Good afternoon, welcome to Box's fourth quarter and fiscal year 2026 earnings call. I'm Cynthia Hiponia, Vice President, Investor Relations. On the call today, we have Aaron Levie, Box Co-founder and CEO, Dylan Smith, Box Co-founder and CFO. Following our prepared remarks, we will take your questions. Today's call is being webcast and will also be available for replay on our investor relations website. Supplemental slides are now available on our website. On this call, we will be making forward-looking statements, including our first quarter and full fiscal year 2027 financial guidance and our expectations regarding our financial performance for fiscal 2027 and future periods, including gross margins, operating margins, operating leverage, future profitability, net retention rates, remaining performance obligations, revenue and billings, net tax benefits, and the impact of foreign currency exchange rates, and our expectations regarding the size of our market opportunity, our planned investments, future product offerings, and growth strategies, the timing and market adoption of and benefits from our new products, pricing models and partnerships, our ability to address enterprise challenges, enhance our product capabilities, and deliver cost savings for our customers, the impact of the macro environment on our business and operating results, and our capital allocation strategies, including potential repurchase of our common stock. These statements reflect our best judgment based on factors currently known to us, and actual events or results may differ materially. Please refer to our earnings press release filed today and the risk factors and documents we filed with the SEC, including our most quarterly report on Form 10-Q for information on risks and uncertainties that may cause actual results to differ materially from statements made on this earnings call. These forward-looking statements are being made as of today, March 3rd, 2026, and we disclaim any obligation to update or revise them should they change or cease to be up to date. In addition, during today's call, we will discuss non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to, and not as a substitute for or in isolation from our GAAP results. You can find additional disclosures regarding these non-GAAP measures, including reconciliations with comparable GAAP results in our earnings press release and in the related supplemental slides, which can be found on the IR page of our website. Unless otherwise indicated, all references to financial measures are made on a non-GAAP basis. Finally, please see our earnings deck, again posted on our IR website, for a more detailed look at our Q1 and full year 2027 guidance. Thank you. Let me turn the call over to Aaron. Thanks, Cynthia, and thank you all for joining the call today. We delivered strong Q4 operating results reflecting continued growth in customer demand for Box AI and the success of our Enterprise Advanced offering. We achieved revenue of $306 million, up 9% year-over-year or 8% in constant currency, and Q4 EPS of $0.49 above our guidance. In fiscal 2026, we drove revenue of $1.18 billion, up 8% year-over-year with operating margins of 28%. It was a defining year for Box as we executed on the launch of Enterprise Advanced, which brings together our most powerful capabilities around intelligent workflow automation, advanced AI, and secure content management to enterprises. Enterprise Advanced customers have reached 10% of revenue, and we're incredibly excited about this early traction and continued momentum. Examples of Enterprise Advanced customer wins include a leading biotech company uses Box to manage large volumes of commercial documents but currently relies on manual searches to find key information. By upgrading from Enterprise Plus to Enterprise Advanced, the company will use AI-powered data extraction and integrated Box Apps to surface critical commercial data directly from documents. Next, a leading global robotics company uses Box as the core platform for its revenue operations and content workflows. The company upgraded from E Plus to Enterprise Advanced to streamline quote creation and approvals with Box DocGen, Box Sign, and Box Apps to increase throughput and reduce errors. They also plan to apply metadata extraction and OCR to financial and legal documents to automate data capture and better manage contractual risk. To understand what's driving the momentum with Box, it's important to think about the criticality of enterprise content when it comes to driving transformation with AI. Nearly every enterprise leader that I talk to today is looking to transform how their company operates with AI. They're looking to accelerate tasks across their organizations, ranging from reviewing legal contracts and doing financial analysis to accelerating pharma research and spreading expertise across their organization. They quickly find that for AI agents to be effective in a workflow, agents need critical context about their business. They need to understand the company's product roadmap, marketing strategy, HR policies, internal best practices, planning insights, strategy decisions, and whatever else makes that business unique. Much of that unique context lives inside of enterprise content, ranging from contracts and financial documents to research documents and marketing assets, all housed inside of PDFs, documents, media assets, collateral spreadsheets, and markdown files, and more. All of this enterprise content is the digital brain of an organization containing the most important insights precisely because of their unstructured nature. Files provide a universal way to create, capture, and share information between systems and people, which is why the growth of content continues to explode. The vast majority of this data, which makes up 90% of corporate data, has been underutilized until today. Now AI agents can finally help us tap into this critical business information and use it to accelerate knowledge work that previously could never have been automated. As we prepare for a world where there will be a hundredfold more agents inside of an enterprise than people, we will equally see incredible growth in unstructured data. Files are quite simply the native unit of work for agents. Age nts use files to keep track of their work. They leverage files as context about the tasks that they're doing and use files to share back and forth with their human counterparts. As AI agents help us augment all of our work across industries like pharma or financial services, legal and healthcare, or the public sector, these agents will need the same level of security, data governance, auditability, logging, and access controls that we've required for people in the enterprise. As we've seen with the growth of products like OpenClaw or the launch of Claude Cowork and others, agents may spin up countless sessions and will need their