Right. Cave, go ahead. Thank you. Good morning, everyone, and thank you for joining us today. My name is Cave Montazeri, and I'll be your host today. We have senior leaders from Bowhead Specialty here to discuss how technology and AI are being deployed by a leading insurance company. Bowhead has built a specialty carrier with both traditional craft underwriting and a growing digital model. What I'd like you to talk about today is understand why technology is changing the speed, quality, and economics of specialty insurance, and how investors should separate durable progress from broad industry noise. Our panelists today include Brandon Mezick, Head of Digital Underwriting. Brandon has almost 20 years of experience in specialty insurance with leadership roles spanning underwriting, operations, and business strategy. Brandon will tell us how Bowhead is using frontier technology to deliver low-touch underwriting process for SME E&S customers in construction and real estate, and how the company plans to scale this further. Also joining us today is Steve Feltner, who serves as Bowhead Chief Operating Officer. He will explain how technology can augment human underwriters in complex specialty lines where human judgment remains critical, but can be supported by better tools, data, and workflow design. Steve has 15 years of industry experience with a background that spans both technical and operational disciplines, giving him a broad perspective on the evolving needs of specialty insurance organizations. Last but not least, Brad Mulcahey, the Chief Financial Officer, will tie together practical financial implications and tell us why the company is excited about digital tools that did not exist when Bowhead just two years ago, but are now embedded in the company's daily processes. One little logistical note, please email me any questions you might have that we will have time at the end of this fireside chat to address or if you want, you can send me an IB on Bloomberg. Let's start with Brandon. For investors who may be new to the story, how do you define the difference between craft and digital inside Bowhead? Why do you have those two different platforms under the same roof, and where does technology create the most value in each model? Thank you for that question, Cave. First I'd like to maybe start by thanking you and our co-chair, Deutsche Bank for hosting us this morning. We're really excited to tell our story in a longer form. Thank you again for the opportunity. Maybe instead of starting with the differences, I'd start with something that unites both the craft and digital business, and that is our focus on underwriting profitability. That is the essential objective of Bowhead. It's at the core of everything that we do. To your question on differences, a simple way to describe it might be in craft our underwriters are making judgments that a model can't yet make reliably, where in digital decisioning is the well-defined, and we think speed and consistency improves the outcomes. In terms of technology and craft, the underwriters are synthesizing dozens of signals we get from submissions, from conversations with brokers, from conversations with customers that don't live in any kind of structured data set. In terms of the value technology brings, it's really about augmentation, giving those underwriters faster access to information like loss histories or the exposure information for a customer or benchmarking pricing data. It eliminates the friction around judgment. It does not eliminate the judgment itself. In terms of technology and digital, the risk parameters here are much tighter. The data is more complete, and we think the decisions then are more refutable. In terms of value in digital technology can be the underwriter. Humans obviously are in the loop for edge cases, and portfolio monitoring. I would note that these aren't two separate businesses that just happen to sit under one roof. The learnings and intelligence that we gain in each business informs how we think about the other. They really feed each other. Great. Bowhead's digital business today includes Baleen general liability for contractors and real estate, plus Express Cyber and miscellaneous professional liability. Why were those lines the right place to start? What makes them suitable for a more standardized workflow without compromising underwriting discipline? We were really deliberate about this. The lines that we started with, as you mentioned, primary general liability in Baleen and Cyber and MPL through Express share at least three characteristics that we think make them really suitable for a standardized workflow. The first is data completeness. For these classes, the data that we need to make sound underwriting decisions are largely available at the time of submission. We're not really dependent on broker narratives to fill in gaps. We've got structured exposure data, loss data, and in the case of cyber, great third-party security data that enriches the customer profiles we're trying to build. The second is a defined risk appetite. These aren't lines of business where we're trying to underwrite something unusual. We have a clear appetite, and those rules can be expressed in a way that a system can apply consistently. It's not dumbing down the underwriting. Instead, it's controlling discipline. The third is, we're building homogeneous portfolios. At the smaller end of the market, the exposure units are more comparable to each other. For us, that means that things like our pricing model can be more reliably calibrated over time as one example. I would just say that this doesn't You know, we're not compromising underwriting discipline because when done correctly, a rules-based workflow eliminates the adverse selection that can creep in when individual underwriters are applying slightly different standards to the same risks. To make that concrete, can you walk us through what a