Conference Transcript - WAY 2026-06-02

Ryan Daniels, Analyst — William Blair

All right, everyone, let's go ahead and get started, please. Again, good morning. Welcome back to our session with Waystar. For those of you whom I've not yet met, my name is Ryan Daniels. I'm the healthcare IT and services analyst here. So very excited to have Matt Hawkins, the CEO of Waystar, with us for the second year, both at our conference and as a public company. Waystar is a great HCIT holding. It's one of our favorite names. It's a company that really sells into a marketplace we think has very strong demand for services as hospitals continue to face pressure and look towards trusted providers to help them both increase their margins and cash flows and to provide a better experience for their patients and their providers. It's an integrated offering, which we think is in demand, single contract, cyber secure, value added offering that's totally comprehensive. And really one unique thing we didn't even talk about a year ago is AI. And this is a company I think is really well positioned to benefit from that, not threatened by that. So it's offering new products. It's adding value to existing products, which helps with retention and cross-sales. And it's a company that sees an enormous outsourcing market that can move to in-source software as they continue to develop. So it's an expanding TAM, and we see accelerating growth going forward. So super excited to have Matt here to tell you a little bit more about this story. A couple quick housekeeping items. I am required to inform you that disclosures are available at our website at williamblair.com. And second, we'll head up to Richardson. That's on the second floor where we'll do the Q&A. So without further ado, I'll turn it over to Matt to talk a little bit more about the story.

Matt Hawkins, CEO

Appreciate it, Ryan. Thank you so much. Ryan basically just gave the story. So thank you for that kind introduction. I'm Matt Hawkins, and I'm the CEO of Waystar. I helped form Waystar with a fabulous team of people in the fall of 2017. And our hypothesis at the time was that provider organizations would absolutely need technology to simplify the way they get paid from both insurance companies and increasingly directly from patients. And so we formed Waystar then, and we were dreaming about the opportunities that we're seeing in the market today all the way back then. And so I look forward to introducing Waystar to you. I'm going to speak to what I assume is a crowd of some experts, healthcare experts, but also some non-healthcare experts and a generalist audience, if that's okay. And I look forward to following up in a potential Q&A session afterward and delighted to be more specific. But as far as overviews are concerned, let's jump in and get going here. Our mission is to use technology in modern ways to help create efficiency and reduce the friction in the payment process in healthcare, often referred to as the revenue cycle. A series of tasks and steps that historically have been done very manually, that increasingly is done with cloud-based software that deploys AI to automate work, to prioritize tasks and organize work, and ultimately to eliminate the need for human intervention altogether. And if we can do that, then the exciting future is that provider organizations will have more time to dedicate toward caring for patients and way less time focused on the administrative burden and trying to figure out how they're going to get paid. So it's a very exciting thing that we're endeavoring to do. We're at a critical inflection point in healthcare where we just need to change what happens. As you likely know, healthcare represents about 20% of the U.S. GDP as far as spend is concerned. And within that $4 trillion plus of annual spend, there's a tremendous amount of administrative burden. By most estimates, it's nearly half a trillion dollars of spend just trying to administer these increasingly complex provider organizations who have consolidated together, and you recognize many of their names. I'll speak to a few of them in a second. Hospitals are now joined with other hospitals. They either own or affiliate with physician networks, post-acute or non-acute sites of care, all in a single system. And they're all trying to get paid accurately in the face of real difficulty. They face staffing shortages. They face friction in the insurance claim submission process that results in annual denials being about 18% of every claim that gets submitted is initially denied by an insurance payer. That's a byproduct of the fact that there's all sorts of manual work that takes place, a lot of error embedded in that manual work. And consequently, sometimes providers don't get paid at all. So they're writing off services that they've performed that they're rightfully able to collect on as bad debt because they don't get paid. And or they're under coding claims so that they're not even accurately reflective of the health care occurrence or health service that has occurred. All the while, the backdrop is more and more patients in the United States of America are participating in high-deductible health plans or they're self-insured and they have to come out of pocket for their own form of payment. And provider organizations historically have not been equipped to deal with patient collections. So here comes Waystar to the rescue. Our vision and what we're working on building, and I'll tell you how we're getting there and it's very exciting, is a world where there's an autonomous revenue management platform that does work automatically, where the need for manual intervention is overcome through technology that generates insights, that learns through the processing of transactions that resulted in a successful outcome, and that connects providers to payers and to patients across the entire ecosystem where we ultimately create an outstanding experience for providers that enable those providers to care for patients very efficiently and also delight patients along the way. When you think about Waystar, knowing that this may be an introduction to many of you and a new story to many of you and a familiar story to some, we'd ask that you think about us as a cloud-native platform, a platform where we're deploying hundreds and hundreds of feature improvements and capability gains in a typical quarter to the million-plus