story on cancer for you all, because there are patients now on your treatment that are in complete remission. They were, I think, at end-stage disease, stage 4, with little hope.
Yes. All the phase I and II studies, you start at the end of the line. Yes, actually our very first patient we treated with cancer, again, so they are all end stage, and that patient went into a complete remission fairly shortly. Of course, we have had some really good results, 60% response rate in patients out now four or five years since that initial phase I study. So, we did get what they called a RMAT designation, Regenerative Medicine Advanced Therapy designation. It is the highest designation you can get from FDA for a cell therapy. So again, we are working with them on that program for basically a confirmatory study, which will probably start more like later next year. So, we will probably start the ALS study in the spring, and we will probably start that one in the fall. That one is maybe six months behind.
Yeah. Some pretty ambitious things you are tackling here. You were on this not only audacious path, but the very risky path of a small biotech. You were one of the first. There is some debate if you were the first or the fourth, I think, within the Veeva Basics team. But you were at least one of the first five Veeva Basics customers, and you use it in clinical, quality, and regulatory. Why take the risk at the time on an unproven product?
Well, I had actually a connection with one of the board members at Veeva from another board, so I had known about Veeva for a while. Coming from CoStar, it is the operating system for commercial real estate, and now actually residential real estate. So I am very familiar with SaaS companies. Veeva was one that I had seen and really admired, honestly, what you guys have done. But when I started the small biotech, there was no way we could afford full Veeva, right? One, we could not afford it from a cost standpoint, and then two, just an implementation standpoint. So I had been having conversations with the one board member, and somehow or another, they got to Jim Thai, and they were like, "Hey, we are thinking about this Veeva Basics." At that point, everything we did is in paper.
We had these huge binders, everything from clinical to regulatory. Some of the original regulatory stuff was faxes to FDA that came from NIH. I at least got rid of the fax when I took it over. But we have got this huge storage space with all these binders, and everything was basically paper-based. So, when Jim talked about, "Hey, would you guys want to be a beta tester?" He told me I was number 1, so I am going to go with number 1. But he is like, "Do you want to be a beta tester on this?" I was like, "Yes." For a small biotech, the price was right. There was not an implementation fee. I have seen and done through my career many implementations where the costs just get out of hand, so it is somewhat sticker shock. So, I was pretty leery of that.
So, that is why we took the risk on Veeva Basics. Honestly, I am not just saying this because I am on here, but it could not have gone smoother. It really could not have gone smoother. I was actually shocked at how seamless it was, and did not cost us anything to implement, and completely just changed the way we do business, and much more efficiently. Again, at 20 people and you are doing your own manufacturing, you would rather put that money into R&D or manufacturing versus a bunch of people pushing paper.
There are many, many companies who have gone since. There are now nearly 200 Veeva Basics customers, and we have you in part to thank actually for Basics Publishing. You were pushing for it so you could do your publishing in-house and speed your regulatory submissions. Why take that on as well?
Yeah. I am a big proponent of, if you have a piece of software that can do multiple things, I would rather have one piece of software, especially a quality software like Veeva, than three separate systems or three separate paper-based things. As far as the filings go, again, we started with faxes, believe it or not. We found some little piece of software, I do not know, it was probably built in the '80s, and we were using that as our gateway. We actually had gotten a letter from the company. They had been bought out several times, and they were small, and they said, "Hey, we are discontinuing this. You are not even going to be able to use it." We could have just outsourced it, but we tend to do things internally. We do our own internal manufacturing, which is pretty rare for T-cell therapy.
And so yeah, I pushed Jim, and I was like, "Listen, this would be super important to us." I think, again, I think whether we were the beta tester or number one, we were one of the first, I think, to publish on that. I do not know, I think we have done 30 or 40 filings on it now. Again, it has just made everything much more efficient for my team. I only have one person in regulatory, so to do 40 submissions, it is a lot. We actually have one happening today. So, it has been great. Again, Jim, I think, said, "Oh, we will have it next year." I was like, "Yeah, sure you will." You guys delivered it exactly when he said. Again, that was super impressive to me.
As a company, I know that's got to be very hard, multi-billion dollar revenue company with a lot of competing things for resources. Was pretty amazing. You guys actually both on the Basics, and then when you added the filings, it actually happened when you said it was. That honestly, kudos to you guys for being able to do that, the whole company.
Well, it's pretty remarkable. You have a 20-person team, no IT people, and as you mentioned, one person in regulatory. How do you think Basics has played a role as you've progressed?
Yeah. Ironically enough, I think I've told you this story, right after we basically implemented Veeva Basics, we've been running our trials for the last seven years, I got an email and a phone call saying, "Hey, you guys are getting audited tomorrow morning." I'm not from biotech originally, spending 30 years in commercial real estate, and I had been audited by SEC and DOJ and other things, but I had no idea what to expect. This guy shows up in full military garb. He's showing us his ID. He's making me sign papers. I'm trying to crack jokes, and he had wanted nothing to do with it. He came in there, and of course, he had his list of things.
Honestly, if we weren't on Veeva at that point, we probably wouldn't have been able to get through the audit to basically try to go storage and find paperwork and other things. The punchline is that we got through the audit with some feedback, but no significant findings. Definitely, I just don't know that it even would have been possible if we weren't on Veeva. So, the timing couldn't have been better.
I appreciate what you said earlier about the amount of trust. When you and I spoke, you talked about how that's been earned over time, that you all can focus on the science because you know Veeva's got our back. I love that. On prior calls, we've had another customer talk about how we're able to move together at the speed of trust. It would be great to know what more you think we can do to help Rapa Therapeutics and other biotechs.
Yeah. I think trust is so important, right? I knew it was a good company, but when I first met Jim and he's like, "Oh, we'll deliver this Basics by X, and you're going to be the beta tester," I was like, "Yeah, sure we will. Sure the implementation will go well, and sure you'll give us filings, right, a year from now." You guys built that trust, right? Again, I can't imagine how fast you guys had to work to get those products out, especially the original Basics version, as quickly as you did. So, I think you guys have, at least in my view, I sort of trusted you because I got good references and everything else, but you guys really have earned that trust.
I think for small biotechs, again, if you guys can do what you did for us to whatever it is, 200, 500,000 other companies, the hope is that these companies eventually, we're hoping now we're doing two confirmatory trials, that we will then get an approved product and hopefully grow into a nice small company. Then you may get acquired, and again, having Veeva Basics really helps through that whole process. The only other last parting comment I'd have, and I said this to you, is that I wish you guys would continue to expand. There's other areas that I use Excel or we use different things in. So, I think Basics was a good start. The filings is awesome. I'd love to see you guys continue to expand because I would be a client.
I would rather have one piece of software that has earned my trust and has worked pretty much flawlessly since we've had it, and not just marketing. It really has.
Yeah.
I would rather have everything in that system. Please keep expanding the product sets.
I so appreciate that, and I really, really appreciate how it gives such important meaning to our values. Of course, the two that come to mind are customer success and speed. For us, speed is with quality. What that means to not only you all, but to the work that you are doing for patients who would otherwise have just months or a few years to live. I so appreciate all you are doing. I so appreciate that you have brought your talents to biotech, and thank you very much for your time.
Thank you, and thank everybody for your hard work, honestly. I know from my experience that it takes a whole company, it takes every person at that company, sometimes working till late in the night or on weekends to make those deadlines and do those things. What I would say is that you guys really are making a difference. You are making a difference with me, which then helps us make a difference with patients and people that are struggling. Please keep up the hard work and keep expanding. We love it.
All right, as I close here about the life sciences area, it is important to remember our long-term strategy. We are trying to complete this industry cloud, all the applications, get them mature, get them current, get them up to leadership, and keep them there, keep them current. Connect the industry out to the external partners they need, and deliver industry-specific AI for the industry. Not just create it, deliver it with value, validated, fitting in with our applications. All right, now we will turn the page quickly over to Aspen. That is another brand new shoot of growth for Veeva outside of life sciences. Aspen, this is cross-industry enterprise CRM application. A whole new thing in Veeva, a whole new separate group in Veeva, very isolated. Isolated might sound bad. They are incubated. They are a startup inside Veeva.
