Hello, and thank you for standing by. My name is Regina, and I will be your conference operator today. At this time, I would like to welcome everyone to the Oracle Corporation third quarter fiscal year 2026 earnings conference call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question- and- answer session. If you would like to ask a question during this time, simply press star then the number one on your telephone keypad. To withdraw your question, press star one again. We kindly ask that you please limit yourself to one question. I would now like to turn the conference over to Ken Bond, Head of Investor Relations. Please go ahead. Thank you, Regina, and good afternoon, everyone. Welcome to Oracle's third quarter fiscal year 2026 earnings conference call. On the call today are Chairman and Chief Technology Officer, Larry Ellison, Chief Executive Officer, Clay Magouyrk, Chief Executive Officer, Mike Sicilia, and Principal Financial Officer, Doug Kehring. A copy of the press release and financial tables, which includes supplemental financial details on our most recent quarter, guidance for our future results, a GAAP to non-GAAP reconciliation, and a selected list of customers who purchased Oracle Cloud services or went live on Oracle Cloud recently, will be available from our investor relations website. As a reminder, today's discussion will include forward-looking statements, and we will discuss some important factors relating to our business. These forward-looking statements are also subject to risks and uncertainties that may cause actual results to differ materially from the statements being made today. As a result, we caution you from placing undue reliance on these forward-looking statements, and we encourage you to review our most recent reports, including our 10-K and 10-Q and any applicable amendments. Finally, we are not obligating ourselves to revise our results or these forward-looking statements in light of new information or future events. Before we go to the Q&A portion of the call, we'll begin with a few prepared remarks, and with that, I'll turn it over to Doug. Thanks, Ken. Let me start by highlighting the changes we are making to our earnings press release and this call. In the press release, we have laid out clearly and explicitly the supplemental financial metrics that we otherwise would have provided on the earnings call so that each of you has the information in writing and in advance. As it relates to our approach to the earnings call itself, I will be very brief and then turn it over to Mike and Clay to provide more substantial thoughts on our business. After which, all of us, including Larry, will be available to take questions. In terms of the results for Q3, we had a tremendous quarter that exceeded expectations across the board. Our momentum continues to accelerate with Q3 being the first quarter in over 15 years, where both organic total revenue and organic non-GAAP EPS grew at 20% or better in USD, as we highlighted in the press release. I'll quickly mention a couple of things and then hand the call over to our CEOs. First, in January, TikTok U.S. completed the separation of its U.S. data operations from ByteDance into an independent company in which Oracle now holds a 15% equity stake along with a seat on the board. In terms of impact to our financials, there is no impact to the revenue related to the services we have been providing as their technology vendor. That is continuing as it was. As it relates to the equity investment, we will be accounting for this under the equity method, and we will recognize our share of the new company's earnings for the period from the close of the investment in late January to March 31st in our Q4 results, as there is a two-month reporting period time lag. It will be recorded as non-operating income or loss on our income statement and is incremental and additive to our financials. Second, in February, we announced our intent to raise up to $50 billion in debt and equity financing, along with a statement that we do not expect to issue any additional bonds beyond this amount in calendar year 2026. Within days of the announcement, we raised $30 billion through a combination of investment-grade bonds and mandatory convertible preferred stock with a record order book that was substantially oversubscribed. As noted in our release, we have not yet initiated the at-the-market equity portion of the financing program. Finally, I'd be remiss not to remind everyone we are reporting our financial results just 10 days after the last day of the quarter, despite the increasing size and complexity of our business. Using Oracle Fusion, we continue to close and file our financial results faster than any other company in the S&P 500, providing us with a significant strategic advantage as well as an opportunity to help our Fusion customers do the same with their businesses. With that, let me now turn the call over to Mike. Thanks, Doug. As Doug just detailed, we really had an excellent quarter across the board and continue to see strong execution. Let me say a few words about our applications business. Oracle has the fastest-growing, most complete suite of Cloud Applications in the market, full stop. Our SaaS solutions are industry complete platforms with highly scalable, trusted, secure, and regulatory compliance systems and processes in which our customers trust us to run the systems that run their businesses. In constant currency, Cloud Applications