digital submission looks like today from intake to quote to bind? What parts of that process are not fully automated? What parts are low touch? Where is human trust still absolutely essential? Sure. It starts with intake. In both Baleen and in Express, most submissions are sent in the old-fashioned way, via email. The moment that email arrives, our systems do several things in parallel. They scan the applications and loss runs. They pull third-party data to enrich the information we have about a customer. Ultimately, that intake process yields a comprehensive customer profile that then gets compared to our appetite matrix. This is then when the process is probably diverged between Baleen and Express. In Baleen, if the account fits our appetite and doesn't trigger a referral, a pricing engine and the document engines fire off practically automatically. Quote documents and specimen policies are assembled, and those are sent back to the submitting broker without human intervention. In Express, all of that relevant underwriting information is presented on a single pane of glass to the underwriter. As I mentioned in my remarks yesterday, that underwriter's review is structured to take less than 15 minutes per risk. After their review is complete, both documents and specimen policies are assembled and sent back to the submitting broker. Here's where the processes converge again. If and when a customer decides to purchase, brokers visit a self-serve site to complete some compliance information. Once they click find and issue, we deliver a complete policy to their email in under five minutes. On the point about human intervention, we think it's essential in at least four places. First, in setting and updating the business rules that the system runs on. Two, in reviewing edge cases that the system might not be confident about. Three, evaluating risks that trigger those referrals I mentioned for things like loss activity. Fourth, for portfolio monitoring at the aggregate level. I would just say we think a lot about that workflow in the context of the experience we're delivering to brokers. We know brokers get especially frustrated when underwriters take a long time to even acknowledge their submission or offer any response. It's worse when an underwriter takes days to respond, asks a bunch of questions, and then ultimately declines the risks. Our brokers do not have those experiences. If a risk is out of appetite, we tell you. Most often we offer bindable quotes, and we do it quick. Thank you. Sure. Let's turn to Steve. On the craft side, how much of an underwriter's day is still consumed by lower-value administrative work rather than actual risk selection and broker dialogue? Have you already made the biggest gains in reducing that bridge? Thanks, Cave. Like Brandon, I'll just take this chance to thank you and Deutsche Bank for hosting this event for us. To answer your question, in craft, we think about this a bit differently than digital. We've deployed technology in our casualty unit around submission intake, data enrichment, and triage, but the objective isn't to abstract the work away from the underwriter. It's to set them up to do it better. The goal is a true single pane of glass. We want the underwriter to have everything they need in one place and not Google searching for basic information on an account. In digital, the technology often summarizes and streamlines decisions for speed and consistency. In craft, we take a different approach. We tee up the data and structure it, we preserve the underlying detail because these are more complex risks, the edge comes from the underwriter's ability to work through the nuance, not around it. While some might call that administrative work, we don't. In our view, that is core to sound disciplined underwriting, that's the balance we're after in crafts. Efficiency around the work, not simplification of the work itself. Building on that, as triage capabilities improve, where does the value show up first? Is it better time allocation, stronger quote-to-bind on the submissions you do touch or the ability to handle more top-of-the-funnel volume with the same team? For triage, you actually see the benefit in that order, and that sequencing matters. First it shows up in time allocation. The earliest and most immediate benefit of better triage is simply giving time back to the underwriters. You're cutting out the noise, meaning low quality or out-of-appetite submissions, so that they can spend more time on risks that actually warrant judgment. Second, you see it in the quote-to-bind quality. Once underwriters are more focused on quality accounts, the hit rate improves. They're quoting more quality deals that are better structured, better priced, and more aligned with our appetite. That's where you start to see real underwriting leverage come through. Third, only then does it scale capacity. With cleaner intake and more efficient workflows, the same team can handle more top-of-funnel volume without adding headcount. The goal is to see. For volume sake. Efficiency is nice, capacity is valuable, but better risk selection and stronger quotes to bind is what ultimately drives margin and long-term performance. Can you give us a concrete example of a process change or a technology enhancement that has made both measurably faster, more accurate or more efficient? Another one example of the craft side and one from the digital side. Sure. This is Brandon. I'll start with digital and then turn it to Steve for example in craft. The best example I can give you on the digital side is how we build the automation layer for Cyber Express. When we launched that business, we didn't start by telling that platform what to do. We started by watching what our underwriters actually did. We launched on a low touch basis for all risks, and behind the scenes we studied the underwriter's decisions, which forms they added or removed, which businesses