own secure file systems and sandboxes while also being able to easily collaborate securely with other people and agents. Thus, to have an effective AI agent strategy, companies fundamentally need a content strategy. They need a secure platform to manage critical content and ensure it can connect to all of their people, agents, and applications. This is what we're building at Box with our intelligent content management platform. FY 26 was another fantastic year of product innovation and momentum to ensure that we stay ahead of the market and power our customers' most critical content workflows with AI. Just in the fourth quarter, we announced the general availability of Box Extract, enabling enterprises to intelligently and securely pull the most valuable information from content and save it as metadata in Box, all powered by leading AI models. W ith Box Extract, companies can turn their documents into data, pulling out the structured data from contracts, invoices, marketing assets, research, financial documents, and any other file type to automate workflows or glean critical insights in their business. In Q4, we also rolled out Box Shield Pro, a powerful new add-on that expands on existing Box Shield content protection and leverages agentic AI to bring new levels of scale, speed, and automation to advanced security controls. We are also incredibly proud to have served as an early launch partner for Anthropic's Claude Opus 4.5 and Opus 4.6 releases, Google's Gemini 3.0 Flash, and OpenAI's GPT 5.2, all available in the Box AI Studio. These are many of the foundational elements in our intelligent content management platform that we delivered in FY26. Looking forward, in FY27, we will be delivering the next generation of AI agent features within Box, enabling AI agents that can do more long-running tasks and advance work on enterprise information. Soon, you'll be able to give AI agents complete projects, and they will go off and work through your enterprise information to complete those tasks, powering everything from writing out complex RFPs to analyzing your contracts to and generating a new one with the most relevant clauses. We are also building the most advanced AI-powered workflow automation capabilities with enterprise content. We will keep rapidly enhancing Box Extract to support even more complex document processing use cases. With Box Automate, which will launch in the first half of this year, customers will be able to combine human and agent-powered workflows to automate any content business process in an enterprise. Combined with new features in Box Apps, we will deliver full no-code business workflows from contract management to digital asset management and more. Throughout FY 27, we will continue to advance our functionality across Box Shield to enable more intelligent threat prevention and data classification with new Box Zones sites for enhanced data residency, Box Governance to power deeper lifecycle management features, and new functionality to help improve the security of AI agents in Box. This is going to be a major year for the Box Platform APIs. Catalyzed by the rise of AI, enterprises will need to further centralize their enterprise content and connect a single source of truth of content to their people, agents, and applications. The same contract that an agent produces, a user may want to review inside of an end user application and may want to show up inside of Salesforce or a custom app. The same is true for every other type of enterprise content, from marketing assets to financial documents. To support these growing AI use cases, we're making it as easy and secure as ever to leverage Box as a platform to integrate content across the entire AI stack, like Claude Cowork, Copilot, IBM watsonx, ChatGPT, or custom agents that our customers build by leveraging Box's APIs, MCP server, and CLI support. We're incredibly excited about this new array of use cases for the Box platform to be used as the file system for agents. We will monetize this through either end user seats that interact with these agents or API and AI unit consumption when our platform is connected to these agents in a headless fashion. We are covered either way. Now, turning to go-to-market. As I've noted, we are incredibly excited about the momentum we're seeing with Enterprise Advanced. Across industries like financial services, legal, life sciences, and in the public sector, including other key industries, we're seeing growing momentum for enterprises to adopt Box's most powerful set of capabilities. With Enterprise Advanced customers now reaching 10% of revenue and driving an acceleration in our top-line metrics. Our partner business also remains a critical part of our strategy as we deliver more advanced solutions for customers. In Q4, we saw continued momentum with key partners. A large government regulator that selected Box Enterprise Advanced as the content layer for regulatory case management. Working with a global systems integrator, Box replaced a legacy system enabling secure document intake, high volume review, and AI-assisted classification integrated into core case systems, positioning Box as a foundational platform for the organization. Next, a global insurance organization upgraded to Enterprise Advanced as part of a legacy ECM modernization led by our partner, DataBank. Box AI now processes insurance policies and related documents at scale, extracting key data from large volumes of policies and endorsements to support underwriting and quoting, reduce manual review, and improve operational efficiency. Given the strong results we saw in FY 26, and especially through the tail end of the year, in FY 27, we believe it's critical to continue to strategically invest to build on this momentum and ensure we're capturing this market opportunity. We will continue to invest in our critical growth verticals with go-to-market capacity and marketing efforts. We're bringing the full power of Box's Enterprise Advanced plan to customers through Box's solution offerings in key lines of business and industries. We're accelerating growth in large enterprises by deepening partnerships with major SIs like Deloitte, Slalom, TCS, DataBank, and more. We're driving growth with key cloud marketplaces like GCP and AWS, and much more. You will hear more about these go-to-market initiatives at our Financial Analyst Day in two weeks. As we enter a new era of work that is defined by AI agents, we are confident in the power that enterprise content plays in powering an agentic strategy in organizations, and that enterprises will need a secure platform to connect their most important enterprise information to their people, agents, and applications. At Box, our opportunity has never been larger to transform how companies work with their content. We are entering FY 27 with the strongest momentum I've ever seen as we become the platform that powers intelligent content