revenue was up 11% in the quarter, reaching an annualized run rate of $16.1 billion. Within that, Fusion ERP was up 14%, Fusion SCM up 15%, Fusion HCM up 15%, Fusion CX up 6%. NetSuite was up 11%. Industry SaaS solutions for hospitality, construction, retail, banking, restaurants, local governments, and telecommunications combined were up 19%. Certainly, very happy with the applications growth in the quarter. In the context of that, I'll say a few words about the reported SaaS apocalypse. You've all heard the thesis or theory that new companies coding quickly using AI will spell the death of SaaS. I don't agree with that at all. I do think that AI tools and their coding capabilities would be a threat if we weren't adopting them, but we are, and very rapidly. Oracle is using the best AI coding tools and the best developers not only to accelerate our SaaS business, but to deliver solutions that enable entire ecosystems across numerous industries. The use of AI coding tools inside Oracle is enabling smaller engineering teams to deliver more complete solutions to our customers more quickly. We are building brand-new SaaS products using AI and also embedding AI agents right into our existing applications suites. By embracing AI with small engineering teams, we have just built three brand-new CX applications. Lead generation and qualification, sales orchestration, and automated selling, and our new website generator. In fact, we just used the website generator to build and launch the new Oracle.com. We've built these new CX products to help our customers sell, not simply to administer a forecast or generate email opens. These are three products that Salesforce.com does not have. Of course, Salesforce.com also doesn't have OCI, the AI data platform, Fusion ERP, and complete industry suites. Complete AI-powered, end-to-end ecosystem automation platforms are quite unique to Oracle. In addition to that, we've already delivered well over 1,000 agents right inside our horizontal back office and industry applications. This doesn't even include the agents that our customers are building themselves or the fleet of agents that we're using internally. These are AI features built right into our applications and existing processes. A great example, I think, is in healthcare, where our brand-new AI-powered integrated EHR, electronic health record system, is live in the market, and the results are quite clear. We are reducing administrative overhead, we're allowing clinicians to see more patients, we're improving access to care, and we're increasing provider satisfaction. In another example, in banking, we provide a comprehensive AI-powered SaaS platform, including everything from commercial banking, retail banking, investment banking, anti-money laundering, financial crimes and compliance, payments, supply chain financing, CX, ERP, and HCM. That banking suite alone contains hundreds of embedded AI agents, all available at no additional cost to our customers. In retail, our AI-enabled solutions span merchandising, assortment planning, supply chain management, point-of-sale, commerce, and of course, ERP, CX, and HCM. In summary, these are not systems that can be replaced by a small collection of niche features cobbled together and bolted on in the name of AI. Yes, some smaller or single-focused SaaS players may well be disrupted, but Oracle will not be among them. Now let me focus on a few key wins in Q3 in the application space. By all means, this is a very short list, not an exhaustive list. Memorial Hermann Health System selected Fusion ERP, SCM, and HCM. This was a win over Workday. University of New South Wales also selected Fusion ERP and HCM, also a win over Workday. Gray Media selected Fusion EPM and ERP, a win again over Workday and also over SAP. Investec Bank selected Fusion EPM and ERP over SAP. HID Global Corporation also selected Fusion ERP and SCM over SAP. Ethiopian Shipping and Logistics Services Enterprise selected Fusion ERP, SCM, and HCM, again over SAP. A major Wall Street bank elected to standardize on Fusion ERP for the entirety of their business and all of their business units, replacing SAP full stop. Loudoun County Public Schools selected Fusion ERP, EPM, HCM, and SCM. The J.M. Smucker Co selected Fusion ERP and EPM. Westfield Insurance picked Fusion ERP, EPM, HCM, and procurement. Mitsubishi UFJ Financial Group is an existing cloud customer and database customer. They are now moving into both our Fusion ERP and industry SaaS applications. stc Kuwait, an existing major tech customer, is moving EBS to the cloud to support their growth. Just this very small list of major applications wins in the quarters. In the quarter, we had over 2000 customers go live in Q3. 