Good afternoon. I'm Ana Soro from Palantir's finance team. I'd like to welcome you to our Q2 2026 earnings call. We'll be discussing the results announced in our press release issued after the market closed and posted on our investor relations website. During the call, we will make statements regarding our business that may be considered forward-looking within applicable securities laws, including statements regarding our Q3 and fiscal 2026 results, management's expectations for our future financial and operational performance, and other statements regarding our plans, prospects, and expectations. These statements are not promises or guarantees and are subject to risks and uncertainties which could cause them to differ materially from actual results. Information concerning those risks is available in our earnings press release distributed after the market closed today and in our SEC filings. We undertake no obligation to update forward-looking statements except as required by law. Further, during the course of today's call, we will refer to certain adjusted financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute for or in isolation from, GAAP measures. Additional information about these non-GAAP measures, including reconciliation of non-GAAP to comparable GAAP measures, is included in our press release and investor presentation provided today. Our press release, investor presentation, and other earnings materials are available on our investor relations website at investors.palantir.com. Over the course of the call, we will refer to various growth rates when discussing our business. These rates reflect year-over-year comparisons unless otherwise stated. Joining me on today's call are Alex Karp, Chief Executive Officer, Shyam Sankar, Chief Technology Officer, David Glazer, Chief Financial Officer, and Ryan Taylor, Chief Revenue Officer and Chief Legal Officer. I'll now turn it over to Ryan to start the call. Our Q2 results are unprecedented but entirely unsurprising, as the abrupt market shift in LLMs that we've been warning you about for years is now here. We delivered 93% year-over-year revenue growth, our highest ever. The story of this quarter is, once again, our U.S. business. It now comprises over 81% of total revenue and grew 115% year-over-year and 23% sequentially. Our U.S. commercial revenue growth accelerated to 149% year-over-year and 28% sequentially. Our U.S. government revenue grew a remarkable 90% year-over-year and 18% sequentially. These top-line results are accompanied by a Rule of 40 score of 155 and $1.22 billion of adjusted free cash flow. We closed 220 deals worth $1 million or more, of which 98 deals were worth $5 million or more, and 73 deals were worth $10 million or more. Record highs across the board. These results are a clear indication of the profound value we've unlocked both for and with our customers who dared to cross the chasm with us. In contrast, enterprises that are not using Palantir are seeing their token meters spinning endlessly just to get slop without any correlation to value. This token model may be working for the labs, but it is not working for anyone else. It's breaking corporate budgets without results to justify the expense. Worse, companies are paying to give away their most important secrets, the very basis for their competitive advantage. Ultimately contributing to the commoditization of their own businesses as their secrets become the training data embedded in the foundations of all future models. On our side of the chasm, what enterprises demand is AI sovereignty, owning the operational definition of the data, logic, actions, and security of their enterprise. An organization's data is its treasure. In its richness is the alpha. We are fully aligned with our customers, building a stack that enables the compounding of their alpha. Our deep alignment allows our customers' ambitions and our own to become one. As Kirkland & Ellis highlighted, quote, "Through our work with Palantir, we have built a new operating model for legal services, one that centralizes and compounds the expertise of our most senior lawyers. What used to take days for a lawyer to analyze, discuss, and draft now happens in minutes. This would be impossible without the Ontology. We do not see this as a vendor relationship or a one-off endeavor. We think this is a revolutionary change in how our work gets done." This is what we do with our customers across industries. The deals we are closing are a testament to the monumental shift in the AI market that's underway as we speak. In our U.S. commercial business, we closed $2.1 billion in TCV with a 271% year-over-year growth rate on a dollar-weighted duration basis. A multinational technology company began working with us in the Q4 of last year at one operating company and expanded on their success with our platform to deliver revolutionary impact across their full portfolio, converting to a three-year, nearly $370 million deal last quarter. Customers are decisive and bold about taking the next step with Palantir. A global asset management firm started working with us in Q1, converted last quarter to a three-year $35 million TCV deal spanning asset management automation and investment lifecycle intelligence across four verticals. After an Agent Camp in May, a global software and services company signed an initial $15 million five-month deal last quarter. A leading