workflows and automation in the enterprise. With that, I'll hand it over to Dylan. Thanks, Aaron. Good afternoon, everyone. Q4 capped off a year of strong execution against the three financial priorities we outlined heading into the year. First, we set the stage to accelerate top line growth by investing in key go-to-market initiatives and enhancing the AI capabilities of our intelligent content management platform. Second, we generated efficiencies across the business by advancing our AI-first efforts and workforce location strategy. Finally, we executed on our disciplined capital allocation strategy, reducing basic shares outstanding by more than $3 million over the past year. In FY 26, we delivered revenue of $1.18 billion, up 8% year-over-year and up 7% in constant currency. We drove an acceleration in RPO growth to 17% year-over-year, or 16% in constant currency. Operating margin came in at 28.3%, up 50 basis points year-over-year, and up 40 basis points in constant currency. Finally, in FY26, we generated record free cash flow of $313 million, up 3% year-over-year. Turning to Q4, we closed the year with very strong results exceeding our guidance across all metrics. We delivered Q4 revenue of $306 million, up 9% year-over-year and up 8% in constant currency. This represents our third sequential quarter of accelerating revenue growth driven by strong AI and Enterprise Advanced momentum. Customers paying us at least $100,000 annually grew 9% year-over-year. After launching Enterprise Advanced as our highest tier suite just a year ago, Enterprise Advanced customers already account for 10% of our revenue. The intelligent workflow automation, advanced AI, and secure content management that this plan offers are clearly resonating in the market. Over the past year, price per seat for Enterprise Advanced customers have commanded an average pricing uplift of 30%-40% over Enterprise Plus at the high end of th e 20%-40% uplift we had initially anticipated. Going forward, we expect this 30%-40% uplift to continue. Total Suites customers now account for 66% of our revenue, an increase from 60% a year ago. We ended Q4 with remaining performance obligations or RPO of $1.7 billion, representing 17% year-over-year growth or 16% in constant currency and providing us with greater visibility into future revenue. Short term RPO grew 12% year-over-year, both as reported and in constant currency. Our strong RPO growth continues to benefit both from longer contract durations and from mid-contract upgrades to Enterprise Advanced. We expect to recognize roughly 55% of our RPO over the next 12 months. Q4 billings of $420 million were up 5% year-over-year and up 4% in constant currency, ahead of our expectations of low single-digit billings growth. This outperformance was driven primarily by strong Q4 bookings. We ended Q4 with a net retention rate of 104%, up from 102% in the year ago period, driven by continued improvements in both pricing and net fee expansion trends. We expect our net retention rate to remain at 104% in Q1 and to land in the range of 104%-105% at the end of FY 27. Q4's gross margin was 82.3%, exceeding our guidance of 82%. This represents an increase of 130 basis points year-over-year. In Q4, we continued to drive cost discipline across the business, delivering record Q4 operating income of $94 million and operating margin of 30.6%, exceeding our guidance of 30%. In Q4, we delivered EPS of $0.49, well above our guidance of $0.33. This includes the benefit from several tax items, which reduces our effective tax rate in FY26 and on a go-forward basis. Excluding these tax benefits, EPS would have exceeded our guidance by $0.02. I'll now turn to our cash flow and balance sheet. In Q4, we generated free cash flow of $98 million and cash flow from operations of $110 million, up 7% and 8% year-over-year, respectively. We ended Q4 with $480 million in cash equivalents, restricted cash, and short-term investments. Our balance sheet reflects the cash settlement of debt principal related to our $205 million of 2021 convertible notes that matured on January 15th, 2026. In Q4, we repurchased 4.4 million shares for approximately $126 million. For the full year of FY 26, we repurchased approximately 9.7 million shares for approximately $293 million, representing more than 90% of FY 26 free cash flow generation. As of January 31st, 2026, we had approximately $59 million of remaining buyback capacity under our current share repurchase plan. With that, let me now turn to our Q1 and FY 27 guidance. Please note that approximately 40% of our revenue is generated outside of the U.S., with approximately 65% of this international revenue coming from Japan. Note that our FY 27 guidance reflects a lower expected GAAP and non-GAAP tax rate benefiting EPS. For the first quarter of fiscal 2027, we expect Q1 revenue to be approximately $304 million, representing approximately 10% year-over-year growth or 9% in constant currency. We anticipate our Q1 billings growth to land in the low single digits, which includes an expected headwind from FX of approximately 530 basis points. We expect Q1 gross margin to be approximately 81.5%. We anticipate our Q1 operating margin to be approximately 27.5%, up 220 basis points year-over-year. We expect Q1 EPS to be approximately $0.36. Weighted average diluted shares are expected to be approximately 141 million. For the full fiscal year ending January 31st, 2027, we expect our full year revenue to be approximately $1.275 billion, representing 8% year-over-year growth or 9% in constant currency. We expect our FY 27 billings growth rate to be roughly in line with revenue growth. This includes an expected headwind of approximately 100 basis points from FX. We expect FY 27 gross margin to be approximately 81.5%. We expect our FY 27 operating margin to be approximately 28% or 28.5% in constant currency. As we have discussed previously, given the momentum and demand we are seeing for Box AI and Enterprise Advanced, we are continuing to invest in strategic go-to-market initiatives to ensure we can reach customers at this critical technology juncture. We will continue to drive operating efficiency through cost discipline, AI-driven efficiencies, and our workforce location strategy, and we remain committed to delivering significant margin expansion over the next few years. As it relates to FY 27 expense and margin seasonality, please note that our annual customer conference, BoxWorks, will take place in Q4. This will shift approximately $3 million in expenses from Q3 into Q4 as compared to FY 26. We expect FY 27 EPS of approximately $1.55 or $1.58 in constant currency. Weighted average diluted shares are expected to be approximately 141 million. In the era of AI agents, Box is powering the full life cycle of content in a single platform with native enterprise-grade security and AI capabilities. Our strong results in fiscal 2026 