2000 customers when you think about our industry applications and our Fusion applications put together. Over 2000 went live, and more importantly, we continue to see the median time to live decrease. A very small sample of go lives in the quarter. Hearst expanded their ERP with EPM as well as HCM. J.M. Huber Corporation is now live across Fusion ERP and SCM. Emirates Health Services went live with HCM, which enabled a comprehensive HR, payroll, and talent suite to elevate their workforce management. Niagara Bottling went live on SCM, moving from on-premises ERP to Fusion. Seadrill is now live across ERP, HCM, SCM, and EPM. Again, with 2,000 go lives in the quarter, that's just a very, very short list of go lives. You can see hopefully, not only momentum, but multi-pillar momentum with these customers. I also have an equally short list compared to the overall list of key tech wins in Q3. Lockheed Martin selected OCI High Performance Computing to scale AI across their environment sufficiently. Rhombus selected OCI Compute, networking, and storage for AI video and security across all of their workloads. Lucid Motors selected OCI Core Services for data and connectivity in order to expand into European markets. Infomart in Japan selected OCI for their mission-critical B2B platform. Claro Brazil selected OCI Alloy for sovereign AI. Air France-KLM, which is a multi-cloud win, featuring a win with the Oracle Database@Azure, and that led to a 13x performance improvement at a significantly lower cost for Air France-KLM. Activision Blizzard, an existing Oracle E-Business Suite, was also an Oracle Database@Azure win. Oracle's embrace of AI across our strategic applications is leading to broader enterprise conversations with our customers involving our full stack, OCI, AI Data Platform, Fusion Applications, industry suites. These conversations are about ecosystem automation. They're not about single apps, they're about automating the entire ecosystem, and they're further enabled by our simplified go-to-market model, which we spoke about in our last earnings call. This is allowing us to close more multi-product deals with more customers, combining the power of the Oracle Database, our OCI platform, our AI tooling, and our complete applications suites. In constant currency Cloud Applications, deferred revenue was up 14% versus in-quarter Cloud Applications revenue growth of 11%, which further supports our acceleration thesis. With that, Clay, I'll turn it over to you. Thank you, Mike. Okay, I'm gonna talk about two segments of our business, our multi-cloud database and AI infrastructure. Both are growing extremely quickly. Multi-cloud database revenue grew 531% year-over-year. AI infrastructure revenue grew 243% year-over-year. Both also have demand that exceeds supply and a clear execution plan from Oracle that will rapidly turn that demand into profitable recurring revenue. Oracle Database has run on any hardware and operating system for decades. Oracle Database Cloud Services, up until recently, were only available in a single cloud, OCI. We created our multi-cloud partnerships with first Microsoft, then Google, and finally Amazon to bring the best database platform to all clouds. Those partnerships unlock an enormous backlog of demand. Our database customers who want to use our database in other clouds. This quarter, we achieved an important milestone. We have global region coverage in all of our partner clouds. We now have 33 regions live with Microsoft and 14 live with Google. We delivered significant growth with AWS, beginning Q3 with two AWS regions live, exiting Q3 with eight AWS regions live, and we will exit Q4 with 22 AWS regions live. AI is also accelerating the adoption of our database cloud services. The rapid improvement in model coding skills and agentic abilities pushes customers to move their most valuable data into our cloud services. They need access to the latest AI features to support vector embeddings, MCP server access, and advanced security controls. Customers also need their data to be co-located with the agents themselves, and our multi-cloud database makes that easy. Our multi-cloud architecture brings the best of Oracle Cloud into our partner regions in. This ensures that we will rapidly turn billions of pipelines into highly profitable database service revenue. Demand for AI infrastructure, both GPU and CPU, continues to exceed supply. This is directly visible in our $553 billion RPO. I wanna share a model for how that RPO turns into profitable recurring revenue, as well as some operational metrics that are early indicators of our progress. AI infrastructure begins with data centers and power generation. Through our partners, we have secured more than 10 GW of power and data center capacity coming online over the next three years. Those infrastructure investments also need funding, and greater than 90% of that capacity is fully funded through our partners, with the remainder planned to finish this month. Once the data center is secured, several things must come together. The data center and on-site power generation has to be constructed. Compute, networking, and storage has to be designed, manufactured, delivered, and installed. All the capacity inside the data center also has to be funded. We continue to innovate across each of these steps. We optimize our data center construction through standardized designs. Our supply chain has improved with more suppliers and deeper relationships. We have tripled our manufacturing sites and increased rack output by 4x all in the last year. We have scaled our installation processes to enable multiple phases of delivery in parallel. Time from rack delivery to revenue has reduced by 60% in the past several months. We also continue to innovate on our business models. On our last earnings call, I shared multiple ideas for how we can incrementally grow our AI infrastructure without Oracle raising more debt or issuing equity. We have signed more than $29 billion of contracts since then across multiple customers using that new model. A combination of bring your own hardware and upfront customer payments enables us to continue expanding without any negative cash flow from Oracle. Of course, this $29 billion is in addition to other deals we signed this quarter. Ultimately, all of this results in capacity delivered to customers and revenue to Oracle. In Q3, we delivered more than 400 MW to customers. 