They're not distracting anybody from what we're doing in life sciences, and they're not distracted by anything we're doing in life sciences. That's also what I love about Veeva. We have different groups doing different things, all with common values and ways of working. I'm really excited about Aspen. I will tell you a bit about it. First, what are we doing? It's a better CRM platform and a better CRM application. It's both a platform and an application. So what do I mean by that? Better platform than what you'll see out there in the industry these days. It's not a version 1 platform. It's not like a version 2 platform.
So better core ways of the way it stores data, the types of APIs it has, the way development is done on the application, the performance of the response, the way you search and find things, the way you extend things, the way you extend it with business rules. All of that core platform stuff has been rethought from the ground up. I know a bit about platforms. I've built a few. People saw Salesforce, Veeva Vault, put a lot of my energy into it, but really assembled a great team around this. So a great platform and a great enterprise CRM application. What does that mean? It means the data model is really well thought out between contacts, accounts, opportunities, quotes, cases. How does that all fit together so that it works for a bank and it works for a manufacturer?
It works for people-centric businesses, it works for company-centric businesses. So a really thought out, complete application that handles things like multi-country and specific business processes that should work for a 10-person company and 100,000-person company with 50 divisions. That's what we're trying to do. It's a big goal. If we accomplish that, it'll be faster to implement, faster to get value, cheaper to implement, cheaper to operate, cheaper to get there, and more friendly, a more friendly application for the users. Because a lot of CRM systems today, people don't like having to use them. They have to use them, but they don't like it. Our goal is that they'll really like this. I think we can do it. We'll see if we can. It's early. So more friendly. Definitely built for AI during the implementation, doing the operation.
AI should keep most of your data clean, and it should enter most of your data, not the users having to do that. So AI in all areas of the application. Right now, though, grand plans for Aspen. We got a small, tight team working on it, working with a few early customers. Of course, we're going to use it internally next year. And by the way, Veeva's not a small company, right? It's a big company, lots of people, so we'll have heavy demands too. But that's what we're focused on. We're focused on our early adopters. It's not about the sales or the revenue. And we believe we have a chance for greatness in Aspen, and the way to do that is create a great product, work with our early adopters to refine it, get them live and happy, and go from there.
Aspen works on 90-day plans. It's a startup, and we're all really excited about it. All right, we'll talk about capital allocation briefly. Most of our capital is going to these two areas of product excellence and long-term growth. When we make applications, we get them up to the or data products for that matter, or AI agents. We want to get them all up to the leadership level, and we want to maintain them there. Continuous investment in these products, and of course, starting new products for our growth. That's where most of our capital allocation goes. It goes to our people, our great people who are creating and supporting and doing services around these products. We do have a very disciplined approach to acquisitions. You'll notice our acquisitions mostly work and create high value. I like that. We like that.
That's good for the entrepreneurs that we bring into Veeva. That's good for our customers, and that's good for Veeva. It keeps us fresh. We do that in a disciplined way. We look for culture fit, we look for business model fit, and we need to have an organized plan on day one about what we're doing and how we're doing it. Really happy with that. You saw two of them this year, with Copli and Ostro, and they're both going well. There'll be more in the future. They might be small, they might be big, but one thing they will be is disciplined, because I just think that's the right way to do it. It's not a land grab or a revenue grab. Disciplined acquisition to add value. And of course, we will continue our share repurchase program.
Brian will talk more about that at the right time. That's another way we allocate capital. All right, with that, let me pass it over to Brian Van Wagener, our CFO, and he'll talk with you more about our financials. Thank you.
Thanks, Peter. First, I want to give a quick update on Q3, which we just wrapped up. We're continuing to execute well and expect to meet or exceed our prior guidance on all metrics. We'll share full Q3 results and our updated fiscal 2027 guidance on our earnings call December 3rd. Now let's jump in. Today, I'll share more detail on our long-term opportunity for growth, on the progress towards our 2030 goals, and on our continued strong profitability. 97% of our revenue today comes from the life sciences industry, about 70% from the top 20 and enterprise customers. All of these large companies are customers of at least one Veeva product today, and that gives us a unique ability to partner with the industry as a whole, including the biopharma companies, the CROs, the sites, the patients, and the regulators, the whole industry. It's a large and growing opportunity.
We now put our TAM at $30 billion, up $10 billion from last year, driven by the opportunity we see in industry AI. At 12% penetrated, we have a long runway for growth ahead in life sciences. Just under half our TAM is Development Cloud, that is clinical, regulatory, and Safety. About 20% is Quality, and the remaining 35% is Commercial. Our execution against that opportunity has been strong. All three of these areas are growing and executing really well. Commercial solutions continues to grow, but it will become a slightly smaller percentage of revenue over time as other areas grow faster. Quality Cloud is growing really nicely, and we expect it to increase to about 20% of revenue by 2030. Development Cloud is large and also growing fast. We expect it to reach about 40% of revenue by 2030, driven by growth in clinical and Safety.
Historically, we have grouped our financial reporting into two areas, commercial solutions and R&D and quality solutions. Given the growth that we see in our Quality area, in our reporting, we will start breaking this Quality Cloud out separate from Development Cloud, and we will make that change starting with our fiscal 2028 results. The breadth and depth of our product portfolio is unique. The three areas we just discussed span 15 suites and about 60 products. Our goal is to be the market leader in each of those products over time, but also for them to work exceptionally well together. While we predominantly serve one industry, it is best to think of our products as a portfolio. They are sold to a range of buyers that face different market dynamics, and so that insulates them from short-term pressure in any one area.
Of our 60-product portfolio, the ones you see here are some of our major applications and data products. That means they are large markets and generally at the center of a critical business process. It is not all of our products. It does not include add-ons and our AI products, for example, but it is many of the big application and data products. The ones on the left, those are leaders today. They are the clear leader in their category. They generally have more than 50% penetration, and so while they are still growing, it is at a lower rate as they mature. These markets can also grow over time, and we have seen that over the last few years in places like eTMF, CRM, and Vault Content. The other products here, those are growth products, and they are in various stages of maturity.
The ones more in the middle, those are in their scaling phase. These are products that are both growing quickly and have a lot of room to grow, so that is things like Crossix, Link, Safety, EDC, Compass, and RTSM. On the right, these are early growth products where we are still very early in the journey. Some may ramp quickly and some may take more time, but these are pretty early on the path. Collectively, these major growth products are much larger than the leader products on the left, so they are growing fast and they have got a lot of headroom to keep growing. In our product portfolio, leader products cement those strong customer relationships, they form a stable foundation of revenue, and they create the opportunity for add-on products around them. The growth products, those are what really fuel our long-term growth.
Earlier, I mentioned that AI is increasing our TAM. That means new revenue potential and also more differentiation for Veeva in the market. We think Veeva will do for industry AI what we've done with industry applications and data. Our deep focus, knowledge, and relationships let us approach AI in a way that's highly impactful. Vault AI, that's agents inside Vault that help you do the work, is making our applications more valuable and is a new revenue opportunity. It's available to customers, and it's priced at a fixed 10% of the Vault. Then there's Copli. That is a big new market in agentic labor. It's hard to believe it's only about six months old, but we're building it across many of our major areas, and we're really pleased with the speed and early progress. The job there is to get to product excellence in the initial agents.
Once we do that, we think we can scale really quickly because the implementation can be much faster than it is in applications. There might be other areas also that don't neatly fit into this model. Ostro, for example, is also an AI product that we're really excited about. You heard about the MAAP architecture earlier. Our AI products both leverage and deepen our structural advantage. The industry really benefits from having a partner keeping their applications, agents, and data coordinated over time. Switching to services. Our guidance calls for services to be above $600 million revenue in fiscal 2027, and we also continue to manage it for profitability with non-GAAP margins typically above 25%. This year, we've seen particularly strong growth in business consulting.