demonstrate the success of this strategy, including an acceleration in our PO growth and an improvement in our net retention rate. In FY27, we will continue to invest in a robust product roadmap and strategic go-to-market initiatives, delivering accelerating revenue growth and higher operating profit. We look forward to providing more details at our Financial Analyst Day later this month. With that, Aaron and I will be happy to take your questions. Operator? Thank you, sir. Ladies and gentlemen, if you have a question today, please press star one on your telephone keypad. Once again, that is star one if you have a question. We'll take the first question from Steven Enders, Citi. Okay, great. Thanks for taking the questions here. I guess I just want to start on the opportunity first for that you're maybe seeing from AI, and just how do you think about how the changes in the Gen AI landscape maybe impacts the content layer and what this looks like moving forward with agentic AI? Thanks for the question. We're, as you can tell on the, on the, you know, kind of remarks, we're unbelievably excited around the role that content plays in any kind of agentic system. There's a few different ways that this will show up. The first is we actually expect to see a major rise of, you know, software in general being generated through AI. If you just imagine that there's a dramatic increase in software that enterprises build, I don't 100% agree with the thesis that they'll build, you know, kind of existing internal systems, but kind of almost independent of what you believe, there's gonna be, you know, vastly more software produced in the future, sometimes bespoke software, sometimes just more companies. For really any kind of enterprise use case, the second that you need some form of unstructured data inside that software, it could be a contract management system, it could be a pharma workflow, it could be a financial services onboarding system, it could be a client portal, all of those systems are gonna need a secure place to be able to store the unstructured data that goes into that system. The first piece is more software is just good for us because all of that software needs to eventually probably touch some type of unstructured data in an enterprise context. Probably the bigger play is, as you have more and more agents doing work for us, and we've seen a few examples of agents kind of break through recently, the Claude Cowork agent, the OpenClaw agent, these are great examples of agents that are doing kind of general purpose knowledge work. If you imagine the general purpose knowledge work that most people do through their day, if you're a lawyer, you're looking at contracts, if you're in banking, you're looking at lots of financial reports, if you're in, if you're in pharma, you're looking at lots of both research and, you know, kind of information coming in from lab tests, all of that is unstructured data. To now replace a person with an agent in that example, agents will need that exact same data to work with. They're gonna need the right contract to look at, they're gonna need the pharma research to touch, they're gonna need to be able to, you know, comb through financial information, the enterprise is gonna want a secure way to govern those workflows and govern the data that goes into them. If you imagine, you know, one of the kind of increasing architectures emerging is these agents that have their own computers that they get to work with. Well, the computer will to some degree be stateless at some point. Like, you know, it might disappear in a week or a month or a year from now, but what can't disappear is the data that that agent worked on. If you're in a regulated industry, you need to govern that data. You need to be able to have audit logs. You need to be able to have a place where you store and, and can go do discovery on that information. The part that actually has to keep state forever, you know, up to the, up to the point that the customer, you know, cares about working with the data is the information that that agent worked with. We really imagine a world where let's say you have, you know, 10 or 100 or 1,000 times more agents in an enterprise than people even, they will need to do work on this unstructured information. Importantly, when they do that work, oftentimes an end user will actually need to see the results of that work or go back and forth with the agent. Fundamentally, there needs to be some type of shared file system for them to be able to do that work. That's why we, are in a very strong position as a platform for both agents and applications, both of which will grow due to AI, to be able to manage that content. That's our overall take. We're seeing this, you know, kind of thesis continue to, you know, kind of play out in the market. You're gonna see a number of developer tools launching over the coming days and weeks, that will further support, developers that are building on this. This is directly what we're seeing already from our customer base and developer base. So we're just you know, excited to continue to make that as frictionless as possible and continue to kind of pour fuel on that fire. Okay. No, that's great to, great to hear. Maybe just on the Enterprise Advanced success so far, I think it's good to see it at 10% of rev already so quickly. Just maybe kind of what are your expectations for, what that will look like for or where that is gonna end up in fiscal 2027? Like, what do you have embedded in the guide? And just, yeah, how are you kind of viewing the, I guess, seat uplifts so far from customers that have taken on the Enterprise Advanced tier? I would say, certainly, very excited about the momentum that we're seeing in Enterprise Advanced, and, you know, just scratching the surface of the opportunity. We do expect to see that continue to drive a lot of the growth for in the year ahead. We'll give more details in terms of what we're thinking and, you know, expecting around that momentum, not just for next year, but in the coming years, in just a few weeks at our Financial Analyst Day. Then in terms of, you know, the type of impact that we're seeing from customers, we mentioned we've been really pleased with just how much the value of these newer capabilities are resonating with customers. We have been seeing pricing uplifts even just from Enterprise Plus to Enterprise Advanced in that 30%-40% range, alongside a lot of the use cases that Enterprise Advanced is enabling, being a catalyst and one of the reasons that we're seeing healthy dynamics around net seat expansion as well. A lot of different benefits, you know, in terms of not just the top line growth, but the underlying customer economics and stickiness that is driving, which is one of the reasons that we're so excited about the path forward and the growth opportunity that creates. Okay, perfect. thanks for taking the question. Thank you. The