providers that we serve. We offer market-leading AI solutions that are powered by the work that we do with Google Gemini. The more modern generative AI capabilities and foundation model solutions are powerful and we're seeing increasing adoption. In fact, 40% of our bookings in the first quarter of 26 came from modern AI native solutions. We're thrilled with that. And what's exciting is that as providers consume our platform, and I'll show it to you in just a moment, they're consuming AI on the platform in ways that are intuitive to them. As most of you know, AI capability is quite frankly ahead of where the human factor is in some cases. And so what prohibits adoption is, amongst some, is just figuring out where do I put AI in to do this task and how do I cyber secure it, how do I normalize the use of it in my work environment? We deliver a cloud-native platform that deploys AI to help bring that capability to providers in very intuitive ways that delight them, and we love that. Our solutions are mission-critical. We want you to know that. This is the true definition of mission-criticality. If you use our solutions, you get paid. if you don't use our solutions, your organizations don't get paid. And so when in the prioritization of all the things that providers have to grapple with and face, they tend to prioritize revenue cycle as a category and therefore our platform as a category because it's vital to how they operate. And we're bringing clarity and simplicity to their environments. We have proven and durable solutions and outcomes. And I'll show you an example of a few of those in just a moment. There's very little tolerance for error in a highly regulated industry like healthcare. You don't vibe code something overnight and then deploy it because of the tolerance for error is so low. The cost for being wrong is very high due to penalties and how you handle and manage data. and how that data ultimately is deployed to effectuate payment. We have a massive proprietary data advantage that I'll describe to you in just a moment. When you look at our platform and what we're building, we're very excited about our increasing market reach. We serve over a million providers, as I mentioned a moment ago, across more than 30,000 client organizations. We have fabulous diversification in our business. In fact, our top 10 clients account for about 11% of our revenue composition. We reach, through the providers that we serve, approximately 60% of the U.S. patient population each year. Now, we may only have, if you were to take a typical patient, they may have 10 healthcare encounters a year. We may only help a provider interact with one of those 10, but nevertheless, we're reaching them. We're helping to facilitate and optimize an interaction between provider and patient that we know statistically delights both. Within our software, we're processing one out of every three clinical patient discharges from an acute setting in the United States. So in addition to the more than seven and a half billion insurance transactions we process each year that constitute nearly $2.5 trillion of gross claim charges, we get tremendous clinical information that we're able to use. Because we're a covered entity and we're a modern network, we naturally aggregate information as it flows and passes through our system. And that proprietary data gives us the right, we're able to use that data in most cases to be able to train our software, train the AI models that we deploy to continuously improve. You can see our software is a workflow platform. It's a cockpit, if you will, organized from the front end of the experience that maps a patient's journey interacting with the provider to the clinical middle part, to the back end reimbursement and collection and payment remittance part. We have software modules that basically reduce the need for manual work, beginning at the front end through things like insurance eligibility detection. We help providers understand whether or not a patient has any form of insurance. We also can detect insurance coverage for a patient if they show up to see a provider and they may not even know if they have access to insurance. There's something very noble about that. We also, understanding the patient's wherewithal and insurance, we run things like propensity to pay algorithms in the background. so we help the provider understand who that patient is. For example, a patient may have the wherewithal to pay, but they may have been conditioned to not pay their health care bill the first time they see it, and so we help educate the provider who the patient is. If the patient is a self-insured case or a self-paid case, we also can help the provider understand if that patient's eligible for charity care, and if they're eligible for charity care, the provider sees the patient. And then the cost of that service is often added to a charity care dollar amount that the provider's performing each year. And they typically get a tax credit or some favorable treatment by the government for caring for that patient. So it's all a net good thing. When you move to the middle part of our business, that historically very difficult part of the accounting or reckoning for the healthcare interaction between a provider and a patient, when the provider sees the patient, then they have to document what they actually did so they can accurately account for and form an insurance claim and then submit that claim to the payer and get reimbursed for it. What's interesting is we have AI. In fact, we deploy over 150 AI models beginning at the front end of that clinical interaction between provider and patient, oftentimes taking unstructured clinical information from the patient chart as either notated or scribed by the provider. Then through filtration, we're able to, on the other end of that middle part of the revenue cycle, accurately account for the diagnostic codes used that reflect the encounter that the provider had with the patient. Use those diagnostic codes in the formation of a highly accurate claim. You can see where this is going, right? Historically, that was done very manually. So sometimes there was missing charges or codes. Sometimes it wasn't accurate at all. Sometimes there was over-coding. And so what our software using AI does is create an accurate reflection of the encounter that then we use to create the perfect claim that cannot be