Okay, great. Well, good afternoon, everybody. Thank you for joining us for day two, day three of Baird Global Consumer, Technology & Services Conference. I'm Rob Oliver, managing director in the tech research team here at Baird. I follow software. It's my pleasure to have Julie Iskow from Workiva here. Julie, good to see you. Thanks. Thank you for having me, Rob. It's a pleasure to be here. Workiva is one of our favorite mid-cap names. I think small cap now. A lot of my mid-cap names have become small caps because of what's been going on in the market. We don't think it should be. I think the goal in today's session is going to be to try to get everybody who's here to leave with a better understanding of Workiva and hopefully want to follow up and understand the platform. Let's just start with the platform because, I think you've heard me say this or write this before, Julie, but I follow a lot of software companies over the years I've followed that have talked about being a platform. I always say if I can get one thing right, it's who actually really is, that would be enough value to keep the job. You guys have went from being a one-product company when I first got to know you years ago to being a true platform today. Maybe talk about what that platform is and what that platform does for enterprises. Sure. You're absolutely right. We started out with automating an SEC filing 17 years ago. And t oday we have a platform that really manages the data that matters in the office of the CFO. That covers a number of areas. It covers financial data, it covers non-financial data, capabilities around GRC, risk management, audit, and controls, really relating to, of course, the financial and non-financial data. We have become that platform. All solutions are built off of our unified platform. We serve the large enterprise customers. We have 85% of the Fortune 1000, I will tell you today that that includes those companies powering the new economy, including those companies that control data, that control compute, that control automation, that control digital distribution, that control energy capacity, it also includes those top IPO candidates that you are hearing a lot about, of course, the top LLMs as well, so that who we become. The capability of Workiva and that broad platform resonates because our customers trust us. Because we, that data in the Workiva Platform that I described, or the financial and non-financial data, we can show the traceability of all that data and the narrative back to source systems. We have the data lineage. We have the proof that that data has data integrity, accuracy, auditability, and of course, the consistency around it. That's really what Workiva is. We have a lot of solutions on that broad platform that you just asked about. Over two dozen solutions now on that platform in verticals, but a number of horizontal solutions, again, across financial reporting and non-financial or sustainability reporting and Governance, Risk, and Compliance around audit controls and Risk Management. You guys have done a nice job at your analyst events of kind of cohorting your customers, and you don't have it all in front of me, but for the purposes of the group, maybe talk about how a company lands with you guys even today, and then that expansion motion into other products. Absolutely. Yes, we used to land, of course, with our flagship product, SEC, and it was one solution. We might expand into multiple solutions. Today, expand with a number of those solutions across the portfolio, and we do, but we also land with multiple solutions and even multi-categories, as I describe the financial, the non-financial, or GRC. So expansion is significant. I think less than or I should say just over 50% of our customers still spend $100,000 or less with us, which means there is a lot of room. They're one in two solution customers, and we have a very broad portfolio across the platform with which we can expand accounts and provide more value to our customers. Where you guys land is often in that SEC filing. I wanted to ask about the SEC proposal on the amendment that would allow for semi-annual reporting. This comes up in all of our meetings now when we talk about Workiva, and I think we feel pretty comfortable with it. And speaking with your team, I know we've learned that, hey, this has been the case in Europe, and you guys haven't seen any real change in your average contract values there. Maybe help us understand why, in and of itself, reporting less doesn't reduce the value opportunity for you guys. Sure. I will say that the proposal that you just described, giving customers the option to report quarterly or twice annually, it is just a proposal. When we talk to our customers, they still are committed to whether or not they have that option, whether that becomes beyond the proposal stage, they still want to report with the rigor of the quarterly reporting. They're still going to close their books every month. They have investors, and investors want, as you know, more data, not less. So they still intend to go through that rigor of reporting, whether quarterly reporting, whether or not they press a button to the regulator. It will depend on who they are, the complexity of the industry, their stakeholders, their investors, and so forth. We're not charging based on the outcome of the report. The value, as I described earlier, is the fact that a CFO or the office of the CFO can have confidence in the data on the Workiva Platform. You do look in Europe, and we are