90% of that committed capacity was delivered on or ahead of schedule, as we've consistently done over several quarters. This is why customers continue to choose Oracle for their infrastructure needs. Investing in AI infrastructure is capital-intensive, but our operating model is optimized to ensure profitability. Flexible infrastructure design, high utilization, and rapid handover combined with diversified customers creates an incredible business. Increased scale spreads our fixed costs over a larger base, increasing profitability. It's unprecedented to scale a capital-intensive business so quickly while also increasing profitability. Looking at the AI capacity we delivered in Q3, our gross margin for that remained above our 30% guidance at 32%. Now combine that with our other segments of OCI, which have much higher margins, like our database services, and you can see why Oracle is growing so quickly and profitably. Our numbers speak for themselves. We are over-delivering on FY 2026 revenue and earnings, and we are constantly raising our FY 2027 forecast. This is made possible by Oracle's transition from a predominantly seasonal license business into a highly predictable recurring revenue cloud business. Demand for AI and advanced compute will continue to expand broadly across the economy. There will be many successful models, agentic platforms, and businesses that emerge. We support hundreds of the most advanced AI customers today, and more continually want to work with us. We build infrastructure that is flexible, fungible, and can support the smallest workloads up to the largest. We continually offer the latest in accelerators from the most recent NVIDIA and AMD options to emerging designs from companies like Cerebras and Pegatron. Altogether, we are confident that the investments we make now in data centers, compute capacity, and customer relationships will only grow more valuable with time. Back to Ken for questions. Thank you, Clay. Regina, if you could please poll the audience for questions. We will now begin the question and answer session. To ask a question, press star then the number one on your telephone keypad. We ask that you please limit your questions to one. Our first question will come from the line of John DiFucci with Guggenheim. Please go ahead. Thank you. Wow, a lot going on here. Listen, I'm gonna let others ask about the AI infrastructure question. We've heard Doug talk about a halo effect that the AI infrastructure business is having on the rest of your business. This quarter was strong and you said that the RPO increase was from large-scale AI contracts. At the same time, we're hearing from the field now that that halo effect is actually turning into business. Outside of AI infrastructure, it sounds like the go lives are steady, but the business activity, and especially the pipeline, are up materially for more traditional cloud workloads, including, you know, dedicated region, sovereign clouds, even Alloy deals we're hearing about. In addition to what Mike started talking about with the often related apps deals, I realize these types of deals aren't the scale of these AI deals, but can you talk about what seems to be an underlying momentum building in these businesses? Am I right to be thinking of this? If I could, on a sort of related topic, can you give us any visibility into CapEx for fiscal 2027? Okay. Hey, John, this is Mike. I'll take the question. Yes, we absolutely are seeing a halo effect, and let me add a little bit of color on that. You know, as far as the apps business, you know, the fact that we're training so many models on OCI and so closely provisioned to our applications allows us to embed very high-quality AI services right into our applications, as I said, as features. Not only are we serving these customers, you know, serving the model vendors for training, but we're also embedding a lot of the output right into our applications. Of course, we're doing prompt engineering and things like that to make it relevant to the business. The fact that we are the custodian in our applications business of so much of the world's mission-critical data, we have very close provisioning, very close proximity to these models. Putting those two things together allows customers to get value from AI very, very quickly. If you've heard any criticism of AI in the world as, "Well, I can't get value quick enough." Well, actually, when you bundle up as a service, and expose the private data to AI that we are the custodian of as the applications, we've seen terrific wins. I mentioned some of the verticals you heard about there, but I think that's true across the board. The other piece that is a very interesting halo effect is leveraging our infrastructure, just OCI infrastructure as a budget creator for customers. You've heard us say it before, we're faster and cheaper than everybody else. When customers are thinking about these large-scale application or large-scale infrastructure transformations, we can also help them get to a position of budget creation to be able to fund that transformation simply by moving their workloads to OCI because we can run them more quickly and more efficiently and less expensively than our competitors. Finally, you know, the other halo effect, before