It's about 20% of our services business, but it's growing really fast, and we expect it to be the main driver of growth out through 2030. The majority of our services revenue today, about 80%, is what we call professional services. So that's things like implementation, configuration, and managed services, and it's grown really well this year too. I'd note that a portion of professional services growth this year is the one-time effect of CRM migrations ramping up. That revenue is going to be stable for the next year or two, but we do expect it to taper off as we get closer to 2029. Customers use our services when they're getting value from them, so growth in services really means more value and more customer success being delivered.
Overall, we're seeing great execution across both subscription and services as we work towards our long-term goal of $6 billion revenue run rate by calendar year 2030, which is roughly fiscal 2031. We've got a very strong track record of setting and achieving these long-term goals, having first set goals of $1 billion by 2020, $3 billion by calendar 2025, and now $6 billion revenue run rate by calendar 2030. We ended Q2 at roughly a $3.7 billion revenue run rate, and we are on track for that 2030 goal. As part of our 2030 goals, we're also continuing to stay focused on both growth and profitability, which is really a core part of Veeva's DNA.
Our margin floor is 35%, but it is best to think of that as a floor, not a target, and we will continue to provide margin guidance annually and to manage for both growth and profitability. You can see that we have consistently grown profits over the past five years. Our fiscal 2027 guidance calls for non-GAAP operating income of $1.64 billion, a bit more than double five years ago, which implies margins of about 44%, roughly flat year over year. As you think about what influences our margins, there are really three main factors. The first is product development, our pace and level of investment in building and innovating.
AI is giving us new ways to improve that productivity internally, which you can see in the speed of development of products like Falcon and Vault AI. The second is product adoption, how quickly customers select, deploy, and ramp on Veeva.
Faster product adoption creates operating leverage. It is about if we have product excellence and can activate an effective sales process and reference selling. The third is keeping lean teams executing well, and we work really hard to keep our teams lean because that drives speed, focus, and accountability. Lean teams is not about margins, it is about the execution, and then the execution creates the great margins. Our spending is not driven by short-term margin targets, but by a long-term focus on product excellence and customer success, and it is that long-term focus that sustained our healthy margins over time. With that long-term focus, product is where we invest the most. About two-thirds of our subscription-related spend is in the product, and that has been pretty consistent over time.
We think that is the right way to invest given our focus on industry partnership, and we run very efficient sales, marketing, and supporting functions, keeping with lean teams. The path ahead for Veeva remains bright. Our team is executing well against a long runway for growth. We are on track for our 2030 goals, and we continue to deliver strong profitability. Now we will take a break, and then we will turn to Paul to get a customer's perspective.
Welcome back, everyone. I have the great pleasure of introducing our fireside chat guest customer speaker, Joanne Byrne. Joanne is the head of global regulatory operations at Roche, and in that role, she has responsibility for global regulatory data, digital transformation, and submission excellence across the entire Roche product life cycle. Joanne is leading the charge at Roche to bring together modern enterprise technology and AI to help plan for the future of regulatory. Joanne, thanks for joining us, and welcome.
Thank you very much, and thanks for having me.
As you know, a top priority for the industry is getting medicines to patients faster. But regulatory can be complex, it can be time-consuming. What do you believe fundamentally needs to change in regulatory to accelerate the drug approval process?
Yeah. I think, quite often, I have to be honest, people look to regulatory and think, "It's slow, it's conservative." But in all honesty, we have to be able to meet the regulations, and we're also dealing with regulators across the globe who have differing levels of maturity as well. If I look at how we're working today and have been working, we're still in very much a document-centric world. It takes us quite a lot of time to put a submission together. Then that whole review approval process is elongated because we have a tendency, the way we need to work with regulators is we'll dispatch in waves. For some of the smaller agencies, they will be looking to approvals at the larger agencies before they're going to review and approve a submission.
In today's world, it takes quite a lot of time from the conception of a change, say it's a technical change or a new indication, really being able to generate the package that will support that submission and then getting approval globally for that. So that's where we are today. Where do we want to be in the future, and where do we think we'll be in the future? We will absolutely move from this document-centric world where we are today and into a far more data-driven future. With new regulations such as ICH M16, M4Q(R2), IDMP, this is looking at and really pushing how we structure content and data in a way that will make it much easier to put the submission together, but also for the regulators to review as well and track the data.
From a company point of view, like everyone, we're looking to accelerate. Our whole aim is to be able to get medicines to patients faster.
So you've talked about shifts, such as regulatory needing to be more data-driven and overall much faster. What does that mean for your enterprise application and your overall AI strategy?
I mean, I have to say, we need to ensure our core competencies and our enterprise systems are fit for purpose for us, first off. We're coming to the end of a multi-year project and program where we've implemented a lot of the Veeva Vaults along with other solutions. We now have everybody working in the same systems. What we're wanting to do in the future is ensure full connectivity of those Vaults. We want data flowing through the Vaults and have more data-driven processes in there. In addition, I think what we've got to remember, even before we look at digital solutions like AI, we shouldn't underestimate what it takes to keep these core competencies up to date and fit for purpose for us. The product, your product, the Veeva product changes constantly. Regulations are constantly changing, and our ways of working are constantly changing.
From my point of view, I'm looking at how do I ensure the sustainment and optimization of our core processes and systems is adequate to meet our future needs. In addition, on top of that, once you've got the background, when you've got the backbone to your processes, we really need to ensure we've got accessibility to data and correct data, and then we can utilize definitely AI, agentic AI, and we're all experimenting in this area at the moment. I think this can give us a lot of benefit in streamlining and driving efficiencies in how we're working. We have a big AI program, but I would say the basics come first. We've got to continue to invest in our core competencies and our core systems and our data layer, and then we can get the most out of AI.
You've highlighted the importance of applications and their ability to evolve as foundational to AI. What is it then that you see as the potential for agents in regulatory?
Our initial focus is very much on ways of working and driving efficiency. I have to say, currently today and using some of the apps that we have, it's very time-consuming and burdensome for users. We want to very much improve the user experience in our systems and tools. We want to streamline and reduce the number of clicks people need to do, and with that, then we can drive consistency and quality of data. I would dearly love to get rid of or remove all free text fields, because once you have a free text field, then you create issues with data entry and consistency there. Initially, over the next year or two, we're looking at how to improve the core processes, our user experience, and our data quality. But longer term, we're also looking at getting the most out of our data.
How do we use data to provide insights on our regulatory strategies and our risk profiles? How do we really streamline and accelerate, as I said previously, our submission generation? We have a number of experiments ongoing on that side as well. But initially, it's very much around driving that efficiency and quality of data.
The potential for agents to streamline the work and increase speed is clear. Given that, can you talk about your decision to be an early adopter of Veeva Falcon?
As I said to you, we've got lots of experiments ongoing, and have had for some time. When I look at how we have approached this, we're in a very revolutionary time. This is a very different way of working, and we've made some mistakes, but also technology is moving really fast. We want to make sure we get the best out of the solutions we have. When you look at where a lot of our data and our documents live, it's in the Veeva Vaults. For us, we are very curious, and one of the reasons we wanted to be an early adopter is, could Veeva bring an innovation engine that is fast, that keeps up with the technology changes, but also is seamlessly integrated into the Vaults and we don't have lots of add-ons? Then we simplify our system landscape.
That's one of the reasons we really decided to invest. I have to say, what really helped as well, the first use case around health authority questions and answers, this process currently within the Veeva RIM Vault is very, very manual and burdensome. If we can streamline this and make it a lot more efficient, this will help us with making sure then we can connect to that data in the future.
One final question, and for this one, we'll take a step back and think about life sciences overall. What do you see as the opportunity for Veeva to lead the market with industry AI?
We are kind of still early, but I think Veeva have come to the table with their AI a little bit later. We've had lots of discussions with Veeva over the last couple of years. But I do think they've got a great opportunity, because a lot of us, a lot of the pharma companies have really invested in the Veeva Vaults, in the Veeva apps, and we have everything integrated there. This is the opportunity. If Veeva can really deliver AI and agentic AI into the processes and streamline how we're working, and make things more efficient, more cost-effective, then I do think there's a great opportunity here for them to take this on.