charging similar prices in Europe, and they do report twice annually. For us, this is really a non-event. It's because our value is the ability of the office of the CFO to go into our platform, see audit-ready data, feel confident about that data at any point in time during the quarter, during the year. It's not about an end report at the end of a quarter or an end of a year. That's a really important concept. The value for CFOs today with increasing number of unverified data sources with significant data, especially around AI, they want confidence in the data that they disclose to regulators, to investors, even to their board and other stakeholders. That's critical. In other parts of the company, data being good enough is good enough. In the office of the CFO, data being good enough, as you know, can be a disaster. We are the safe place for the CFO's data. They know every data point and every number and narrative at any point in time can be considered audit-ready. They can be continuously report-ready, whether they press a button twice a year, four times a year, or need to pull those numbers out at any time to get holistic views of their business. They can do that on the Workiva Platform and feel confident about the numbers and the narrative and the traceability and the defendability and the explainability of those numbers and that narrative. I've followed this office of the CFO now for many years, and one of the hard things about it is that it doesn't always move quickly. One of the great things about it is if you're a company like you guys, it gives you the time. It feels to me like you guys have a window of opportunity on the AI side to innovate and be the AI layer, and that certainly was the theme for you on this last call. You came out really to address like, hey, what you're doing concretely in AI. Maybe talk a little bit about some of the products that you guys featured. You talked about AI-powered Data Query Analyzer, GRC for evidence investigation, AI and financial reporting. Talk about your AI strategy and where you're seeing. Sure activity today. Big question. I will say we're not acting as if we have time. We are moving quickly. We're devoted and dedicated to innovation, particularly with AI, because we want to offer that to our customers now and ensure that we're staying ahead of the curve. We don't look at it as we have time. We have a huge advantage with the data lineage, data traceability, data defensibility for the office of the CFO, as I described, and we're going to take full advantage and capitalize on it. It's why when we roll out new solutions, it's very straightforward in the office of the CFO, where we have our huge customer base, trusted customer base, to go and provide additional solutions to them. The way we think about data is the way most classic SaaS companies should be thinking about it in this new era. I say that meaning a lot of us have classic SaaS platforms, and they're not yet ready for applying the models' AI and going and accessing that data and becoming fully autonomous, meaning orchestrating agents to get outcomes without human involvement or human optional involvement. We've been on this path for the last year and a half or so. We've been transforming our platform. What it means is we don't just store the data, we don't just store the documents there for accessibility. We actually begin to get context around the data and those documents and what's stored in the platform from our customers over the past decade. We are building out that semantic understanding, that semantic layer that you hear about, where we have data models, right? That when AI is applied, you can actually facilitate agent development and the orchestration of those agents. That's the path we've been on and we continue to be on. We've already begun to leverage some of the capabilities that just rolled off of your tongue, yes, we've been doing those, and they're leveraging the transformed platform. We're taking the good stuff about Workiva, what's given us our leverage and our strength and taken us to the billion-dollar mark in ARR, but we're taking that with us as we transform the platform, make it very easy for large language models, for agents and so forth, to access the data on the platform to provide autonomous capabilities for our customers. We are doing that. One example, we rolled out tie-out agents, for those of you who are familiar in the office of the CFO, it's one of the most time-pressure activities in the office of the CFO, checking for data consistency before audits and filing. You can do it autonomously now, that is an incredibly labor-intensive and stressful process, error-prone, and paying a lot of attention to it. We can do that now autonomously because we've transformed portions of our platform that enable us to do that. I do also want to make the point, we're protecting our core, we're growing the core, we're transforming our current products, reinventing them to be more autonomous and ultimately fully autonomous, where humans can come in when they want, opt-in, human optional. We're building, of course, new TAM with the transformed platform. Those capabilities will, of course, be AI first and autonomous as well. It gives the user, the customer, options on how much they want to be in there governing the process, how little they want to be in. The idea is make it efficient and autonomous to get those outcomes. That's the way we think about AI. We're not resting. Maybe we have more time. We don't look at it at all that way. We're