they reclassified, whether they de-credited or debited a risk. Once we had enough data to see those patterns clearly, we encoded that into a rule set and then applied that to the simplest, most homogenous segment of the book where decisions were the most consistent. Those risks became fully automated. The more complex risks in Cyber Express stayed in a human's hands. I think this approach matters strategically because we know why the rules are what they are. We can update them when the environment changes, which it often does in cyber liability, and we have a baseline of human behavior to audit against as we move forward. Steve, you want to talk about examples in craft? Yeah, sure. I'll provide two examples, if that's okay. We recently deployed a tool to our underwriters that reads underlying policies, extracts and organizes terms and conditions, and presents the information in a clean, structured dashboard for the underwriter. Historically, this was an extremely manual process. Underwriters would spend considerable time reading through lengthy underlying policy documents to determine what coverage they were following, where exclusions or endorsements differed, and how the structure compared across carriers. That work is important, but it's also time intense. What the technology does is accelerate the understanding but not eliminate the judgment. Instead of spending hours locating and organizing the information, they can now spend their time interpreting the information and making better underwriting decisions. Also, I just mentioned a platform we use in our casualty unit for triage amongst other functionalities. Before committing to this platform, we ran a controlled pilot within our casualty team. One group of underwriters using the platform and another continuing in the existing workflow. After just one month, the results were clear in the data. Underwriters using the platform produced roughly 30% more quotes than the control group. The real insight wasn't just higher output, it was better allocation of underwriting time. Getting to a no faster allowed our underwriters to spend more time reviewing quality risks and engaging with brokers, which in turn generally leads to more submissions. Thank you. As a reminder, if you're on Zoom, you can raise your hand if you have any questions. If you're dialed in by phone, you can send me an email at cave.montazeri@db.com or you can send me an IB on Bloomberg. I'll take those at the end. Back to Brandon. One structural advantage Bowhead had from the start that you were building a new organization rather than inheriting decades of legacy systems and tech debt. In practical terms, what does that allow you to do faster today, whether that is launching products, adding data sources, changing rules, or integrating third-party tools? The short answer is yes to all of those. We think the advantage is real and compounding. When you build a modern modular tech stack from day one, without a legacy layer or trying to retrofit, we believe it sets a huge advantage. Every capability we've added has been additive and not a replacement of something that isn't working. Just working through some of those mentions. First on product launches. Once we complete the product design, which really takes a lot of time and requires extensive collaboration between disciplines, bringing a new digital product to market can happen in a few weeks rather than a few quarters in terms of the technology implementation. The infrastructure we have in place for things like intake pricing, issuance, data capture already exists. A new product is essentially a new configuration on top of that infrastructure plus some distribution work, which is really important. We usually start with a soft launch, to ensure that technology works as expected and to make sure there's a strong product market fit. The second is around data sources. As you mentioned, adding a new third-party data source is a days-long integration, not like a months-long IT project. It matters a lot because the data ecosystem for underwriting is evolving quickly. Things like new cyber risk signals are available. There are new financial health indicators that are available. All of that help with underwriting decision-making, and being able to plug those in quickly is a real advantage. Third, on rule changes. When market conditions shift and we need to update things like appetite or pricing, we can do that in the platform without messing with the underlying code. The underwriting team can change how we're treating a class or a geography and seeing it flow through submissions the next day. Ultimately, I think this is what the market has long chased. Without sacrificing underwriting quality. As I mentioned yesterday, most approaches have traded something away to get their large teams of low-cost labor, legacy systems being forced to do things they weren't designed for or asking people to work harder. Baleen was built on a different premise. Being a digital-first company means that one of our competitive advantages is organizational agility. We make decisions faster, we iterate on our models more quickly, and we have really strong alignment between claims, actuarial, underwriting technologists, product operations professionals. They share this common view of risk without the internal friction that might come with size. The carriers with the biggest budgets are playing a very different game. We are not trying to outscale them. We are, however, trying to outthink and out execute them in the markets that we've chosen. How do you measure if what you're doing is actually working? What are the most important metrics internally? Is it turnaround time, underwriting, underwriter productivity, buying rate, expense efficiency, broker adoption, loss performance, anything else? All of those. Yes. I would say the expense ratio that you mentioned, it definitely matters, and investors are right to focus