Well said, Joanne, and we are certainly equally excited about that opportunity with industry AI. I want to thank you once again. Thanks for your partnership. Thanks so much for joining us today. With that, I will turn it back over to you, Peter.
Thank you very much, and to you as well.
All right, the highlights you have seen, we talked about the golden age of life sciences. That is good for the world, good for our customers, and good for Veeva. It is powered by AI. We have strong execution in what we are doing. We get things done at Veeva, right? Make great products, good sales teams, services, et cetera. We are innovating in new areas. Especially, we think industry AI is a big opportunity. We have raised our TAM by $10 billion, and we are on track for our $6 billion revenue run rate in calendar 2030.
Thank you, Peter. Thank you to everyone for joining the webcast again for our 2026 Investor Day. We will now move into the Q&A session. On for Q&A will be Peter, Brian, and Paul. Thanks. Welcome back, guys. As a reminder, if you would like to ask a question, please raise your hand through the Zoom tool. To kick things off, we are going to start with Joe Vruwink at Baird.
Great. Can you guys hear me?
Yeah.
Okay. Thanks very much for the time today. Peter, all the way back at the start of your comments, you talked about how AI is going to enable some things that weren't possible in the past. The question is, as you start to think about your customers operating differently, how does that change the opportunity where Veeva can be helpful? On my mind, there's so much attention around discovery and experimentation going up because of AI. Does that actually shift what you can do, where you can be helpful in areas like Validation or event monitoring? Maybe more of Veeva ends up in the Quality and Safety areas for your customers over time. Just how does AI change the mix of Veeva, if you will?
Well, I would say AI speeds up this area of drug discovery, right? Because you're getting biology in the model, so that's a good thing. On the other side of it, when the patient and the doctor, when the patient starts out to say, "I'm not feeling well. I think something's wrong. I might need to see a doctor," that type of thing, and then the patient starts to educate themself, AI is going to help a lot there, and it's going to help the doctor and the patient get together. So, make the drug faster, get the drug to the patient that's ill faster. But in the middle, there's the development side, development and manufacturing of the drug. That process I don't think will change.
It's just that that process was done mostly by humans before, and now it's going to be done by humans and agents. That's really the opportunity I see, that we can have agents doing some of that work, and that's just going to make things more efficient. That plays into our strengths because we have to make our agents work well for humans, but also agents. So that's one thing. It's always like that, Joe. You always got to keep going, keep more modern. Then we have agents, right? We have our Falcon agents. So I really think we're in a good position to contribute.
Thank you.
Thanks, Joe.
Thanks, Joe. We'll now take our next question from Ken Wong at Oppenheimer.
All right, great. Thanks for taking my question. A couple of just Falcon questions, somewhat in the same vein as Joe. But as Falcon takes over standard work, Peter, do you think customers may eventually need fewer applications, have fewer users? How do we balance that efficiency for the customer with kind of Veeva's ability to monetize, especially when thinking through that you're somewhat capping the pricing ratio at 10% right now? Any thoughts there would be great.
Yeah. Most of our products are not user-based. Most of our Vault applications, they are priced by capabilities or by size of the R&D spend or number of studies or type of study or number of overall employees in the company, things like that. I think we are really insulated from that whole user compression thing. Also, those models and how we can price can change. If a pharmaceutical company has 50,000 people today, but they somehow, 20 years from now, have 1,000, we would just price for our products differently because they are still adding the same value. Then in terms of the 10%, that is for Vault AI, that is AI in the Vault applications. But Falcon, that is different. That is priced by the capability, and different agents are going to have different prices. For example, our intake agent in clinical, that has a fixed annual subscription.
But for a top 10 biopharma, that is going to be definitely a seven-figure deal. But for a very small biotech, that might be $100,000 a deal. So, we will find a way to modulate that over time. I guess the main thing is that product really has to work, right? That is a very sophisticated agent that has to be right and has to be right all the time, and has to withstand the changes of underlying models. So that is a lot of work. We got to get that thing right.
Understood. Brian, just to piggyback off of that, I guess how should we think about the cost side of things when you have got Vault AI, again, anchored to 10% of the subscription, and you could arguably have sort of a buffet of AI activity?
Yeah, I think, Ken, with AI, the main thing here is it is still really about the value that we are creating with the product, which is why you heard us talk so much in the presentations earlier around customer success and product excellence as the main focus. With Vault AI, this is really about simplifying this for customers, so they really love it. And it is good for us to take the responsibility of managing that efficiently versus having a misaligned incentive to token max or do something else. It is good for our customers, it is good for society. So we feel really good about that change. Then, Falcon is different.
Falcon is going to be priced by the agent, so we feel good that if we are creating value for customers, that the margins will be there. But it is too early to really talk specifically about the margins here. You don't want to get rigid on that early in the innovation cycle. We don't expect a material impact in the short term and are confident in the value that we're creating in the product.
Great. Thank you so much.
Thanks, Ken. Our next question will come from Alexei Gogolev with J.P. Morgan.
Next year, I think our innovation is going to be walk-on music to give people a couple seconds to get their cameras on and hop on here.
I like that. Hi, everyone.
Hey, Alexei.
Thanks a lot for giving me an opportunity to ask a question. I wanted to talk about IQVIA. Peter, in the past, you talked a lot about IQVIA mainly in commercial, but now you're emphasizing clinical operations standardization. What does success look like in the next 12 to 18 months?
In the clinical area, success, well, they have. That's the largest CRO in the world. They are running at any given point in time probably more than 2,000 trials, right? Clinical trials. This is an amazing company doing a lot of things. In just seven months, they're going to move their whole core applications for clinical operations. That's eTMF, CTMS, and even the Site Connect, how they reach out to site. In just seven months, they're going to move that all live to Veeva for all new studies. That's step one, and I'm really focused on that, right? Delivering that value at speed. By the way, that just shows how good our services team and our product is getting. I would say, Alexei, if we had to do that two years ago, that seven months probably would have been 14 months.
And we're able to implement things faster because the product is better and the service is getting better. Step number one is we complete that on time. They're very, very happy with that, a happy customer. I would say over time, I think IQVIA and other CROs can be a great channel for our Study Suite. When the sponsor, the biopharma says, "Hey, I want you to outsource this study. I'm going to outsource it to IQVIA or somebody else," they might say, "Hey, yes, and use the Veeva Study Suite," which is EDC, eCOA, and RTSM. That makes it easy for the sponsor, and that's great revenue for Veeva, and it helps IQVIA and other CROs accomplish their goals of technology not getting in the way. So, I'm very bullish about customer success of CROs and the CRO channel. CROs want to get more automated.
They absolutely do. Now finally, we have the technology in AI to help them do that.
Thank you, Peter. Brian, very quick question on services. You're now guiding over $600 million, saying business consulting is the main driver longer term. So how should we think about services margins and mix as AI adoption increases?
Yeah, it's a great question, Alexei. So BC, business consulting, as we've talked about, has been a key driver of growth for the last year or so. We have expected it to be the main driver of services growth out for the long term here through 2030. This year, we've also had very strong growth in the other side of services and professional services. We manage both of those to have strong margins. Now, the economics are changing a little bit, as Peter talked about, with more of our projects moving to fixed prices, because they're AI-enabled service packages now. But we're going to continue that same focus of managing it for growth and for profitability in services. No change in the philosophy.
Thank you, Brian. Thanks, Peter.
Our next question will come from Rishi Jaluria from RBC.
Oh, wonderful. Thanks, guys, so much for taking my questions. Maybe I want to start with thinking about some of the longer-term targets, right? You're simultaneously growing your TAM from $20 billion to $30 billion on just the thought that AI expands the addressable opportunity, in addition to other things. But you're keeping your calendar year 2030 target the same. Can you help us understand just how should we be thinking about the relationship between the two? The read on that would be, well, AI for Veeva won't be fully monetized till at least calendar year 2030, and I'm sure we're going to see more of it between now and then. What would need to happen to begin capturing that incremental TAM ahead of calendar year 2030 versus treating it as a post-2030 story? Then I've got a quick follow-up.