excited to leverage the technology, transform our platform, make sure we protect our core and grow that core, and then of course build TAM expanding capabilities with AI autonomously beyond the current platform. You said on the call, you disclosed that roughly 30% of customers had enabled AI on the platform. What are you seeing? You have tiered pricing, and you don't have a seat-based model. So when I look at your. Can you say that again? We don't what? Yeah. You don't have a seat-based model yet. When I look at the model you guys have, it seems to me like you're well-positioned to benefit in this world. I guess what does 30% have enabled? What does that mean? What are the ways that investors can measure success I assume when we're here next year, it's going to be a much higher number, but what's the right way for us to chart progress with that? Is it customers moving into the higher tiers of pricing on good, better, best? What's the right way to think about that? Sure. I'll explain a little bit about the good, better, best model, which is a way we've been able to extract more value and provide more value to our customers. We started this good, then I'll get into the AI. We started good, better, best last year, and what we were finding was we were starting to offer a lot of capabilities around, say, our SEC product, as an example. We noticed we would provide the capabilities, but we were discounting it to customers who weren't quite ready or weren't mature enough for the solutions. We put in kind of an essentials version, a standard version, and a premium version. If you weren't quite ready, we charged you for the essentials versions, and then we have a path to go extract more value, provide more value, moving you to the standard and to the more premium tier or the advanced tier. What we've done of late is we've put in our advanced AI offerings in that premium tier. It's a good way for us to get that out in the market with customers having predictable pricing regardless of usage. If you're a bigger company and more complex and we think you'd use more AI, we would charge you a higher price point in that premium tier. If you're smaller, you're just getting started, you're less complex, it would be less. It's a way for us to look at usage, but give the customer some predictability as they buy our solutions. It also gives us predictability as well on the usage and recoup costs for AI usage should we need to. The way we're thinking about it is, yes, adoption, and what we mean by the roughly 30% or a third of our base is they've enabled it, they've activated it, and they're using it to some extent. Some of that is just core to our platform. We've embedded the AI LLMs in our platform, in every workflow, in every solution. We offer it to customers to streamline and expedite their work, and get things done more quickly. That's just core capability in the platform, table stakes. The next phase was AI-assisted or AI-augmented, and we've put that within the platform, but also in some of the specific solutions. Those are the things that we've started to put in the premium tiers and charge for, and we're watching and monitoring the usage. Yes, you're seeing customers pay for that premium tier, and we're getting 20% uplift or more on the premium tier and the advanced tier. We're going to continue to use that model for a while. Gives us an opportunity to see how customers are using with some predictability. Helps us get feedback on that AI and build more fit for purpose and more specific, useful, valuable capabilities for our customers. Ultimately, we'll move to what I described as just orchestrated agents doing more autonomous work and full outcomes, where the users can go in when they want to go in. They can see the full range of the report or the outcomes. They can go in at any time with reviews, to do governance, and to ensure the right outcomes are there. They can see and trace everything being done by the AI. They can feel confident in those outcomes. That's how we're thinking about it today, and we find the good, better, best model with AI in the premium tiers is a good way for both customer and Workiva to start introducing those capabilities. We've got a lot more coming, both on the augmentation, yes, but really on the autonomous outcomes. That's really where we're focused. Everything we build now is in service to that more autonomous future. How important is I think back now to the model transition you guys did to, back, what was it? 2018, when you guys moved to the solutions-based model. It worked great, and it ended up really driving customers to adopt more of your Platform. There must be some muscle memory, some learnings that you have from that period, which help to inform you now. Yes Because Frankly business software investors are really just concerned about this model's transitions and who can manage them and who can't. It's such a great question. It's one reason we're being so thoughtful about the pricing of our AI capabilities. In 2018, we were looking at our customers. We were seat-based. We sell into the office of the CFO. Who is more conscious about spending than the office of the CFO? What we want people in our platform. We want them to reimagine things. "Possibility runs on certainty" is kind of our motto these days. We want to give you that platform of certainty. We want you to do whatever you want in there. In fact, some of our use cases come from customers doing things in the platform. That's where multi-entity reporting came from. What we found was