I turn it over to Doug for your question on CapEx, is around sovereign AI. Our sovereign story is not new, and it's not a knee-jerk reaction to the things that are happening in the world. You know, combined together with our Alloy story, you know, we're really seeing increasing pipeline across the world. The fact that our form factor, and we're so differentiated in our form factor, and we can deliver, you know, not just a smaller form factor, but complete OCI services on top of that form factor no matter how many racks are involved, whether it's three racks or 500 racks, we think that's a huge differentiator in the market. You put apps together, you put OCI AI services together, you put sovereignty together, and yes, it's a pretty big halo effect. Yeah. John, I just want to start by acknowledging the creativity in getting two questions in at the same time. That's always fascinating to watch. On CapEx, I think we'll get back to everyone next after the end of the fiscal year and talk about next year's CapEx at that point in time. I will state a couple things. Obviously, from what Clay has gone through, the most interesting thing that you should start thinking about is the uncoupling of CapEx with capital requirements from Oracle. Obviously, when we have these additional funding mechanisms, there may be additional CapEx, but it doesn't require out-of-pocket cash from Oracle, which is quite interesting. Underlying that, as we remain committed to what we talked about last quarter, which is maintaining the investment grade rating at Oracle, as well as staying within the financing envelope that we talked about, obviously, of which we've announced that we're doing $50 billion this calendar year of that total. More to come, John, on the CapEx after next quarter. Very much appreciate the color on that, Doug. Mike, your prepared remarks on AI and how Oracle approaches it, everybody should use that because it's a logical approach. Thanks, guys, and nice job. Our next question will come from the line of Mark Murphy with JP Morgan. Please go ahead. Thank you. Congrats on the acceleration, Clay. As Oracle transitions to higher levels of AI inferencing, what do you view as the right strategy for trying to optimize the location of your data centers? For instance, if you know you have these huge centralized data centers in Texas and Wyoming, they're very close to power, but they're pretty far from the population centers and the fiber routes that are out there on the seaboard. You know, it crosses our minds that the users and the devices are a long distance away. As you make this move more into inferencing, are you seeing any reason to try to pivot those locations a little closer to where the users and the traffic are? Sure. Great. This is Clay. Great question, Mark. Let me start by, I think, highlighting our perspective on inferencing and then how that impacts kind of data center deployment. First thing I would say is I think we're, you know. For a while there was a lot of training going on. Inferencing is very rapidly growing everywhere and anywhere. I think it's because of higher and higher utilization of the models themselves and also new use cases. You know, as anyone who's been using Claude or Codex recently in the software space knows, these are incredible tools. They're changing how we do everything. Inferencing is going to have a huge amount of demand. Now, when you talk about data center location, you mentioned, you know, latency is the one. Realistically, there's several reasons you might care about the location. It might be for the cost, it might be just overall availability, it might be for sovereignty. There's different reasons to pick a location. Honing in on your point about latency, the thing I think to understand is that latency is all proportional. Meaning, if what you're trying to do is you're trying to do a, you know, a very, very low latency trade on the stock market, waiting for the 100-millisecond round trip from coast to coast is a bad idea. If what you're doing is you're asking a question for your business that's gonna take an AI model several seconds to think about, an extra 40 milliseconds of latency from New York to Wyoming is not gonna hurt you. When you actually talk to customers about use cases where they need lower latency, the latency problem right now is not actually the location of the hardware, it's the type of hardware that's being deployed. That's why you're seeing so much innovation going on around these AI accelerators. If you look at what you know Groq does, or Cerebras or Positron, all of these different types of customers are saying, "Well, not only how do we reduce the cost of inferencing, but also how can we significantly reduce the latency of it?" I think, you know, if you look forward to you know GTC from NVIDIA next week, you'll see some key announcements from them. Across the board, I think the way that as an industry we're going to consolidate and kind of reduce latency has to first start with a different architecture for that inferencing. Thankfully the data center location is actually a very tiny part of that. It makes it much more flexible for us to go out and put the data centers where power is abundant, land is plentiful, and we can actually optimize for what's available to meet this ever-increasing demand. Thank you very much. Our next question comes from the line of Siti Panigrahi with Mizuho. Please go ahead. Great. Thanks for taking my question. I wanna ask