denied. And when we do that, we reduce the need for manual work, manual rework, or errors tremendously. And we help drive to accurate payment quickly. In the minds of provider decision makers, our software helps address four things. The first is we help reduce the overall cost to collect. Historically, the average in the industry is about anywhere from six to seven percent, where 10 percent of that is software, let's say, and 90 percent of that is human labor. What we do inverts that, where we can say 80 percent of that should be addressable with technology, 20% of that could be keeping an expert human in the loop to monitor the progress while we lower the cost to collect. The second thing is we also drive to more accurate payment. That's what providers want. That's what payers want too. And that's what patients want. And through the use of technology, smart technology, we're running algorithms to test and detect across the seven and a half billion proprietary data points that we process each year on our platform to help the provider understand, yes, this is an accurate combination of codes that can be used to submit a claim. The third, of course, is to compress the time to payment. And statistically, as I'll show you in a moment, we do just that. Fourth, of course, is the need for a cyber secure working platform and a solution. The penalty for not being cyber secure is very high. And we take our cyber posture very seriously in a world of bad actors. We're mindful and try to be dutiful. And increasingly, as we interact with provider decision makers, as they see our software platform, they ask us to attest for cybersecurity because of the demand and the need for that throughout their organizations. We often displace point solutions. A point solution might be represented by any one of those small plus signs toward the bottom. But when we deploy our software and we show up in a competitive environment, we often talk about the benefits of using more and more of our platform and expanding the relationships with clients over time as we displace point solutions historically. We believe that there are at least four pillars that enable Waystar's right to win in AI. First, we have a mission critical system of record and system of action that drives to real outcomes in the reduction of costs to collect, in the optimization for yield on each insurance claim we process and the compression of time to collect while being cyber secure. And we're doing it at scale. We also have an unmatched proprietary data advantage, giving the massive data that we custody and curate and are able to use in HIPAA compliant ways to drive decisions, to create optimized tools that help providers, and to reduce the need for manual work. And imagine in your minds, there's a lot of talk about AI today. Imagine that if everybody's using a foundation model at the same pace, then what foundation model use doesn't become the long-term advantage if we're all using foundation models. There's a symmetry at the pace at some future point. So the advantage has to become something else. We believe that proprietary data is at the heart of our advantage. We also have a very deeply deployed network. And by that, I mean, we're deployed across over a million providers who reach to every insurance company in the United States. And we connect to all the different, more than 530 different practice management and electronic health record systems. deeply deployed, hard to displace or disrupt because of the value that we're creating for the providers that we serve. And we have domain expertise that act as forward deployed engineer equivalents that are constantly sitting chairside next to the provider or team members doing work in the revenue cycle to optimize the experience and to ideate around the future of what's possible. You can tell I get pretty excited about this. But where the industry's headed is from a traditional RCM on the left, which is often siloed set of information, disparate data points, to a more organized, unified RCM in the middle, where now you have a cohesive platform. You have access to data that you can unify to begin to draw insights from, as I've described, to optimize your insurance coverage detection process at scale, to optimize your prior authorization automation, and understand when you need to include medical necessity-based justification to the payer along the way, et cetera, et cetera. So this is shared intelligence, shared data to create insights and opportunities, and orchestrate what AI should be used at what moment in time, not all AI is created equal or necessary. Foundation model AI is very expensive. The cost of tokens are very expensive. And in some cases, you need to deploy foundation models to be able to derive the benefit that you're trying to achieve. In other cases, depending on how your data is organized and ours is organized in a cohesive platform, a unified data model, you can actually deploy a much more cost-effective, instead of large language model, small language model on a look at data and manage the cost and orchestrate to bring the right AI to the right use case. Ultimately, deploying agent after agent. And Waystar, as I've said earlier in the year, we're committed to deploying multiple agents through the course of 26 and beyond. We're marching our path toward the autonomous revenue cycle management platform. And at some point, we'll do away with the term cycle, and it will just be the autonomous revenue management platform. Work being performed, oftentimes without an end user even knowing it, behind the scenes, while the organization, the patient as the individual and the payer all get the benefit from that type of platform. We believe that this is the way of the future and that Waystar is well-positioned to march our way toward that. We deploy a number of agents already, as you've heard me describe, and algorithmic and AI capability. But imagine even further orchestration as we work our way into the use of more proprietary, well-organized data to look beyond the platform level and the user interface to the orchestration level and then down to utilize proprietary data where agents are benefiting from every transaction we process. They're getting smarter and smarter from front, middle, and back of the revenue-generating experience. Again, data in healthcare is a long time and persisting challenge. data tends to be very siloed. You