Yeah, I'll jump in there. The way to think about the $6 billion 2030 revenue goal is that's a long-term goal. It means it's something that we're working towards. It's not a CAGR, it's not a forecast. That's what the annual guidance provides. We do that because it's good to have a goal. But each year on the path to it's going to be a little different. There's always going to be some lumpiness. There are going to be some years that go a little slower or faster. We're pleased with the progress towards 2030 so far, but there's a lot of execution left to do. We're not dependent on AI or Aspen or other things to hit the goal, because they weren't factored into the initial bottom-up build. But the goal doesn't change just because we're building and innovating. That's something we're always doing.
Yeah. Okay, got it. That's helpful. Then maybe just on the Vault AI pricing, I know we talked about this a little bit, but look, I think coming out with a 10% number is very much, in my mind at least, a pretty strong rebuke to a lot of the conversations happening out there about token-based pricing or consumption or outcome-based pricing, whatever, and preserving predictability. Can you maybe talk us through, how did you kind of arrive at the right pricing model when the rest of the industry seems to be going in a different direction? I'm assuming a lot of that was based on customer conversations. Would love to hear your perspective. Thanks.
Well, on that, I think there's always opportunity. I think you can see from Veeva, we don't like to follow the herd, right? Because we're doing something different, and there's less data when you're following the herd. Yes, it was really having the patience to say, "We need to listen. We need to listen. We need to not be pushed into doing what others are doing. We need to listen. We need to experiment until we get it right." Also, we need to understand, what are we capable of in Vault AI? How transformative is it going to be or not? What is our cost of goods sold? So we had to wait on that. Then when you listen to customers, what they want, first of all, they want optional AI, for sure. They don't want to be forced into something and paying a mandatory AI price.
We deeply don't want unhappy customers for many reasons. We don't want unhappy customers. So we don't want to force any mandatory AI. They want predictable, for sure, right? Because they have budgets, et cetera. They want predictable. Then they need something that adds value, actually adds value. So for us, it just, the time came right, and we came up with this innovation like we do in the management team. Okay, let's give them predictability, but the value that a top 10 pharma is going to get is much higher than a smaller biotech. But we don't want to price by the user. That doesn't make sense. So that's where we came up with the 10%, considering we're pretty sure we can keep it very efficient and keep our cost of goods sold quite a bit under 10%.
Also, we know we have to put a lot of effort into it. I always want to see, okay, if something can cost me a dollar, it's got to provide at least $2 worth of value. That's kind of how we price things, based on how much value. We don't want to maximize the price on any one thing. I know it's a little bit of a long answer, but in terms of our philosophy, we don't want to try to maximize our price on any one thing, because over the long term, you're abusing the customer relationship, and you're going to open the door for a competitor, and you're going to harm your customer relationship. That doesn't fit with us. So, we stayed out of the AI hype kind of thing and just stepped back. Okay, what's the right thing to do here?
Make an excellent product. What's a fair price?
All right. Very helpful. Thank you so much.
Thanks.
Thank you, Rishi Jaluria. Our next question will come from Stan Berenshteyn with Wells Fargo.
Hi. Thanks. Peter, 2026 has been a proving ground for AI. Obviously, a lot of your customers are testing it out. Can you comment on what's the uptake? Do you have any visibility into the uptake of these AI products into next year? Can we expect some revenue inflection?
Actually, on my end, it just broke out a little bit. You said, "Can you comment?" So you will have to repeat that. I am very sorry.
Sorry. Can you just comment on 2027 in terms of, do you anticipate any AI inflection into next year? Obviously, this year was kind of a proving ground, so just trying to understand if you have some visibility into next year.
Well, no, I cannot really comment on or do not want to give any projections for next year. We do have an active pipeline for Falcon right now. Pipeline is just a pipeline, and we have some early adopters, and we do have some deals that are measured in the seven figures in the pipeline, and some deals that are in the six figures. So, I think it will contribute next year. Yes, for sure. We will sign contracts, significant contracts that are not experimentation. I think you see from Veeva, we never wanted experimentation revenue. I do not think it is a good thing, experimentation revenue that you can get and then it can go away. That is not the game we are playing at all.
Next year, I think we are going to have solid subscription, value-based, baked-in long-term revenue, but we are not ready to size that yet.
Got it. Well, thanks so much.
Thank you.
Thank you, Stan. Our next question will come from David Windley with Jefferies.
Brian, somebody's going to set the record. I think David did it for getting here the fastest. There you are.
I'm going to go, Brian, I'm going to go with "Enter Sandman." How about that? That'd be my-
It's a classic, but you got to be the closer to do that one.
My question, Peter, for you is a little bit of a competing, I suppose, set of concepts. In your discussion about Study Suite and the opportunity there with the CRO channel, I guess first I want to understand, do you see that as primarily the clinical data or both clinical data and clinical operations? I guess it'd be inappropriate to say that part of the TAM wasn't available to you, but you did say you really hadn't pursued it that aggressively. How much of that, how much TAM would you say is contained in that you weren't really actively chasing?
When I consider that Study Suite, I'm primarily considering in that $1 billion I mentioned, I'm primarily considering the clinical data products, EDC, RTSM, eCOA, through the CRO channel, where it's outsourced that. There's no way to say exactly how much that is. It depends on how many trials are run. It depends on your pricing. It depends on a lot of things, how much service is in there, et cetera. But it's in that ballpark. So that's about it. Yes, that was included in our TAM, but it was something we never really pursued because, well, all things take time, right? You're focusing on certain things, and then there's a level of coordination that you need to put in your product and services and in your field teams that are selling into the sponsors, but collecting the revenue from the CROs. That's one thing.
Also, our Study Suite would not work very well unless the CRO is using our Clinical Operations Suite, because the CRO would have a burden of a different Clinical Operations Suite trying to fit in with our clinical data, maybe some data mismatches, and the sponsors would end up feeling that. So I never really felt comfortable pushing that until I knew, okay, we have a lot of the CROs on our Clinical Operations Suite, and especially we can see that more is coming.
Yes.
There's a time for everything, and now is a time. Well, maybe there's not a time for everything. I think that's probably too broad, but there was a time for Study Suite, and I think it's here.
I would agree with you. You do have a lot of CROs on Clinical Operations. My other question is then on Falcon and how you manage, I guess I'll call it the channel conflict, so to speak, that those same CRO channel partners are perhaps some of the labor that gets disintermediated by an agentic labor application or AI. How are you seeing that accepted by those channel partners?
Yeah, I would say it's an excellent question, very insightful. When we announced Falcon earlier this year, that was something that I thought, "Okay, are we going to have conflict there with the CROs, and how's that going to work?" Because you really can't discuss something too much until you announce something, right? Then we're discussing. Well, there has been no conflict there, and what I rapidly learned is the CROs make a lot of their money on very high-value services, and they really don't want to do that commoditization work. They do it because they have to. Their view is, somebody will commoditize that with AI. Hey, if Veeva can do that, great. If we can get an economical product from Veeva, great.
Otherwise, they'll do that internally, and they'll have their own internal agents. So we're both aligned, the CROs and Veeva, that that lower-quantity work should be done by AI, and they want that. They want to move up the stack higher value. So there's no friction. It's great.
Super. Glad to hear that. Thank you very much.
Thank you.
Thank you, David. Our next question will come from Brian Peterson with Raymond James.
All right. Thanks, guys. Hopefully I wasn't too delayed there. So, hey, Brian, I just wanted to ask, it looks like the Commercial Cloud portion of your long-term targets went up a bit. I'm just kind of looking, want to understand maybe the moving parts and what drove that, and as we're thinking about mix, something has to go down. So I just want to make sure we understand, as we're thinking about 2030, what has moved within that?