next question is from Rishi Jaluria from RBC. Oh, wonderful. Thanks so much for taking my question. maybe I wanna start, Aaron, in your prepared remarks, you talked a lot about many of the verticals, especially regulated verticals, where you're helping enable a lot of these AI use cases. Can you talk a little bit about kind of the state of enterprise AI adoption and the willingness to take AI from pilot and proof of concept into more widespread production and, you know, what you're seeing specifically out of more regulated industries? And then I've got a quick follow-up. Great question. Obviously, I think right now you have a bit of a, you know, tale of two cities with AI adoption. You have a lot of these sort of deep engineering use cases, AI coding, et cetera, that have obviously, you know, taken off 'cause the very users of these platforms are technical. They can adopt their own tools. The, you know, the communities are pretty wired together. You have sort of, let's say, the rest of knowledge work. In the rest of knowledge work, I think what it often takes is applied use cases with AI that can actually bring real transformation to the workflow. You know, I think at this point it's safe to say every knowledge worker has some degree of access to a chat tool, you know, either personally or professionally. You know, general purpose, I'm asking the internet or some systems questions is, I think, you know, increasingly growing. The real interesting, you know, part is, can I actually go in and automate and accelerate and augment my workflows in an organization? With Enterprise Advanced, this is really an applied system for how do you bring AI and AI agents to enterprise content workflows. The biggest one that has taken off thus far is really data extraction. You have a large repository of contracts or invoices or financial data, and you wanna be able to extract key details from that and then kick off some workflow or pump that data into a data lake and then query it or query it with Box. We are seeing a lot of growth in those use cases right now. There's, as I kinda mentioned on the call, we have a new product called Box Automate that is coming. We shared this with customers at the tail end of last year. Box Automate is sort of one click above data extraction, which is I might wanna sort of design an entire workflow, a client onboarding process, a contract process, a digital asset review process, and at multiple steps in that process, I want agents to do certain amounts of work, dealing with content. Now, you know, we move from really kinda task-specific applied use cases to really increasingly more of the full business process with both agents and people, you know, kind of showing up at the relevant point. We are 100% focused on applied AI use cases in an organization. That's, I think, why we're seeing, you know, healthy adoption of both Enterprise Advanced as well as in regulated industries, maybe ones where it wouldn't have been maybe, you know, initially intuitive that they would be able to adopt so quickly. It's because these are applied use cases, and our platform is purpose-built for security compliance, you know, data governance issues that they're gonna run into with AI. Yep. Got it. Thanks. That's really helpful. Then Dylan, for you, just maybe a bit of more of a housekeeping. If you As you talked about your Q1 billings guide, you talked about FX as a, correct me if I'm wrong, 530 basis point headwind to growth. That seems a little bit high, especially in light of the rest of your kind of as reported and constant currency growth rates. Can you expand a little bit on just kind of the math behind that and why the headwind from FX is so extreme in Q1? Thanks. If you look back to a year ago, there was just a pretty significant movement in the U.S. dollar to yen exchange rate in that period. That's one of the reasons. Also, if you look at our Q1 results from this past year in FY 26, was really the reverse story, and was one of the contributing factors to extremely strong billings growth. Really is unique to just the movement that we saw in that exchange rate a year ago. For the year, you know, much more normalized. You know, you did hear that right, in terms of the, you know, 530 basis point headwind for Q1. For the year, we expect FX to be a roughly 100 basis point headwind to our billings growth rate. Definitely a pretty unusual dynamic just in the first quarter based on those rate movements a year ago. All right. Understood. Thank you so much. We'll take the next question from Brian Peterson, Raymond James. Thanks, guys. Congrats on the really strong quarter. Dylan, I'd love to understand as you went through the quarter, any help on how you're thinking about linearity, demand, and any perspective from a geo in terms of Japan, North America, anything that you call out there? Do you mean linearity in terms of what we saw within the fourth quarter? Yeah. Two parts. Sorry. Yeah. For the fourth quarter, two parts. I would love to understand just the general linearity as you went through the quarter and anything you would call out in terms of strength by geo. Linearity, was, you know, really, positive, both because I think the team's done a really nice job, you know, in terms of driving that, and not, you know, letting everything sit to, you know, the last, you know, days or weeks of the quarter, which also gives us more cycles, to bring in some of those deals, you know, drive some of that upside. That was certainly a contributing factor to the underlying bookings, strength and outperformance that we saw. At the same time, which also touches on, your second question, we have seen, you know, a nice strength and a really good momentum in the performance of our commercial business, so SMB, mid-market. Uh, and, uh, that is just, uh, you know, inherently, uh, more linear, uh, typically than, than, uh, enterprise, uh, within the quarter. Uh, and so seeing that strength also contributed to the, uh, the strong, um, uh, linearity, uh, that we saw. Uh, and then on top of those segments, um, you know, a-a-again, uh, uh, Japan was a, you know, strong performer for us. Uh, and then we have seen, um, you know, some of the regions in the US really, um, you know, starting to hit their stride as well. Um, but no, uh, you know, really unusual trends in terms of what we've seen over the past year, uh, other than, uh, just continued, uh, and additional strength, uh, on the commercial side. you know, everything, just a higher overall level of performance, you know, across those different segments. Got it. Aaron, maybe one for you. You talked about, you know, some of the different end markets that might be coming to Enterprise Advanced. I'd love to maybe understand, how do you think about the evolution of that ramp in terms of selling into the customer base, but also maybe coming in with net new to Enterprise Advanced? I don't know if you guys can share