about the opportunity with your AI database and AI data platform. With recent excitement on AI and around enterprises now adopting tools from frontier LLMs, so what are you hearing from customers about training their private data and then building their private LLMs? How confident are you in seeing the inflection in your AI database growth that you talked about at the Analyst Day in October? Yeah. Thanks. This is Clay. Look, I think there's two parts to that question. One is how much adoption are we seeing of kind of private LLMs, and then how much are we seeing of using AI with private data? I think in the early days, a lot of people thought that most customers would be doing, you know, very specific training of their own large language model. I think that has largely proven to not be the case. Instead, what I think is incredibly popular and growing in popularity is people taking the best models and wanting them to combine that in a private way with their private data. We're seeing a lot of demand for that. If you listen to Mike earlier talk about right? How we're embedding these AI models into our applications, that's one use case. Obviously, not everything unfortunately runs inside of an Oracle application, and lots of custom applications are written. We added a lot of functionality to our Oracle AI Database make it easy to connect via whether it be through MCP servers or natural language to SQL that you can use these models to use. Also we have our AI Data Platform product, which is really about solving this exact problem. You have a lot of data, it may be application data, it may be custom data in different data lakes and lake houses. It may be data in a structured database. All that together gives you an agentic platform to quickly build applications on, as well as access to all of the greatest models from multiple providers. Across the stack, we're seeing a lot of momentum across that, and that's why, you know, in my prepared remarks, I talked about the growth that we're seeing with our multi-cloud database. What we see is that for customers to take advantage of the latest and greatest AI, they first have to be in the cloud, and there's still a lot of data that's not in the cloud. We see acceleration of moving that, you know, most important private data to a cloud environment so they can then take advantage of the latest and greatest AI with that data. Great. Thanks for the color. Our next question comes from the line of Mark Moerdler with Sanford Bernstein. Please go ahead. Thank you very much for taking my question, and congratulations on what's a really good quarter. Really great work. I'm gonna change over a little bit, and discuss on the financial side a little bit. Now that you've completed your major debt raise, can you explain, given the blend of the cost of building out the AI data center and the cost of raising capital to fund the AI data center, how comfortable are you with the values you're creating from the AI data center business itself? As an adjacency, if you just don't mind, can you talk a little bit more on the sovereign cloud? Can you discuss how you parlay the AI data center business into being the AI provider for sovereign clouds, and how that should impact the value of Oracle? Thanks. Sure. I think we're gonna split this one up, Mark. This is Clay. I'll take the first half, and then I'm gonna throw it to Mike to talk about some of the sovereign cloud stuff. Look, when you think about the overall profitability of these AI data centers, there's two pieces. One is, you know, how profitable is it, purely on the accelerators themselves? You know, we gave guidance in the past that we see, you know, gross margin in the 30%-40% range on that. That continues to hold for us. As we continue to get better and better at running these data centers, delivering them more cheaply, optimizing the amount of cost for networking and hardware spend as well as power, we see that continuing to incrementally improve. We're very pleased with that. The other thing to understand is that in these AI data centers, whether it be for inferencing or for training workloads, only thing being procured is not AI accelerators. There's a lot of general purpose compute. There's a lot of whether it be high performance or large scale blob storage, there's load balancing, there's identity security products, et cetera, et cetera. Now, typically on the order of 10%-20% of the total spend ends up going to adjacent services. When you factor that in, which has higher margins, depending on the mix of services, the overall profitability continues to improve. That's without taking into account, you know, as I mentioned earlier about our multi-cloud database business, that that's a much higher margin business, more in the 60%-80% range. It's growing very, very rapidly. When you combine all of these pieces together, the overall margin profile of OCI continues to strengthen and grows rapidly. I mean, the thing I would say, you know, the question that I think is underlies this that maybe people don't understand is the limitation on the profitability is not on the capacity we've delivered. Let's say that I'm building a data center and it has four data halls and I deliver the first data hall, that one's profitable. The reason that we're not even more profitable right now, you know, despite the fact that we are continuing to grow EPS, et cetera, is because we have so much under construction at one time, and we have some expenses