they were holding back using our platform. They said, "Oh, if we have to pay for additional users, let's limit it." We thought, "Let's move to solution-based pricing and charge them on value." Our solutions have different measures of value. If you're in multi-entity reporting, we charge for the number of entities. Big companies have lots of entities worldwide, so they're going to pay us on entities, not the number of people using it. If you're a complex company and you're using our controls solution, it's number of controls. If you're buying a financial reporting, SEC reporting, it's the size and complexity of your company. Has nothing to do with the people. When we move to this pricing around AI, a lot of questions are coming in around, are you charging for tokens? We're being very thoughtful about it, because if you go in the office of the CFO and say, "Here's some new capabilities, and we'll charge you by use in your token use," we're pretty thoughtful about the reception of that. Which is why we love the good, better, best pricing, because the CFOs. Are SaaS companies doing that today, just charging by tokens yet? We're all thinking about how it's going to be perceived. We did learn a lot as we did that transformation on the pricing model, which worked beautifully for Workiva. Yes, we are not seat based. We don't have that challenge. We have an integration capability, data integration capability, and we charge on number of integrations. It works beautifully because as the company grows, we get to extract more and more of that value. Bigger, more complex companies buy more of Workiva, pay more for Workiva. It works really well, and we want to be very thoughtful about the pricing mechanisms and models that we choose for AI. I wanted to ask about probably the only part of your business that we really know just as well as you, or better, and that's the capital markets cycle. We're in a pretty good one right now. Yes You guys serve that capital markets end market. You mentioned some of the foundational LLMs models. You guys, I think, are doing a good job landing with some of these. Maybe help frame for us how you guys are exposed to this current cycle. Then also, more broadly, companies are staying private longer, they're larger, they're more sophisticated. Seems like there's an increasing role for you guys within those sophisticated private companies that report to other entities. Yeah maybe just not to the public markets. Yeah. A lot of questions there, too. I'll start with just capital markets in general. We have seen an uptick. Certainly Q1 of this year was more active from an IPO perspective than Q1 of last year. For us, we've kind of baked an increase into our models, for sure. Yes, we are very well poised to serve this market. SpaceX just went public, and that's no secret anymore that Workiva was the provider of their S-1. We worked with them on that. As I mentioned earlier, top LLMs are our customers as well, which is a statement right there for those wondering about whether or not Workiva thrives in this environment. They're using us. They have job descriptions on their websites looking for people experienced with the Workiva Platform. Even SpaceX has a large language model, and they are looking to us. They did for their IPO and more. I think the IPO market is alive and well. We're poised to go after those. Yes, it's a great land and expand for us, but more and more frequently, we're seeing the customer come 12 months to 18 months earlier than the IPO was planned. They will buy private company financial reporting. They'll buy private company controls in preparation, then the S-1 comes. We win that as well, and then there's the SEC, and the SOX follow on, and multi-entity reporting, and non-financial reporting. If you're in financial services, a whole host of regulatory capabilities as well. We have, again, two dozen solutions across the Platform, and depending on verticals that you're in, there are a lot of opportunities there to land and expand. I will say this, historically, we focused on the public companies as our customers. As you mentioned, more and more companies are staying private a lot longer, and more companies are just staying private, and we have moved to serving the private company market. We have, again, horizontal solutions that are very well-positioned in these private companies, whether private equity, whether they're financial institutions, whether they're fintech, something like Stripe, not talking about going public. We have a lot to offer companies that are staying private as well. We take you through the private to public journey. We sell before and after. We bring value and expand platform and portfolio within companies, account expansion, but we also serve the private company market today. Got it. I want to touch on the changes in go-to-market. You've been clear that you're going to surround yourself with a management team that's seen scale before, that's executed at scale. You had a head of sales there for many, probably 18 years or whatever, who got you guys to billion, so did an amazing job. You just recently brought in someone who you had experience with before, as a Chief Revenue Officer, who has that scale experience. How, if at all, has the go-to-market engine changed? Are there more changes to come? Are they potentially disruptive at all, or are we past that part of it because we've gone through sales kickoff? How is it different the way you look down into the pipeline? How is Michael Pinto managing things