of that 10% how many came in kind of migrating from the existing base or net new, but would love to unpack that a bit. Thanks, guys. Yeah. I mean, Enterprise Advanced sets us up very nicely for net new conversations, because it's getting you into a workflow conversation, and in particular, you know, an agentic workflow conversation. You could have, you know, never had run into a use case that we previously would have been able to solve for you, with Box, and we can come into your organization and instantly have a conversation around being able to start to drive automation in some process that again, maybe 2 years ago, we'd have no ability to play in. This could be, a, you know, a contract automation process, a client onboarding workflow where we're doing more of the intelligence. It could be in a healthcare, data processing workflow. We have customers where we've had conversations where they want to rip and replace a legacy ECM system, and maybe they were starting to kind of figure out, can they migrate that to the cloud or build out their own capability? Then all of a sudden, they kinda see the full depth of data governance, security, compliance that they're gonna need, especially in a world of agents, and decide that actually Box is gonna be the superior, more future-proof solution for that. In all of these examples, Enterprise Advanced is kind of putting together the a package between workflow, no-code apps, AI agents, and, you know, sort of metadata extraction, all backed by a level of data security with Box Shield Pro and other capabilities that allow you to move your mission-critical work and content to Box. We're seeing that again in a wide range of new logos as well as existing customer upsells. Thanks, Aaron. Matt Bullock from Bank of America has the next question. Great. Thank you. I wanted to ask about net revenue retention expectations. Looks like it's gonna improve modestly in fiscal 2027, but I'd be curious to hear if you could unpack the components of that across, you know, pricing per seat benefits, net seat expansion. It sounds like APIs and units are gonna start coming into the model as well this year. It's, I presume, only marginally, but could that be something like 50 basis points of tailwinds to NRR this year as we progress towards that longer-term target of 1 to 2 points of growth from platform? Yeah. In terms of drivers of the net retention rates, both for the coming year and then the, you know, additional improvement that we expect to deliver in the coming years, you know, would expect to see that coming from the combination of slightly higher impact from pricing uplifts and, you know, continued momentum with net seat expansion being more of a driver, which is a change from, you know, looking back to a year ago, that was more so being driven by the pricing side. We're now seeing and expecting to see, you know, more kinda healthy mix between the two, with, you know, no expected change on the full churn rate on that side. In terms of the overall platform business, yeah, we could see that, you know, certainly contributing to the, to the net retention e-equation, and part of the overall pricing dynamic, and that uplift that we'd see there. To your point, at least for the coming year, don't expect that to be a material driver of any change in the net retention rate. Got it. Really helpful. Just one quick follow-up, if I could. I wanted to ask about Enterprise Advanced pricing uplifts. You know, you've seen consistent 30%-40% uplift relative to Enterprise Plus already at 10% revenue mix here, and you're innovating quite a bit. My question is: Do you foresee the pricing uplift for Enterprise Advanced potentially ticking above that 40% kind of baseline that it's tracked at so far over the next couple of years as you continue to add value? would say, you know, probably wouldn't set the expectation to see that move up too much in terms of the core upgrade from Enterprise Plus to Enterprise Advanced. you know, certainly what we're driving is to deliver more of an overall contract value increase when custom ers make that move through the combination of just increasingly monetizing those platform components that we've been talking about, as well as, and kind of in conjunction with opening up the new use cases to drive more seats. Because that 30%-40% uplift is really specific to the apples to apples, "Hey, you have X seats, you know, and now they're moving to Enterprise Advanced. What's the price per seat? Don't expect to see as much of the upside from the success and innovation of Enterprise Advanced show up in that specific metric, but more in the overall contract value through those other related levers. Fantastic. Thank you. The next question will come from Lucky Schreiner, D.A. Davidson. Great. Thanks for taking my questions. Maybe a unique one, but over the course of the year, did you notice any difference in behavior between the early adopters of Enterprise Advanced versus customers that maybe adopted in 4Q, just given the vast improvements in the models that we've seen over the course of 2025, and any way we should maybe be thinking about that for 2026? When you say the models, i.e., AI models, right? Correct. Yeah. Some of the agentic abilities that, you know, you guys can provide on the platform. Yeah. It's a great question in terms of how you're characterizing it. I don't know that I could pinpoint. I don't know that I would pinpoint any specific thing, but I like the general trend that is sort of embedded in that question is actually correct, which is, you know, if I go back, let's say 14 months ago when Enterprise Advanced, you know, initially kinda hit the scene in conversations, you know, there was still lots of use cases in mission-critical workflows where you would have to do a lot of work to make sure that the data extraction was, you know, as accurate as you needed. As each model family kind of has its next upgrade, in its lineage, you know, we tend to see, you know, anywhere from single digit to double digit percentage points in accuracy and kind of quality of the models on unstructured data. That's just universally a good thing for us because it means there's even more swaths of use cases that we can go after and say, "Hey, you know, we can go and extract critical metadata from those, from, you know, those even more complex contracts or financial documents or assets that you have." So I'd say that the general trajectory, again, without, you know, pinpointing Q4 specifically, is that customers will get more and more comfortable automating more and more of these content workflows as these models continue to improve, and we're already seeing that trajectory take off with our conversations. It's a fantastic, just like universally good trend for us that we're gonna keep riding. Awesome. That makes a lot of sense. On the Enterprise Advanced customers, congrats on, you know, the 10% of revenue. That's