nonprofit health system signed a pilot at the end of 2025, converted last quarter to a three-year partnership at $37 million TCV. Our U.S. government business remains a source of extraordinary strength, with momentum across both defense and civil. We continue to take great pride in our U.S. government work, equipping our nation with the most advanced battle-tested AI capabilities. For Palantir, this is our calling. Our customers are making the decision to go deep with us with greater urgency and conviction than I've ever seen before, choosing AI sovereignty over dependency and compounding their alpha in a way that their competitors and adversaries will forever envy. I'll now turn it over to Shyam. Thanks, Ryan. Ryan just talked about the incredible customer momentum behind sovereign AI. I want to spend some time on the underlying product investments that positioned us for this moment. AIP succeeded because it's the best, most ergonomic environment for AI in the enterprise. It integrates mixed model AI teams across heterogeneous, interdependent workflows and delivers the fastest implementations that turn tokens into real economic value for our customers in complex, high-stakes environments. What makes it work is exquisite and layered. Data integration and transformation, Ontology and actions, security and audit, workflows, agent SDKs, agent orchestration with telemetry and observability, evals and customer-specific benchmarks, AIP Evolve, and our latest investments in post-training, both supervised fine-tuning and reinforcement learning. Every layer builds on our foundational primitives, every layer flows together. This infrastructure captures the rich operational telemetry to feed the compounding loop, an automated model factory that runs inside the customer security boundary and accumulates intelligence in weights they control. Last quarter, I said tokens are the new coal and AIP is the train. Now our customers can build their own locomotives. AIP is where your sovereign AI is built, deployed, and compounded. We're excited for a new era, not one of benchmaxing, but of benchmaking. The assumption that the frontier is actually the best performing is just not borne out in practice. Within 24 hours of bringing Nemotron Ultra into our stacks, we found five production tasks where a standard Nemotron Ultra model without post-training beat frontier models. This underscores that a handful of common benchmarks can be gamed. That era, benchmaxing, has ended. The new era is benchmaking. A customer-specific benchmark is not just a scorecard. It's a hill to climb. It's the normative orientation that directs your entire operational workflows and post-training pipeline. It defines what better means on your terms for your business with your strategy, everything optimizes against it continuously. Because the benchmark is yours, the trade-offs become yours, too. AIP gives you the control plane to trade cost, performance, and latency against each other, and to decide where you run your weights versus theirs, workflow by workflow, continuously. You can have a continuous improvement cycle that compounds your alpha into your weights. AIP was built for this. We continue to see that our product is winning head-to-head. The others are focused on productivity. We are laser-focused on turning tokens into real economic value for our customers. The reality is that the market has created far more intelligence than it has converted into value. A more powerful model does not solve this problem. The limiting factor is the rate of AIP deployment. A major Silicon Valley tech company recently ran a bake-off, a frontier lab and its deployment team against AIP and our Forward Deployed Engineers. Remember, only Palantir has FDEs. Everyone else has sparkling sales engineers. The lab picked a ticketing automation problem and failed to deliver anything of value against it. We built agent swarms for each of our customers' customers, proactively recommending marketing, packaging, and pricing changes to drive revenue and utilization. This work converted into a $10 million ACV contract. The lab was shown the door. Same customer, same timeline, same models. The only difference was AIP and Palantir's unique FDE tradecraft, it was determinative. It was an incredible quarter in U.S. government, measured not just by 90% year-over-year revenue growth, but by mission impact. Maven continues to deliver for the Joint Force, from the factory floor to the foxhole. We had our first program in the Maven platform launched this past quarter, where a government program of record chose Maven as the platform that they will operate their program in, taking advantage of our open data standards, ontology, developer tooling, peering, security, and other platform primitives to go faster and deliver seamless experiences and capabilities to the department's chosen command and control platform. Maven has also continued to win as the developer and builder platform for the Joint Force. With over 25,000 builders, uniform service members, civilians, contractors, and companies are developing agents and applications in and on the platform at the speed of war. For all that growth, our Department of War trailing 12-month revenue is still less than 25 basis points of the Pentagon's budget. Finally, last week, we held our first American Builder Summit in D.C. to celebrate the Americans who stepped forward to join the