Yeah, it's a great question. Eagle-eyed there, Brian, as always. It's really an artifact of us simplifying the exhibits. The last time we showed it, we broke med tech out as a separate line. A portion of med tech is in commercial. You've got some rounding because it's directional. There's really been no material change in our view of what 2030 is going to look like. It's just a function of streamlining the exhibit.
Got it. Maybe as a follow-up, Peter, you made some comments about, we're at halftime here in terms of the Vault CRM migration. You also expressed some confidence in win-backs. I'm curious, how do you think that would evolve? Why would that happen? Maybe if that does happen, when would we start to see that? Thanks, guys.
Yeah, I'll take that one. How that will happen, first of all, we just want to stay close to our customers, right? A lot of these win-backs are in large pharma, and we have a lot of other products in and around there. So we want to be nice and deliver to our customers. We want to really focus on the customers that have picked us and make sure their products, their implementations are super successful, which they are, and really push that implementation. I think how do these win-backs happen? It happens, can happen when the other solution doesn't deliver very well.
When they start to roll out and maybe their field force is like, "Wow, this is not what we were expecting." We've already had a couple of those projects have had delays, and one delay is okay, maybe two, three, okay, it starts to get an issue. Also can happen with executive turnover also, right? These are large companies, certain people made certain decisions, and sometimes there's turnover. That can happen. So we're not pushing it, right? We're being patient. We're very confident that we have the better solution over the long term, and you just have to be there and be a partner for these customers, and if things don't go the way they expect, we'll be here.
Thanks, guys. Appreciate it.
Thanks.
Thanks, Brian. Our next question will come from Tamjid Chowdhury with Guggenheim.
Hey, guys. Good seeing you all. Thanks for taking our questions. I guess the first one, as you continue to expand Falcon across R&D products, how do you see the competitive landscape evolving there, particularly in light of OpenAI's recent acquisition of Orchestra Bio, which has some overlap with your clinical operations business?
Yeah. So, good question. We don't see the model companies, the big AI companies, as competition, right? They are focused on a lot of things. They're interested in life sciences. They focus a lot on the research area. They're teaching their models about biology, and we think that's great. It's one of the big enablers of the golden age of life sciences. But in terms of what we do, it's pretty thorough and complex with Falcon, not just with Falcon, but with our Vault applications and our data and consulting. It goes from clinical to manufacturing to commercial, all kind of fit together. We just really don't see the model companies as competition. Who knows what may happen in the future, but I think what we're doing is pretty detailed. And we're focused on that strong link between Falcon and the Vault applications and creating industry standards.
We have 8,000 people working on this, right? I think we think they are really not competition at this time.
Great. Thank you. As a follow-up, the acquisitions that you have made this year, you mentioned it, Ostro and Copli, are both on the commercial side of the business, but it sounds like there is a big opportunity on the R&D side of the house. How do you reconcile that, and how should we be thinking about you prioritizing investments between the two?
Well, we are always very disciplined on our acquisitions, right? You will see that, right? Look how Crossix worked out, et cetera, right? We are very disciplined. We do not really have failed acquisitions. So we look for culture fit. We look for a willing seller. We look for a clear business strategy, ability to execute. So if you look at 200 things, you might find one, and it is just somewhat random when you can find one. So we look in all areas. We found these two. We might find others in R&D. We might find other small ones. We might find a big one. You just cannot force this stuff.
Great. Thank you.
Thanks, Tamjid. Our next question will come from Kirk Materne with Evercore.
Hey, guys. Thanks for taking the question. I appreciate it. Peter, maybe just to follow up on that last question, you could go a little bit deeper on the big hyperscalers or the big LLMs. I mean, they do have relationships with a lot of your customers now, and I imagine most of those are on the drug development side. My guess would be that they do want to hook themselves into other workflows and things that might not be codified already that you guys are working with them. I guess, is there an opportunity to partner with them as well? I mean, I think most people will view it as sort of potential competition, but there could be a better together scenario with you all and the LLMs. I'd be just curious if you could run through a little bit.
Yeah. Certainly, our products work together, so the big hyperscalers, right? We have our tools that fit into their models, skills for Claude, et cetera, so you can use Vault applications in a headless manner. That's pretty straightforward. Then, of course, we use models from OpenAI, sorry, from Anthropic and others inside of Falcon and inside of Vault to provide reasoning. But what's really interesting there is over the last six months, we really have all we need for the models. We have the level of reasoning that we need because the value is on top of it, right? Not only the application and the agents, but the very specific harness. So if we're doing something about a clinical trial, it's not okay, like, "Oh, it works 80% of the time," or something like that, or it changed, right? It's the harness on top of that.
There may be opportunities for tighter partnership at some point, but it's not really something we need at this time because the model provides reasoning for us. It's infrastructure for us.
Okay. That makes sense.
The better it gets, that's all great, but right now, we actually don't need it to get that much better because we put the value above it because we need to be more deterministic, right? There's actually a value in what we do. There's a value in consistency. Consistency has a value all of its own that's actually above correctness, especially when you're talking about reasoning. Consistency is something that people can work with.
Along those lines of consistency, the determinism you have in your systems, how do you think about people accessing Veeva Vault through other UIs and through an MCP server? Is that something you, I assume you want to give them, your customers, that level of flexibility? Is that headless strategy something you're going to entertain, some of your products or the platform itself?
Absolutely, right? People are doing that today, and they will do that a lot more in the future, and we're enabling that, right? We have MCP server today. We have the Vault's command line interface coming up. So absolutely, Vault is going to be used by end users, and it's going to be used by agents. What we're not doing is we're not charging extra for that. We're not some toll gate thing like that. It's not like that. You get capability in Vault, and you can use it because I think long term, our customers, they're going to hire humans, and they're going to hire agents. Both of those things, both humans and agents, they have to coordinate on some way on what is the clean data, what is the business rules, what is the workflow, and that's what Vault is for.
I really don't understand this notion of charging extra for agent usage. It would be like, in the past, we had end users using our application. Also, we have APIs, right? It's like, "Oh, are you going to charge extra for an API call?" It's really not anything that anybody If you ask any customer, "Do you like to be charged for AI access?" Not many of them are going to say yes. I don't think it's the right thing to do.
That's helpful. Thanks a lot.
Thanks.
Thanks, Kirk. Our next question will come from Jailendra Singh with Truist.
All right. Can you guys hear me okay?
Yes.
All right. Maybe first a quick clarification on David's question. You described CRO opportunity as more than a billion-dollar opportunity that the company hasn't historically pursued. How much of that opportunity is embedded in the current $6 billion framework, or is that all incremental?
Brian, you want to take that one?
Yeah, I'll take that one.
talking about the TAM versus the revenue goal.
That's right. Exactly. Jailendra, I think that's really a question of TAM versus our goal for 2030. The TAM is not new TAM. It was there before. It wasn't, as Peter said, something we were as actively focused on because you got to focus somewhere, which doesn't mean everywhere. So what we're saying now is we're investing more in that area, which hopefully means it's fuel for the growth path to 2030, but it's not really a change from the path we were on or expected to be on.
Okay. Then I want to ask about the discussion earlier about, I think Joanne Byrne from Roche, she made a very good point that customers need the underlying data connectivity and workflows in place before they can really scale AI. As you look across your customer base, how much of the market do you think is actually AI-ready for your tools and platforms? Is the customer readiness now a bigger constraint than the technology itself? Is that the main reason why still majority of your growth might come from your top 20, because they are much ahead of the other players?
That's a good question. I wouldn't want to characterize it in percentages, but it's both. It's both the customers not being AI-ready and the technology. For example, Falcon, it's not ready, it's not proven yet. So I think it's both. The data is actually much more organized in the smaller biotechs, particularly like the smaller biotechs using our Veeva Basics products. We have almost 200 customers there, and that is an industry standard process. So by definition, their data is absolutely organized. So where it's harder to organize, if you have a large top 10 biopharma, they have multiple different systems, many add-on systems. They may have done some acquisitions. They may have some deferred maintenance. They may even have some on-premise systems, right? That's where it's more difficult. The larger you get, the more data issues you're going to have.