for those things. Now, we're very good at that, right? We're very, very good at minimizing the time under which that construction is happening. We're very, very good at reducing those costs during that time period, but they're not zero. As our business is going through this hyper-growth phase, that's the only drag on profitability. Thankfully, we're very good and getting better at delivering that capacity. That capacity when we deliver it, is all already contracted for at a very profitable rate. When you combine those things together, we're extremely confident in both the capacity we've delivered and the continuing to increase profitability of our AI business. Mike's gonna talk about sovereign- Sovereignty, you know, as I mentioned earlier, I think we're very well positioned. You know, a year ago, sovereignty was about data sovereignty, and there were some faux solutions in the market where there was sovereign data from a primary perspective, but DR maybe somewhere else, maybe in another country. Of course, that's no longer acceptable. Sovereignty is about sovereign data, sovereign operations, and even sovereign contracting. Our alloy model is perfectly positioned to deliver on all three of those things. By delivering full stack solutions, again, the big difference between what we're doing with sovereignty and what some of our competitors is doing, we're not simply putting an edge sovereign zone in. We're putting full stack OCI, which has all of our OCI services, and, as you mentioned, margin mix also allows us to run all of our application suite, our AI data platform in that software zone as well. Of course, you know, the margins on some of those are different than our infrastructure margins. I think that we're in a very unique position to deliver all that we have at Oracle in a sovereign zone. That sovereign zone can be as small or as large as the customer wants it to be. The other piece is that we have full flexibility as to where we draw the line of sovereignty. We often think about sovereignty in terms of lines of customers, but we also have, you know, customers that we've been talking with, enterprise customers who may operate across multiple countries, let's say in Europe or in Africa, that actually wanna have a sovereign zone. A sovereign zone that they control, and they operate in their data center, and they're serving customers in a certain vertical industry like healthcare, for example, or retail, for example, and their sovereign zone is drawn in their Alloy across those countries. We can accommodate all of that. We have the most flexibility. We think we have the most flexibility in contract and the most flexibility in delivering, and again, the most important thing is that we deliver all that Oracle has in these sovereign zones. It's not a subset, it's not a few edge devices, it's all of OCI. Extremely helpful, both the answers. I much appreciate. Congrats again. Our next question will come from the line of Raimo Lenschow with Barclays. Please go ahead. Perfect. Thank you. Congrats from me as well. I wanted to ask something that we are struggling a lot with when we talk to investors, and that's kind of the theme of SaaS software, application software is dead because AI is gonna kill it. Just wanted to hear what you guys are hearing when you talk with customers. Is that like some one of these investor things? Is that getting discussed on the customer side as well? And how do you explain it? I'm just thinking about like, you know, what you guys do, it's a lot deterministic rather than probabilistic. So, you know, that might probably be the explanation here, but just wanted to hear your perspective again. Thank you. Yeah. This is Mike. I'll take the question. As far as the customers that I spoke with, I've not yet met a customer who tells me they're ready to give away their retail merchandising system, their core banking system, demand deposit account systems, electronic health record systems, and some you know some small cobbling together of niche AI features is going to replace all of that overnight. In fact, you hear quite the opposite from the customers. What they're asking us is, "How can we consume as much AI out of the box that you're putting into your applications across the board, and how can we get that up and live as quickly as we possibly can? Because we think that's the best way to actually realize value." Look, these systems, what we're running at Oracle, as you know, these are highly complex mission-critical systems with decades of industry experience, decades of regulatory compliance, and these are the systems that our customers use to run their business, run their government agency, run their healthcare organization, whatever the case is. I really like our position here. As I said, we're leaning very heavily into AI ourselves. We have 1,000 AI agents already live in Fusion. Our banking suite alone has hundreds of AI agents just inside our banking solution. Yes, we think AI is disruptive. We do, but we think we're the disruptor because we're actually embedding the AI right into our applications, full stop. Again, at no additional cost. These are features that come in the application suite as part of quarterly upgrades, as part of a regular cadence. Instead of thinking that AI spells the death of SaaS, at least for Oracle, I think it actually helps our SaaS position, and helps us get to market even more quickly. We're thrilled with the results that we have and, you know, expect