American Tech Fellowship and to let them make the case that AI is creating jobs and prosperity by sharing their stories and showing what they built. We created ATF because the most transformative applications of AI that we saw were being driven by people without traditional tech backgrounds on literal front lines and factory floors. We now have over 1,000 ATF grads. One of our speakers, Jonah, who joined Tabet as a submarine parts manufacturer 13 years ago, straight onto the factory floor. He's a proud blue-collar worker who still turns wrenches for a living. He built an AI application that took production planning from 30 to 40 days down to less than one. AI alone cannot do that. It takes AI in the hands of the American worker, the tribal knowledge earned through success and failure on the line, the insights only they have. The models are commodities, the American worker is not. I'll turn it over to Dave to take us through the numbers. Thanks, Shyam. We had a phenomenal Q2, delivering our highest ever reported year-over-year revenue growth rate of 93% and our highest ever adjusted free cash flow of $1.22 billion, representing a 63% margin and 115% growth year-over-year. We surpassed billion-dollar milestones in GAAP net income, adjusted free cash flow, and adjusted operating income. Revenue in our U.S. business grew 115% year-over-year and 23% sequentially in the Q2. Our U.S. commercial business accelerated to 149% year-over-year and 28% sequentially, and our U.S. government business grew 90% year-over-year and 18% sequentially. We closed $2.132 billion of U.S. commercial TCV bookings, representing growth of 153% year-over-year and 81% sequentially, nearly $800 million above our prior highest U.S. commercial bookings quarter. We are seeing the immense demand of enterprises recognizing the need for sovereign AI to retain full control of their alpha. On the back of this exceptional continued strength in the U.S. and accelerating demand for our sovereign AI capabilities, we are raising our full-year U.S. Commercial revenue guidance to in excess of $3.424 billion, representing a growth rate of at least 134%. We are also raising our full-year 2026 revenue guidance midpoint to $8.154 billion, representing 82% growth year-over-year, an 11-point increase over our full-year 2026 revenue guidance from last quarter, and our largest ever full-year revenue guidance raise. Turning to our global top-line results. Q2 revenue grew 93% year-over-year and 19% sequentially to $1.935 billion. Q2 U.S. revenue grew 115% year-over-year and 23% sequentially to $1.573 billion. Revenue from our largest customers continues to expand. Q2 trailing 12-month revenue from our top 20 customers increased 67% year-over-year to $124 million per customer. Now moving to our Commercial Segment. Q2 Commercial revenue grew 110% year-over-year and 22% sequentially to $945 million. We closed $2.337 billion in Commercial TCV bookings in the Q2, representing 118% growth year-over-year. Our AI platform continues to dominate the U.S. market as the only real choice for operationalizing LLMs, particularly as more customers demand full ownership over the data, logic, actions, and security of their enterprise. Q2 U.S. Commercial revenue grew 149% year-over-year and 28% sequentially to $764 million. We closed a record-setting $2.132 billion of U.S. Commercial TCV bookings, representing growth of 153% year-over-year. Over the past 12 months, we closed $5.964 billion of U.S. Commercial TCV bookings, 117% increase from the prior 12 months, highlighting the accelerating demand for AI that creates real operational value. Total remaining deal value in our U.S. Commercial business grew 124% year-over-year and 27% sequentially. Our U.S. Commercial customer count grew to 653 customers, reflecting growth of 35% year-over-year and 6% sequentially. Q2 International Commercial revenue grew 26% year-over-year and 2% sequentially to $182 million. Revenue from strategic commercial contracts was approximately $400,000 for the quarter, representing 0.02% of overall revenue. We continue to expect revenue from these contracts to be less than $500,000 in each remaining quarter of this year. Shifting to our Government Segment. Q2 Government revenue grew 79% year-over-year and 15% sequentially to $990 million. Q2 U.S. Government revenue grew 90% year-over-year and 18% sequentially to $809 million. This growth was driven by continued execution in existing programs and new awards reflecting a growing demand for our AI platform in government. Q2 International Government revenue grew 42% year-over-year and 5% sequentially to $181 million. We closed $3.4 billion of TCV bookings, up 49% year-over-year. On a dollar-weighted duration basis, TCV bookings grew 129% year-over-year. Net dollar retention was 157%, an increase of 700 basis points from last quarter. We ended the Q2 with $13.1 billion in total remaining deal value, an increase of 83% year-over-year and 11% sequentially, and $4.9 billion in remaining performance obligations, an increase of 103% year-over-year and 10% sequentially. As a reminder, RPO is primarily comprised of our Commercial business as it does not take into account contracts with initial term of less than 12 months and contractual obligations that fall beyond termination for convenience clauses, both of which are common in most of our Government business. Turning to margin and expense. Adjusted