impressive. If I look at the percent of revenue coming from Suites, that implies nearly all of the revenue came from upgrades from Enterprise Plus customers to Enterprise Advanced, which makes a lot of sense. Is there anything about the non-Enterprise Plus customers that might be slower to upgrade to the higher tiers and maybe how are you thinking about that opportunity? Yeah, I think that that's right, that the majority of the Enterprise Advanced customers who have upgraded were coming from existing customer base and, you know, more likely than not, you know, coming from Enterprise Plus. Wouldn't say there's anything unique about the types of companies, you know, whether it's, you know, company size or, you know, any unique dynamics about the actual company. Just from a use case point of view, you know, certainly those customers who would be, you know, more already bought into the value of Box's, you know, platform offerings and who have a lot of the use cases that would benefit the most from Enterprise Advanced capabilities, as you'd expect, and especially from an early adopter stage, there's pretty strong correlation with, you know, those customers who are already on Enterprise Plus, which was previously, you know, our highest tier offering. That's, you know, really I would say a function of, you know, timing and the specific customers, you know, it's almost a self-selecting, you know, if you're one of the early adopters of Enterprise Advanced, you know, more likely than not, you're on Enterprise Plus. We see a huge opportunity for those non-Enterprise Plus customers, just given, you know, the types of use cases, the types of conversations we're having, and the potential there as well. More of a timing thing than anything else is what we'd point to. Got it. Appreciate the color there, and congrats on a record year. Thanks. Next up is Jason Ader from William Blair. Yeah. Thank you. Thank you, Aaron. I wanted to give you the opportunity to address a couple of the bear narratives out there for SaaS. First is the fear that SaaS apps become back-end databases on which an intelligence layer like Claude sits and captures much of the value. Second, that seat-based models face structural challenges because of knowledge worker job displacement. Yeah. This might sound like reiterating a little bit of the first question. We're, you know, I don't, you know, the, there's almost nothing in that that is bad for Box, I guess, ironically. I don't necessarily, you know, totally believe, some of those components, especially the, you know, kind of future of knowledge work and the, and the volume of that. I think that most people are gonna use AI to accelerate their work and augment their work, kinda workforces. What we're building as a platform is, when you have critical information, contracts, research data, marketing assets, HR files, financial documents, all of that content is going to need to be shared between agents, people, and systems or applications. There's simply no way around it. You can't have two agents that are maybe trying to coordinate a task for a lawyer be working off of two different sets of contracts. They fundamentally would need the same access to data. You need a shared file system. That shared file system has to be accessible to your agents and your people and maybe the ratio changes over time of different kind of roles in the economy in different parts. No matter what, there'll be some human in the loop at some part, so then the data has to be shared with a person. And ultimately, that company is going to need to have the same governance, the same security, the same controls on that information as they did with people. Imagine that you're a large bank, and your bank is processing, you know, escrow documents or loan, you know, kind of files from a client. That data will have to be governed just as like when people went and reviewed those documents. They're gonna need to sit around for, you know, 10 years in some cases. You're gonna need to see the exact traces of what the agent did and what decisions they made in that workflow. All of that is unstructured data. It will all become content, whether it's markdown files or PDFs or, you know, Word documents. That's all enterprise content that has to be secured and governed, controlled, and protected in the exact same way that we've always been doing it because files are the sort of this natural medium by which people and agents share information. I would just say that our platform story becomes really increasingly the core of how we can power both, again, agents, applications, and people. You know, in a scenario where you have maybe a seat decline because agents have grown so much, which, let's posit as some potential scenario, the agents that are growing on the other end of that still need a place to then store their documents and their enterprise content. I don't know if you heard this answer, but if you have more and more, let's call it vibe-coded software or SaaS, those systems still also need repositories for being able to secure and protect and govern the content that gets generated. We already have a business model for that. That's our platform business model. We can grow either through platform consumption or we grow through continued seat adoption, both of which we're seeing right now in the business. I think we're kind of protected on both dimensions there. It's really, again, because of the critical nature of how companies need to manage this information. You need data governance. You need data security. You need compliance. You need data residency. None of that can go away in a world of agents, and in fact, probably it becomes more important in a world of agents. Because if you have 100 x more agents running around doing loan processes than you had people, the chance of a mistake happening, the risks of an agent, you know, revealing the wrong piece of information to a client goes up exponentially. Those agents don't have context for what they should or shouldn't be sharing. It's very easy to prompt inject those agents. There's a lot of risks that can emerge. You need to give them isolated environments, but those are isolated environments that need some degree of controls and mechanisms, and in many cases, kind of collaboration with the user. That's what we're powering. That's what our platform has always done for humans and for applications, and now we're adding agents into the mix and why we see this as, again, just universally a good thing. I think maybe the one thing where we sit around, we look at Claude Cowork, and we see OpenClaw, like we are just incredibly happy for the existence of these things. We were a Claude Cowork partner on their plugins. Like the more knowledge work that happens agentically, it's all goodness for us. It just creates, you know, a tremendous amount of data that needs to get stored somewhere securely. Okay, awesome. Sorry, just as a