on it. Internally, our view of technology effectiveness is a little more granular. We think about this across three dimensions. The first is maybe throughput and speed. Here we're measuring things like time from submission to quote, how often we're converting those quotes into binds, and how many risks are going straight through without human intervention. All of those are leading indicators on the platform's efficiency. The second dimension is the quality. Here we're looking at things like the accuracy rate on automated decisions. Here we measure those against what a senior underwriter might do if they reviewed that same file. We also look at things like the rate of midterm endorsements or corrections that we need to make, driven by data errors or early loss indicators on the digital book versus craft. Here, back to tech, back to quality. Technology just shouldn't be faster. We think it should also be more accurate. Third, the third dimension we focus on is broker adoption and friction. Here we're looking at things like the repeat submission rate of brokers and the speed that we're rolling out access across all of their networks of offices. If brokers aren't coming back, something about the experience isn't working, either speed or coverage or communication. We treat the way brokers are adopting us as a signal of the platform's quality. Maybe just to wrap this up, we do measure a lot. There are two metrics that I would highlight that define the broker experience, and that is speed and quotability. In the first quarter, as I mentioned yesterday, we responded to 75% of submissions within 15 minutes and 100% of submissions within one business day. We also quoted 75% of our new business submissions in the first quarter. To me, that means brokers are getting fast answers they can actually use. Great. Let's talk about financials now. Your, your expense ratio fell below 30% in 2025, outperforming your previous guidance of low 30%. You're now expecting the expense ratio to be below 30% in 2026. Brad, how should investors separate the benefit of scale from the benefit of actual automation? Thanks, Cave. I think if we back up a little bit, our older guide, if you will, was below 30%, so call it 31%-32% expense ratio. That came as Baleen had just started and Express was merely an idea at the time. That previous target of low 30% had some assumptions on continuing to scale. We're still early in the investment mode with digital and automation in general. We knew the digital strategy should be accretive to the craft expense ratio when it's fully mature. As we invested in the digital platform before the premium was earned, it actually added pressure to the expense ratio. Recently we've trended below 30%. In fact, it's 28.4% in Q1. As you know, we try not to overemphasize any individual quarter to look more at the longer term trend. This recent trend below 30% is mostly from the continued scaling and tech initiatives on the craft side. We're still in investment mode in digital, but already seeing the benefits of those early investments Steve and Brandon mentioned. In fact, I'd say our confidence in the digital strategy's impact on the expense ratio increases with each passing quarter. I wouldn't be surprised if we land well below 30% once digital is fully mature and up and running. Thank you. There's a lot of excitement around AI, but the practical question is where it can be trusted or where it still needs guardrails. As you think about Bowhead's roadmap, where do you see the most credible use cases for AI and advanced analytics? What governance standards need to be in place before these tools can play a more meaningful role in underwriting or claims? This is Brandon. I'll maybe start with some use cases in underwriting and turn it over to Steve to discuss the same in claims. Within underwriting, I think there's this continuum that we think about based on credibility or maybe said another way, how much the output can be verified. On one end, we see some really high credibility use cases. Those are things like document analysis, data extract and extraction, like reviewing submissions, processing endorsement requests, generating loss runs. In all of these cases, the output is verifiable. You can catch the error if they make one, and the efficiencies that you can gain are significant. In the middle of that continuum, there are some use cases that we think are best operationalized with guardrails. One example might be a chat-like interface or an internal tool set. Helping underwriters query the book or generate comparisons or even draft some endorsement language. Importantly, for all those use cases, the output is going through a human review before it gets implemented or before it affects that transaction. On the other end of that continuum, there are cases that we believe are least credible. An example there might be fully autonomous AI-generated terms on anything outside of a very narrow, rules-based digital context. I think the regulatory clarity over those use cases just simply isn't there right now. Steve, do you want to maybe share some insights on claims? Yeah, sure. If it's okay, I'll use a similar framework to Brandon, because claims like underwriting really operates along a credibility continuum as well. At the high confidence end, you automate aggressively. These are repeatable rules-based processes where speed and consistency matter the most. Examples in claims would be first notice of loss and intake and classification, acknowledgement communications, drafting standardized correspondence like coverage letters. These are areas where automation makes process fast and more consistent, without sacrificing judgment. In the middle, that's where AI becomes a force multiplier. Here technology is augmenting, not replacing the adjuster. Examples of this in claims would be, you know, risk and severity assessments, summarizing the incident key facts, supporting