to have a lot more color on this as we go forward. Okay. Thank you. Our final question will come from the line of Brad Zelnick with Deutsche Bank. Please go ahead. Great. Thank you very much. I'll echo my congrats and also just say that the messaging is very, very clear and very helpful. My question is for Mike and perhaps Larry, and it extends on what Raimo's asked. You know, you've introduced AI Agent Studio inside of Fusion, and we all know that the crown jewels within an enterprise live inside of Oracle Database and Oracle Apps. I'm curious, how do you see Oracle's role evolving in a world where many other players are vying to be the AI interaction layer across multiple different enterprise systems and workflows? Brad, it's Mike. I'll start. Look, I think data gravity matters here, and I think mission-critical data gravity matters even more. As we said, we've announced the AI Agent Studio inside of Fusion. Fusion is a system inside our customers that is the custodian of their operational data, their mission-critical data. If you're gonna build a bunch of AI agents or your system integrator is gonna build a bunch of AI agents, the question I often have is. Where would you start? Well, you'd start inside the system of record. You'd start inside the system of gravity because that is the data from an inferencing standpoint, from retrieval augmented generation standpoint, it's gonna be highly relevant and highly specific and add a bunch of context to AI. Now, the AI Agent Studio that we've released in Fusion is not specific to just Fusion data. You can build AI agents across our industry applications, across third-party applications. Third parties can build AI agents in there. The fact that we're delivering, you know, an all-in-one best of solution, a full-scale SaaS application, AI-powered SaaS applications, and giving you the ability to create your own AI agents either on top of that or next to that in a standard upgraded quarterly platform release schedule, I think is going to be quite attractive. This AI Agent Studio that we built with Fusion, it's part of our quarterly upgrades. It's part of our quarterly, our regular security patching. You're getting the best, we think, of both worlds. You're getting packaged best applications. You're getting an Agent Studio, which is very, very close to the most mission-critical, germane data that enterprise possesses, and you're getting the ability to create your own custom bespoke agents, if you'd like to, as well. Yeah, I'll just end with we provide a bunch of pre-built agents for all of our applications. In addition, we provide a development environment, the AI data platform, the development environment that allow our customers to easily add their own agents to what we've built. We don't think we can build all the application agents for a banking system or all the application agents for a healthcare system. A lot of our partners are gonna do that, a lot of our customers are gonna do that. What the AI data platform does is it provides a complete integrated development environment where you can build your own agents using any AI model that is in the Oracle Cloud, and that is basically all of the popular AI models. You can use it for coding the agent, you can use it, yeah, you do multi-step reasoning for queries. You can. We plan in our Fusion accounting system, for example, we will have a complex agent that does something called the close. When you close your books with Fusion in the not too distant future, it will be an autonomous agent, no human beings involved. You will close your books by simply telling the AI agent to go ahead and close the books, and then you will get your results. We provide a lot of AI capability built into our applications, but they are open. They are open that allow our customers and our partners to add to that portfolio of agents, and we build an entire ecosystem that automates healthcare, automates financial services, automates retail. That is what AI is allowing us to do, is to expand our horizons for the scope of the suites of the SaaS software we're building to automate entire ecosystems. Let me talk about healthcare. In healthcare, Epic automates hospitals, acute care hospitals, in some cases clinics, but primarily acute care hospitals. We automate acute care hospitals, we automate clinics, we automate laboratories. Well, we automate the payers, the people who actually pay the. We automate the insurance companies. We automate the HCM system that trains their nurses, that schedules the right radiologist when an MRI is given, that automates the hospital's financials, that also automates the FDA and that approves the latest drugs, that deals with the pharmaceutical companies. That's the healthcare ecosystem. It's enormous. Thank God we have these coding tools now that allow us to build a comprehensive set of so ftware, agent-based software to automate a complete ecosystem like healthcare or financial services. That's what we're doing at Oracle. That's why we think we're a disruptor. That's why we think the SaaS apocalypse applies to others, but not to us. Really great stuff. Thank you, Larry. Thanks, Mike, and congrats. Thank you, Brad. With that, I'll. A telephone replay of the conference call will be available for 24 hours on our investor relations website. Thank you for joining us today. With that, I'll turn the call back to Regina for closing. This will conclude today's call. 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