quick follow-up. Could you talk about the AI API monetization opportunity in relation to that answer that you just gave? There's a couple parts of the API monetization. There's a pure volume-based mechanic. If you were to use Box, you know, tomorrow, and you deployed a fleet of agents, and they were all running around, you had 100 times more agents than people in your organization, and each of those agents, you would probably want to have a Box account of some sort. You can either have a headless Box account, you can have a regular Box account, you choose. You're gonna want those agents to be writing, reading, storing data, sharing with other people. If it's done in a headless capacity via our APIs, we have a platform business model which is consumption-oriented. You'll just pay for the API calls that go into that. If you use our direct intelligence layer, which taps into, you know, Claude and GPT 5.2 or any new model, Gemini 3, then we also monetize that through AI units. We've got dual consumption monetization levers that will basically grow, you know, somewhat correlated with just the growth of AI agents in the economy, assuming our customers are, you know, deploying those capabilities. Of course, seats still like we're still, you know, relatively early on total seat penetration. There will actually be a scenario where seats will grow because of agent growth, because we will then tap into use cases that we didn't previously solve, where there still will be a human in the loop working with agents, but now we're able to capture more of those use cases than we would have, you know, for that particular knowledge worker five years ago. There's sort of just it's multifaceted sort of growth levers, but it like if you just had to like be like, okay, what's the simple concept here? It's that agents use files. That is their core thing that they work with. Every time you hear any viral thing on, you know, online about an agent storing off its work, creating a memory, having documentation, having a specification to work off of, it's always a file. Those files are gonna get generated, they're gonna need to get stored somewhere, they're gonna need to be governed, they're gonna be shared with people. That is just the general sort of, you know, tailwind that our platform is gonna be able to support. Thanks. Seth Gilbert from UBS has the next question. Thanks for the questions. I guess for the first one, you had the best greater than $100,000 customer growth in about 11 quarters. The question's on the customer adds front. Can you help us expand on where you're winning? Is it Enterprise Advanced, other SKUs, other parts of the business? I believe someone else asked on the split of Enterprise Advanced new versus existing logos, but I'm not sure I caught the answer. Maybe you can expand there as well. Thank you. Yeah, I would say the $100,000, you know, Plus customer count growth is very much directly driven by the sort of overall set of capabilities that are either a part of Enterprise Advanced or customers that are now getting more involved in our platform because they kinda see us obviously on the right side of this AI curve. Actually it's interesting the neutrality piece, we haven't talked about it too much on this call, but it's sort of somewhat timely in this idea that at any given moment you might wanna use a different AI model for a different capability in your enterprise, and you don't wanna be moving and shuffling around your content depending on that use case. That's another benefit that you get with our overall platform. There's a lot of these sort of, you know, strategic tailwinds where our platform is positioned. Some customers, you know, might buy our platform, not yet Enterprise Advanced, but they're buying it because they recognize the sort of importance of many of these aspects of our platform overall. So that's also helping drive the growth, but Enterprise Advanced, you know, very much emphatically is helping lift that number up and we're seeing it just kind of across industry right now. Got it. That's helpful. Maybe as a follow-up, as you're marching towards the long-term guide of double-digit top line growth, margins are remaining roughly flat for FY 27. I understand the drivers of these flat margins, but maybe you can talk about what has to happen for margin expansion in the future. Do we need to see, you know, top line growth above 10% to get margin expansion or maybe there's some efficiencies on the S&M and R&D side that will kind of percolate through once the investment phase next year has, you know, taken shape? Yeah. would say there's nothing, you know, no required growth rate to be improving operating margin at a greater clip, you know, versus the, you know, kind of incremental improvement in constant currency that we're expecting to deliver this year. You know, this year really, as we've talked about, is about doubling down and making sure that we invest to capture the market opportunity just given where we are in the market evolution. Most of those investments are on the sales marketing side. If you look back over the last few years, you know, we've generated significant margin expansion even while growing in the single digit range. In addition to all of the opportunities and and efficiencies that we're driving around, you know, kinda how we're deploying AI internally, you know, including with Box's own product, some of the same areas that we've been driving, you know, operating margin up into the high 20s% are the same things that are gonna get us, you know, the next several points of growth. That's things like, you know, continuing to take advantage of our lower cost workforce location strategy. you know, a lot of the other areas that, you know, we've invested in, that are generating stronger returns, whether that's with Salesforce productivity, the ROI of the marketing programs, or just as a lot of these core strategic go-to-market investments mature, you know, those will be able to generate more leverage as well, including through our partner ecosystem. Really a lot of things across the board, but would really, you know, frame the operating margin, you know, and lower rate of improvement, you know, in the current moment more as a strategic decision to put more dollars toward growth versus anything, you know, about the model itself. Everyone, at this time, there are no further questions. I'd like to hand the conference back to Cynthia Hiponia for any additional or closing re-remarks. Great. Thank you everyone for joining us. To drill down deeper on our strategy and financial model, we are hosting a Financial Analyst Day on Thursday, March 19th. Please go to our IR website to register, and hopefully we'll see most of you there in person in New York. Thank you very much. Once again, everyone, that does conclude today's conference. We would like to thank you all for your participation today. You may now disconnect.