coverage analysis with relevant policy language. In these cases, the adjuster remains fully in the loop but is better informed and faster to act. Then there's some low credibility cases at the other end of the spectrum. These would be speculative use cases like, you know, AI predicting claims outcomes and autonomously paying or denying claims. Like Brandon said, you know, we don't view these as credible today. There's some regulatory hurdles to get through there as well, particularly in our complex specialty lines. In summary, I think our approach here is very deliberate. We automate where confidence is high, we augment where judgment matters, and avoid overreach where credibility just isn't there. Thank you. That's our question. Cyber, a very interesting line because the risk environments change very quickly, especially with the new development in AI. As you automate more of the smaller risk cyber workflow, how quickly does the technological feedback loop adjust to your risk entering the market? This is Brandon again. I think that's exactly the right question for cyber, and it's why the way we design the system matters enormously. We've addressed this in a few ways. First, the cyber appetite rules are structured in a way that they can be updated quickly. As I mentioned previously, underwriters can change a parameter overnight. When something like a new type of ransomware emerges, we're not waiting for an IT cycle to adjust eligibility criteria, for example. Second, we use cyber risk signals at intake that update in near real time. The risk assessment on a new submission always reflects current signals, not just what an insured reported on an application from 90 days ago. In a class of business where exposures can change a lot between application and bind, we think that really matters. Third, we're monitoring our cyber book continuously. If we see claim activity starting to cluster around a technology provider or a sector or industry, that triggers underwriting review. We have this continuous feedback loop between claims, underwriting and actuarial that ensures we're making any necessary adjustments quickly. Lastly, just on cyber, I appreciate that there are different views on cyber across the industry. Different views make a market. Some carriers avoid large risks because they typically experience the largest claims. Other carriers may avoid small or medium-sized risks because of concerns about the sophistication of their cyber defenses. At Bowhead, we're a market for cyber risks across the customer continuum. We have platforms to underwrite both small risks quickly, which were designed by expert underwriters, and we have platforms to evaluate large complex customers, which are handled directly by some of the best underwriters in the industry. We don't change the way we underwrite based on size. Our essential approach and standards for for things like eligibility are shared between craft and digital. Great. Thank you. Finally, my last question before we open up for Q&A. In specialty insurance, do you think technology becomes a true moat or do vendor platforms eventually make everyone look more similar? Where does Bowhead believe its real edge comes from? We think about this a lot. It's like the biggest long-term strategic question for us. I think the honest answer is, technology alone is not a moat. The combination of technology, data, underwriting expertise assembled and integrated over time is the moat, and that is really hard to replicate. Vendor platforms have done a good job of commoditizing certain activities like managing workflows or processing documents. I do hope that over the next five years, the baseline technology standard across the industry does rise. It's great if it does. It does not worry us. What vendor platforms can't replicate first is proprietary data. That proprietary data that we collect compounds every submission we process, every policy we bind, every claim we pay creates a feedback loop that informs how we evaluate and price the next risk. The second thing that it doesn't commoditize is the underwriting culture and decision-making framework that we've built and how our underwriters interact with each other and with the platforms. What type of risks they prefer, how do we use data to help with decision-making? That institutional knowledge is ours. The tools might be available, the underwriting judgment embedded in how you use them isn't. In summary, I would just say that our actual edge isn't any one piece of technology. Instead, it's a combination of decades of craft underwriting expertise and the technology infrastructure to scale it. Thank you. Operator, should we open it up with Q&A? Sure. We have a question from Scott. Scott, you should be able to open your line. Thanks, guys. Thanks for doing the call. Scott Barishaw from Deutsche Bank. I just wanted to ask about, you know, obviously the focus of the call is technology use and, you know, it's a couple things around where do you see Baleen being as a percentage of total premium. In the quarter, you guys did $11 million or so of premium, 300% increase. You guys do about $200 and change million of premium. Like, where can we think about this in the next couple of years? I looked at Cave's model. It's, you know, kind of goes up a little bit in percentage, like, you know, is there the possibility that this becomes a really, you know, bigger percentage of the total premium in the next few years? Scott, I would say yes. I wouldn't put any particular number on it. I would say that we expect the contribution to grow meaningfully. The drivers of that growth are real and durable. We're activating more broker relationships. We're seeing more submissions. We're expanding the product pipeline. I would say the 7% or so of total Bowhead GWP is our starting point and not our ceiling. Right. Like we've spent a lot of time with some, you know, very tech forward, you know, insurtechs