Okay. One more if I can. In the clinical network strategy, are these contracts with CROs going to be like fixed enterprise subscription at the CRO level, or would you guys participate economically only when the CRO deploys this application at the study level?
Yeah. There's really two parts. The clinical operations part, so that's Site Connect, CTMS, eTMF, that study training, those types of things. Those will be a fixed capability. For a CRO, they would view that as a cost of theirs, right? That they would burden, that's how they drive efficiency. The clinical data management, those are normally passed through back to the sponsor. Because in the clinical data management, the types of services and the tech you need may depend on the study. I'm doing a study and it's a smaller study, less patients, less sites, and it's a mental health study. Okay, well, now I'm doing a study that's many more sites, many more countries. It's a cardiac study. It has different patient assessments. Okay, that's a more expensive technology. So that's generally passed through.
Got it. Thank you.
Thank you.
Thanks, Jailendra. Our next question will come from Andrew DeGasperi with BNP.
Brian, you are going to have to sing the walk-up music.
I will attempt maybe.
I could sing maybe in the background.
Brian can sing. So everybody knows, he can sing. He can actually sing.
Oh, good to know. Maybe just a follow-up after the last question, and I thought what was interesting was that Joanne Byrne from Roche again mentioned how these new regulations essentially are pushing these pharma companies to structure content and data to make it easier to not only submit these documents, but also to review them. I was just curious to know maybe, since I haven't heard much about this, at least where I sit, is this sort of an ongoing or relatively new development? Is this potentially an enabler for Veeva to potentially deploy these agents in the future? In other words, is that timeline going to essentially match how these pharma companies adopt these regulations or meet these regulations?
Yeah, it is definitely an ongoing thing. Regulations change in the regulatory area, in the clinical area, and in the drug safety area, and that's been going on since, for the 20 years I've been going on in life sciences. Is it changing faster now? So far, I have not seen it changing faster, but I think it very well could accelerate because the health authorities are getting more tech-enabled and they're getting more AI-enabled. I think the rate of regulatory change may accelerate a little bit. We'll have to see. Yeah, and it's really a major pain for the life sciences companies to keep up with that, and I think that's a wonderful thing that we do.
I was talking yesterday with the CEO of a small biotech, and they're in the clinical trials phase, and their product is approved for this clinical trial for the U.S., and they want to open up some sites in Canada. Well, that's a different health authority, but they have Veeva Basics, so he said, "Well, we just use the Veeva Basics. We did the submissions in Canada. We really didn't have to think about it too much because it was all in there." Now, without something like Veeva Basics, you really would have probably had to go get a different system that worked for Canada, get a consultant, figure out, move your data in there, right? Now, the impact of that, and I know I'm going off a little topic, is, well, maybe that's a very serious disease. Maybe it's something like ALS, which is terrible and debilitating.
Well, that might cause a two-month delay for that patient, and you might not be able to get that patient in the trial. We like it. It's technology, it's good stuff, but it's also important to understand what is the impact that it has on companies and on patients. We're not developing a spreadsheet here, right? It has real impacts.
Right. I guess maybe just one on capital allocation. I know you did two acquisitions earlier this year, small ones. They hadn't been done in a while. You did introduce a buyback authorization earlier this year. I'm just curious to know, in terms of how do you think about the balance of the three buckets in terms of use of cash? Has that changed in any way? Are you still essentially maintaining that framework that you've had before? Or should we see things moving more in one direction versus another?
Brian, you want to take that one?
Yeah, I can pick that up. I think, Andrew, the first thing is driving organic growth, right? We've got this big $6 billion goal. We're investing in the product on a whole bunch of fronts. So, that's certainly the first most important use of capital as we think about it. Second, M&A definitely has been a focus for us over the past couple years, and we had a couple smaller acquisitions, tuck-in acquisitions earlier this year. We continue to look at acquisitions on a range of sizes, right? Peter talked a couple times about how important it is to stay disciplined, so we're staying very disciplined there. But to the extent that that helps accelerate the journey and create customer success and product excellence faster, we're still focused on that. Then the share repurchase program we started earlier this year, so we're a few quarters in now.
Pleased with how that's going. So those are the three main pillars, and they're really unchanged over the past couple cycles.
Thank you.
Thanks, Andrew. Our next question will come from Billy Fitzsimmons with Piper Sandler.
Hey, guys. I think I'm the loser for longest to get Zoom on, so I apologize for that. Just on the financials, going back to everything we've talked about and the long-term targets, and then what we've talked about with Falcon monetization. The 2030 goal kind of implies low teens CAGR per year, and it's kind of talked about organic growth in existing products. We've talked about today how Vault AI is going to be priced at 10% pricing, and Falcon is a potentially big new market for agentic labor. How much of Vault AI and Falcon revenue, if any, is in that $6 billion target? How do we think about potential upside there over time as these products are adopted, if that's a possibility as it's rolled out to the base?
Yeah, Billy. We built that $6 billion goal, gosh, a couple years ago now, I guess, two investor days ago that we announced that. We built that bottoms up based on the products that we had at that time. We're not dependent on Falcon or Vault AI or Aspen to achieve that $6 billion goal. We're also not putting a financial target on those businesses yet. As we said, they're still very early, and we think that they can contribute to Veeva over time, but the $6 billion goal doesn't require them for us to achieve it.
Perfect. Makes sense. Thanks, guys.
Thanks, Billy. Our next question will come from David Larsen at BTIG.
Hey, thanks for all the details. Really appreciate it. I have been getting a couple questions from investors, some good ones, I think. Can you talk about the UCB win, also the IQVIA win, to the extent you are able to, please? Just were those existing clients? What did you add? What incremental services did you sell? Just any color on UCB and IQVIA would be great. Thank you.
Paul, you want to take UCB? I will take IQVIA.
Yeah, UCB, I'm assuming you're referring to the recent press release. Maybe it was this morning. Feels like a long time ago, on Vault CRM selection. So yeah, UCB, another very meaningful, significant customer. They've been a customer of Veeva for a long time for Veeva CRM, and now we've won them in all markets, and we're happy to add them to the Vault CRM family. We're doing well in the Vault CRM space, and this is another meaningful addition there.
So you used the phrase all markets. Was it a limited market previously, and now it's all markets?
That's right. Yes, that's correct.
So, like Europe to worldwide?
Yes, it is global. That's right.
Okay. And legacy Veeva Vault to now the CRMs, the core-
Now it's all The commitment is to Vault CRM.
Okay, great. Thanks, David.
That's right.
In terms of why with UCB, I think they're like many of our customers. They have a strong pipeline that they really believe in. Once you go through that pipeline, that research, that drug discovery, you really don't want to take risks, and how do you bring that out to patients, right? So they would look for the most robust product and the company that they could rely on that fit within the other Veeva products they had. So, we have a great relationship with UCB. I know many of their executives. That's an outstanding company. With IQVIA, it's different, right? Especially on the clinical side. Historically, they had not been a customer of ours because, if you wind back, I think roughly two years ago, we had a legal tussle with them that really prevented business from being done.
There was no real tussle on the clinical side of IQVIA, but when you have a legal issue, which was rooted in the commercial side, that spilled over, and so we just couldn't do business together. So it was sort of forbidden ground, right? Then we solved that legal issue, started working with them, and they just decided, "Well, we're just going to go all in with Veeva." It feels great because they spoke at our customer summit. We had our R&D, our development and quality customer summit in Boston maybe a month or so ago. There was about 3,000 people there. It was a fantastic event. An IQVIA leader in the clinical area came up and spoke on stage with me, and you could just see in the audience, they are comforted. Two of their largest partners are working together.
They know that's going to create value for them. So I couldn't be more excited for Veeva, the business, and IQVIA, but also how this is going to help customers, right? You always want to help customers. It makes your business go better at the end of the day.
Another question I have been getting is, like in 2024 for your investor deck, I think it is like slide 50 of 62, it shows the penetration rate of all these different modules, which I thought was very interesting. Just at a high level, I have been asked, what is the current penetration rate of your customers now across your portfolio? If you had to put a number on it for subscription, is it 60%? What could it get up to, and what sort of incremental revenue lift are we looking at? How much revenue potential is there with upsell into your base?