could go back 10 or 20 years and you might say, and we work with 16 of the top 20 hospitals and health systems in the United States and nearly 2,000 hospitals overall. But the vast majority of our clients operate outside of hospitals too. They operate in ambulatory settings, 10, 20 doc practices, so to speak, orthopedic surgery groups, primary care physicians, post-acute and non-acute sites of care. You can probably picture in your mind where historically data has been very siloed in these entities. Tough to aggregate. Therefore, it's tough to create insights and tough to know if you're working in a primary care physician group on the West Coast, how do you get insights from the insurance interactions of a primary care group operating in the Midwest or in the southeast or the northeast. And because data has historically been siloed, it's been very tough to drive those insights. The nice thing about Waystar is, again, we have the right, given the fact that we are a covered entity, and we're able to traffic in this information to appropriately and carefully custody this information, combine it with the clinical, administrative, and financial information we use to then unlock unprecedented automation, unprecedented insights, and unprecedented outcomes for the clients that we serve. We're going after a large and addressable market. Historically, you'd say, well, this is about a $20 billion a year market becoming a $25 billion dollar a year market. The midpoint of our guide in 2026, from a revenue perspective, is just shy of $1.3 billion. So we're a sizable business and growing into this addressable market opportunity. But we see even more addressable market opening up. If you were to look at the amount of dollars being spent for services being performed inside hospitals, health systems, and throughout the country in these ambulatory settings, there are market estimates that it's nearly $100 billion plus of annual spend. If we can deploy AI and modern capability that can eat into and displace the need for those services to occur altogether, we dramatically enhance the addressable market opportunity in front of us. And we're very excited about what we're seeing and what's on our roadmap to track toward that much larger adjustable market. We're grateful for the clients that we serve. These are market-leading institutions that operate, as you can see, in every care setting across the United States. We don't work with any clients outside the United States today because there's so much opportunity within the United States to drive improvement. In addition to all these clients, we also work with a number of channel partners. As I mentioned, there's over 530 integrations that we support, and of those 530 integrations of practice management and EHR systems being used across the country, we support over 200 active channel partner relationships who give us the right to call into their practice management or EHR clients and then begin to use Waystar in coordination or as a linchpin to help those providers get the full benefit of our modern solution. We also work with the outsourcing firms that you may recognize listed on the lower right-hand part of the page. Our platform drives meaningful impact. As I mentioned a moment ago, we're helping to reduce the likelihood that a claim gets denied. In 2025, after launching a brand new AI-based solution, in 2025 alone, we help prevent nearly $16 billion of denials. We bring financial visibility to providers who desperately need it to operate their organization successfully. Our first-pass claim acceptance rate across the billions of insurance transactions we process is nearly 99%, meaning the payer accepts the claim and is able to begin to adjudicate that. And if we know that statistically, we can do a bunch of analytics and create insights that would inform, oftentimes pre-service, what the likely patient financial responsibility is or will be, and empower the provider and the patient with that information through software and AI capability that we have. We're creating, we can deploy our software very rapidly, so there's a rapid time to value benefit. It's leading to quicker payments and increased revenue to provider organizations. And that's how we compete in the market. We have strong win rates, and we've had record bookings quarters. In Q4 of 25, we had an all-time record booking quarter for us, inclusive, for those that know our story, of the period of time where we had a competitor that was cyber attacked and we helped several thousand providers begin to use Waystar in early 2024. So we're seeing demand and the four demand indicators for our business are high given the meaningful outcomes that we drive. We're delighting clients. We're pleased with that. We're market leaders in positive net promoter scores. A net trusted brands in the world. We are ranked first in the industry in satisfaction. And in a day and age where people are desirous to use AI, but they want to use it in trusted ways, client trust really matters. And so we're grateful for the recognition and acknowledgements that we're receiving along these lines. I just would highlight as I close that we had strong Q1 performance at the start of the year, 22% top-line revenue growth, 26% adjusted EBITDA margin, excuse me, adjusted EBITDA growth, and 43% adjusted EBITDA margins. We generate cash that we use to build our balance sheet and gives us tremendous optionality to invest in the business, to smartly deploy our capital. And we have fabulous retention rates. And the last thing I'd highlight is as we look at the growth drivers for our business in the future, we feel like we have a track record of expanding within existing clients, adding new clients every quarter, deploying and launching new AI solutions that show up in meaningful ways to our business model, reaching the market through expanding channel partner relationships and adding incremental payer connections to our business with new novel interaction types. And then certainly on occasion through being very disciplined in our approach to strategic M&A, we believe we can be a great home for some novel technologies that we could tuck in and add to our business. So we're excited about this. And I thank you very much for your time today. And I look forward to those of you that have questions in the follow-up session. Thank you, Ryan, for hosting me. Yeah, I appreciate it.