differently? Sure. Thanks for highlighting the new management team. We brought in three very senior leaders, very experienced leaders. Our CFO, Barbara Larson, has spent years at VMware and then a decade at Workday, even being CFO at Workday. She's very seasoned, has seen the scale. Brought in a CPO, Deepak Bharadwaj, who's been at Adobe for the last several years, and prior to that was at ServiceNow and scaled there with them as well. Michael Pinto, who, yes, was at Databricks for a few years and was at AWS for a number of years. All of them have seen the sub-billion to the multi-billion. Yes, definitely wanting those who've seen the movie before, know how to scale companies, know what it takes, understand the rigor and the discipline and the operating execution that's needed, both to have returns to shareholders from margins, but also taking those funds and putting them back into the company for innovation that we've been talking about, right? Michael Pinto specifically, he came in here and just looked at what we were doing, was very much in support of the strategy that we laid out at our last investor day. Lot of actions for operational efficiency and productivity and strength across staffing and structure and strategy. He is coming in not to do a hard pivot. He's been here six months now. No hard pivots, but really refinement of that model, building just a go-to-market machine that's needed for a company that's moving beyond the billion to the two and three. That's really what all of those leaders are doing. I wouldn't say there was a drastic change, but just an overall increase in the level of play in our go-to-market organization, which extends beyond his own sales and sales operations and commercial ops, across marketing and customer and partner success. Just great go-to-market experience building the sales machine. There's plenty of actions I can talk about around specifics, but we did lay those out in our recent Investor Day, and we'll talk more about it at Investor Day in Las Vegas for those who can join us at our customer conference coming up in September. We'll talk more about it and get a chance to meet three new executives who are here to propel us well beyond the billion which we hit this year. Yeah, exciting times. You also made some board member additions, too. We did make some board member- Including Scott Herren, one of my favorites, and phenomenal CFO, in my view, from Autodesk and Citrix and Cisco. Yes. We had a very small board. Good governance is you refresh in the right increments of time, and it was time. I love who we've brought on. We brought Astha Malik last year. In the second half of the year, she came on. She's the Chief Business Officer at Braze. Brings a world of experience and is living my life right now in SaaS, so really good operational execution. She scaled Zendesk beyond a billion. Then we brought Scott Herren, background at Cisco and Autodesk, right? Two CFOs, Scott Herren and Mark Peek, Mark had worked with Barbara, is a mentor to her, our CFO, even though she was the CFO of Workday. He's an outstanding add. Scott Herren is fantastic. All of them have navigated transformations in SaaS companies. All of them have scaled well beyond the billion into the multi-billions. All of them have navigated so many changes in the world around SaaS, just really mature, strong board members that will partner in the boardroom, that can navigate any and everything out there. I'm so excited. Thank you for bringing that up and highlighting it. Yes, transforming executive team. Big, strong additions to our board. We didn't just change and refresh, we actually expanded the board. Very exciting for Workiva as we move into this new era with innovation, strong leadership team, strength on our board to guide us in the right direction. Can't be happier with where we are today as a company. Got it. We only have 30 seconds left, and I've got a bunch of other questions, but I guess, so is there LLM activity in the financial suite right now? Do you actually see people piloting LLMs? It's so easy to spin up anything, right? Right. Yes, there's a lot of startup activity. Think about being a CFO in the enterprise into which we sell. Right. Where are you going to put your bets when you're looking at data and disclosures and capabilities? You have to report to regulators and investors. You need precision, and not only do you need precision, they're very probabilistic. They base their outcome and their numbers on patterns and on probabilities. We have a deterministic platform. We can prove that the numbers that you are reporting are accurate, they're traceable back to the source system. We can leverage all the data that you have in our platform from years prior. That's the difference. You hear the terms probabilistic, deterministic. Deterministic, LLM is probabilistic, but it's more than that. It's a safe place for the CFO to leverage AI. You know your outcomes are going to be, again, with data accuracy, data integrity, data consistency, and you can explain them to auditors. Auditors go into the platform. Yes, it's very easy to build software, but you need to have the moat, the advantage, the trusted customer base, the data, and the ability, of course, to prove that data is the right data and explain that it is. That's where Workiva shines. Data and narrative, deterministic. Great. Please join me in thanking Julie Iskow from Workiva. Thank you guys very much. Thank you, Rob. Really appreciate you being here. Likewise. Thank you all for interest in Workiva. So