Brian, you want to take that one? It is a bit of a nuanced answer there, I know.
Yeah. I appreciate you calling out the name of the slide because you were testing the limits of my memory on the two years ago slide number. We had an updated version of that slide today that we shared in my section that we tried to simplify a little bit because there are so many applications at Veeva, right? 15 suites, more than 60 products. So what we tried to do this year is focus a little bit more on the major products, and hopefully that will be a helpful update from the cycle two years ago. It is still very early in the journey, David. I mean, the TAM is $30 billion, and we are 12% penetrated against that TAM. So that is where we see the potential over time.
Now, you think about existing products, and maybe that is like a slightly smaller portion of it, but it is still very early in the Veeva growth story. There is still a number of growth avenues in the leader products that we have that are market leaders today, but have customers that have yet to adopt them. Those leader products, even when we sell them, there are a number of add-ons that sit around them where there is a lot of growth opportunity. And then we have all of the growth products that are newer, central anchor systems that still have tons of runway ahead. There are many avenues for growth at Veeva right now.
Just one last quick one. How would you describe the state of the R&D market right now? It seems like over the past five years, there was a lot of fluctuations, IRA, tariffs, and so forth. Are we now in sort of full growth mode, green light, things are progressing? Any thoughts on the Democrats taking a lot of power in the House and Senate?
Well, I'll probably take that one. On the research side, in the clinical development side, it is somewhat interest rate sensitive, right? So that can make things go up and down, but that's been pretty stable and good. So the funding environment and the new trial starts are high now. They're good, and we see the innovation going. I think we're starting to see some effects of the advances in the research capabilities. So there's a lot of mojo in the small biotechs now, so I think that's good. Customers, they prefer stability if they can get it. Like all businesses, they prefer stability. There has been some instability in the past years, right? There's the drug pricing schemes, the most favored nations, the wars, the supply chain, the COVID. They don't like that, but they're also used to that instability now.
At the bottom line, patients need to get their medicines, and everybody has an interest in that. As far as the Democrats win, yes, it was quite a historic win. I wouldn't say it's your average election. However, I don't think it will have any impact on life sciences. I don't see any short-term impact or long-term impact that I can see now. It's a pretty resilient industry.
More coverage means more claims, which means more revenue to providers and also the pharma industry. So, it might be a good thing, but who knows?
Yeah. We'll have to see. Things don't change overnight, but in general, yes. What I'm enthused about, when somebody doesn't feel well right now, for whatever reason, and they think they don't feel well, through all the way, through all the steps of, "Oh, there's a therapy that I can use that helps me," there's tremendous amounts of barriers now. You can't self-diagnose yourself. It might be so specialized, you can't get an appointment to a doctor, right? Your insurance doesn't cover this and that. If life sciences can treat more people more faster, that's going to equate to more value, to more revenue, and to a better world. That's what I mean by this golden age of life sciences.
I'm actually very optimistic for the life sciences industry, and I think many people can understand that at a personal level if they've ever been sick or have a loved one sick. Is it very easy to figure out what's going on and to get treated? We accept it as it is today, but I think it's still tremendously inefficient.
Thanks very much.
Thank you.
Thank you, David. Our next question will come from Tyler Radke with Citi.
Okay. All right. I think that worked. My question was on-
You won. That was a record.
That was-
Yeah. Okay.
That's going to be hard to beat. All right. I didn't even use an agent for that yet. Question on the Vault Agent strategy. Actually, I do have my agent right here helping me out. If you hear her in the background, she's excited about AI as well. Curious just as you think about some of the emerging opportunities, I think you had a slide talking about the considerations for other areas you want to go with Falcon Agents. Is that going to be using the underlying platform that you have today, or should we think about acquisitions kind of getting you there? Then, just as it relates to acquisitions, Peter, I think you talked about considering things small and large.
Any just limiters that you would kind of encourage us to think about to the upper end of those acquisitions that you'd be considering from a large deal perspective?
Yeah. For the first question, the agent framework that is used for Falcon, that's going to be a reusable thing across all those applications, just like Veeva Vault is. It doesn't mean we might not We might do an acquisition for a specialized skill in an area of domain knowledge, but yes, that agent framework that we're developing, that harness, is definitely a reusable one. In terms of acquisitions and sizing and guard lines, of course, we don't know the future. We want to maintain a healthy cash position. At this time, I don't anticipate doing something that's so large that we have to take out debt or something like this. That's really not on our radar. Not to say it's impossible, but that's not the way I'm thinking now.
Great. Then, if I could just ask a follow-up, kind of thinking about how AI is maybe accelerating the core, both in terms of migrations and urgency. Is there a way to quantify, if you're landing a Development Cloud deal today, is the sign to live time 20%, 30% faster? How much of that, if any, in terms of that acceleration and migrations, are you incorporating into those Development Cloud targets?
Well, we have our target, which is our $6 billion target, so we're not going to update that this year or next year, right? That's our target, and we want to meet or exceed that. I think your percentages that you said there, that could vary by area, but yeah, that's in the rough timeframe that we're getting faster at implementing things. All things considered, that drives revenue for us. Now, I would say that was always partially in our plan, right? We always knew that we were going to get more and more efficient with our services. So, I would say things are going as expected there.
Thank you.
Thanks.
Thanks, Tyler. Our last question will come from Charles Rhyee with TD Cowen.
Sorry, I'm clearly not the fastest in this.
You're going to be the best though.
All right. Obviously, a lot of great comments today, and appreciate that. Maybe I can ask maybe a question that's a little bit in a different direction here to end it. If you look at where the pharma industry is going lately, think of drugs like GLP-1s, a lot of the focus has now been shifting towards a direct-to-consumer approach. You're even seeing companies kind of developing drugs with a direct-to-consumer in mind, go-to-market strategy. Maybe in commercial, can you talk about how you support your pharma partners in this kind of shifting approach, where it used to be detailing to physicians and targeting prescribers?
What does that new world look like when companies are trying to get to patients and engage them, deliver care in that kind of way? What do you think of what that market looks like? How are you currently supporting customers today, and how do you foresee maybe tools that you have that companies aren't using today could deploy to help them on that journey? Thanks.
I would say, when it's direct to consumer, you have to consider, is this an over-the-counter medicine that doesn't need a prescription, or is a prescription needed? We're generally going to play in that area where a prescription is needed. When you're doing direct to consumer, that involves a lot of our PromoMats and our Falcon MLR, right? Because you have the reviews and things like that. Crossix, of course, is a big thing, right? You got to optimize your media dollars and Crossix measurement and Crossix optimization. Market access and the B2B selling is critical. That's critical for this type of thing, and that's something that happens around the world, right? You can't just get coverage right away, right? You have to do that. So that's our CRM system and the key account management. So, that shift is gradual, and it's been happening over time.
But in the areas, yes, a lot of revenue definitely in GLP-1s, but that's not the be-all, end-all. So, for example, when you think about regenerative medicines, and there's been major scientific advancements in that area, what types of things is that going to enable, right? There's a lot of different things going on, and so, I'm really enthused about that all. Especially, an interesting thing that doesn't affect things over in the R&D side as well when you're developing these drugs. In fact, some of these drugs that are more heavy, broad, consumer-focused will actually run some of the largest clinical trials because you need coverage of a lot of patients. So, I think it's a good trend. The more medicines, when they reach the more patients, the more value into life sciences and more value that we deliver to our customers.
Direct to consumer is a good trend for Veeva.
Great. Well, I'll just leave it there. Thanks for taking the question.
Thank you.
Thank you, Charles, and to everyone for joining the Q&A portion of the event. I will turn it back over to you, Peter, for any closing comments.
All right. Thanks, everyone, for joining. I love the speed of which you joined on Zoom, and I loved your questions and love seeing your faces. I look forward to hearing from you on our Q3 earnings call, which is coming up soon. Thank you very much.