where they're on, you know, thousands of brokers' desktops. Like, you know, how is that process going for you guys? Are there any holdbacks from brokers? Has there been any pushback from brokers, I guess, would be the question for Baleen? There hasn't, and I think one observation we made in our research and development phase was that brokers have portal fatigue. They do not like having to go to one or many portals to get one or many quotes. Their process, by and large, for the kind of business that Baleen targets is to, if you can believe it, send underwriters a submission via email. Our approach was to meet them where they are, but to work at the speed that those platforms, portals can deliver, which is why we're so obsessed with this 15 minute turnaround time, more or less in Baleen and Express. Yeah. No. I would also point out that the appetite of markets on most portals are limited. They might not have the same willingness to write hard-to-place customers in terms of nature of operations, venue or loss history. I think that's where some of the platforms struggle and where Baleen really fills a gap. I guess my final question is thinking about Baleen as a part of Bowhead, is that, you know, I mean, you guys have an iconic CEO in Stephen Sills. Like, can Cave and I go out and create, you know, Baleen? Like, are you guys at just such a advantage of being a part of, you know, such a, you know, unique company of Bowhead and having a CEO like that? Maybe talk about just sort of the benefit of being a part of Bowhead. I think Baleen has been able to see the success that we have because we're a part of Bowhead. I'm also happy to report that I think Bowhead is benefiting from the investments we're making in digital, as Brad mentioned. The way that we created Baleen within the company, I think is a really unique story. Stephen said, "I want you to effectively go on Mars to build this business." That approach, it sounds simple, but it is awfully hard to do in larger companies where there is a magnetic force to use what you have and to play by a certain set of rules. You're right, Stephen is an icon. He's a visionary. It's been incredible to build Bowhead and Baleen. I do think Baleen benefits from being a part of Bowhead and vice versa. Well, congrats on the success so far and look forward to seeing it continue. Thanks, Scott. If I may follow up on Scott's last point, can you talk about Express? Yesterday during the call, you did mention this kind of like positive feedback loop where Express is relying the craft business. You know, some business the craft business would normally do but couldn't do it because it was too small or not profitable enough. Also Express, I think it could help also get more broker mindshare in helping the craft. Could you maybe talk about that and give us a bit more details on that little feedback loop? The example that I used, that I give is, in previous versions of Bowhead, we would go and we launched our cyber offering. Initially, we were a market for excess and for large customers. We would walk into a broker's office because we're wearing the Bowhead jersey. 25 brokers show up to hear our pitch on cyber. When we say we can offer excess for large customers, I suspect we lost 30% of the room because they weren't handling excess for large customers. Our story and our pitch to brokers today is very different. We say, sort of like I did, we're a market for cyber. If you've got small risks, think of us. If you have large risks, also think of us. I think the message is simpler to brokers. I think it's more compelling, and we see the impacts of that in the craft submission numbers, which I think are being helped by the Express offerings and vice versa. It is sort of this halo effect that we're experiencing. I think it all has to do with the simplicity of the message, and how relevant our offerings are to brokers. Sally, do we have any more questions on the line? Not at this time. All right. Well, we got one question by email that I could address to Brad. Bowhead was founded in 2020 as a remote-first hybrid company. How did that shape the company's culture and the type of talent you've been able to hire? Do you think you have attracted employees that are more likely to embrace change and new technologies? Yeah, good question. I think if we go back to 2020 and you think about when Bowhead started and the world was sort of ending, the type of people that came on board early were that joined a startup in that environment were obviously highly entrepreneurial, thriving in change. That base was there. The person I would say that we hired, and I would say it could be called a builder, someone looking to make a difference, have an impact. We recruited a lot of people from larger organizations with really deep expertise, there was too much bureaucracy, not enough accountability at those organizations. That type of person obviously embraces new technology by definition. More recently, you know, we've been able to hire people who prefer our remote-first hybrid workplace over the return-to-office mandates that we're seeing out there. Obviously, this allows us to hire expertise regardless of their location. We trade large rent expenses for smaller travel expenses, and we still get together regularly. You know, the secret to our success, as Brandon mentioned, people that are remote, is applying that culture of expertise over the technology that we're building, especially on the digital strategy. The expertise we bring in on the craft business informs and perpetuates the digital business, which then culminates in a better broker experience in both craft and digital. We believe that better broker experience ultimately results in higher growth for the company. That was a great way to end this little panel. Brandon, Steve, and Brad, thank you very much for your time. Looking forward to keeping in touch. Operator, we're ready to close the Q&A. Thank you.