gross margin, which excludes stock-based compensation expense, was 86% for the quarter and reflects an increase in costs associated with taking on cloud hosting for one of our Government customers. While this change led to higher cost of revenue in Q2, going forward, we believe it will power faster time to value, drive greater efficiency, provide greater cost certainty to the customer, and enable us to expand their future workflows. Adjusted income from operations, which excluded stock-based compensation expense and related employer payroll taxes, was $1.194 billion in the Q2, representing an adjusted operating margin of 62%. Q2 adjusted expense was $741 million, up 14% sequentially and 37% year-over-year, primarily driven by the continued investment in our AI platform and technical hiring. As in prior years, we expect a significant ramp in expense in the Q3 due to the seasonality of new hire starts and other product and marketing initiatives. We remain committed to investing in the most elite technical talent as well as R&D for our product pipeline and sovereign AI efforts, all while delivering on our goals of sustained GAAP profitability. Q2 GAAP operating income was $912 million, representing a 47% margin. Q2 GAAP net income was $1.062 billion, representing a 55% margin. Q2 stock-based comp expense was $265 million, and equity-related employer payroll tax expense was $17 million. Q2 GAAP earnings per share was $0.41. Q2 adjusted earnings per share was $0.41. Unrealized gains from our holdings in SpaceX resulted in a $0.03 tailwind to GAAP EPS and a $0.02 tailwind to adjusted EPS in the quarter. Our combined revenue growth and adjusted operating margin accelerated to 155% in the Q2, a 10-point increase to our Rule of 40 score from the prior quarter and our 12th consecutive quarter of an expanding Rule of 40 score. Turning to our cash flow. In the Q2, we generated $1.216 billion in cash from operations and $1.22 billion in adjusted free cash flow, representing margins of 63%. We ended the quarter with $9.2 billion in cash equivalents, and short-term U.S. Treasury securities. Turning to our outlook. For Q3 2026, we expect revenue of between $2.16 billion and $2.164 billion and adjusted income from operations of between $1.292 billion and $1.296 billion. For full year 2026, we are raising our revenue guidance to between $8.15 billion and $8.158 billion. We're raising our U.S. commercial revenue guidance to in excess of $3.424 billion, representing a growth rate of at least 134%. We're raising our adjusted income from operations guidance to between $4.889 billion and $4.897 billion. We are raising our adjusted free cash flow guidance to between $4.5 billion and $4.7 billion, and we continue to expect GAAP operating income and net income in each quarter of this year. I'll turn it over to Alex for a few remarks, and then Ana will kick off the Q&A. Obviously, we are loving these results and loving what they mean for our customers and broadly speaking, the West. Reflections on how we got to 93% aggregate growth, just under 150% growth in U.S. commercial, and an aggregate growth of 115% in America, which is astonishing, even surpassing the already anomalous results we've posted in the past and at a very significant scale. The story really does begin at the beginning when we dedicated ourselves to our most important partners in the U.S. government, and we built products to deliver value for them. We delivered those value for them by looking at the world in its naked state. We did not have AI available. We had to work with NLP, so we had to develop forward-deployed engineer model to extend the technology and deliver value. The nascent version of Ontology was developed. Shyam, Aki, others strapped BlackBerrys around their head and made the code work in sensitive environments. What we learned and what was built into this company is that there are things, values, structures that are more important than purely extracting value from a client. We rejected the way in which we were being taught in Silicon Valley to build a software company at the time. Palantir, of course, is now both infrastructure, software, FDEs, orchestration, and business know-how. It's a completely different hybrid. At the time, we were being told our job was to trick the clients into giving us money for something that made them attached to us, but really added no value. Essentially a parasitic model. In the rejection of that, we fully aligned with our partners. Now, to do that, as we went through the years, we built PG, Foundry, Gaia, Maven, Ontology, AIP. Now we're taking the AIP stack and extending it for sovereign AI, which requires us to be able to orchestrate and fine-tune models to provide a completely sovereign stack to our partners. What is the philosophical importance of that? We are offering a present that augurs to a future that we want to live in. What does that future look like? We have more rights in the PG frame. It's safer in the sovereign AI frame, which is arguably by far the most important because all these other things are downstream from GDP growth and GDP health, what if we transform America into the only democracy that actually grows where production is more efficient and manufacturing actually happens? What is that frame? That frame is not you are going to buy into a future where you have no job, where adversaries win, and everybody who does win is a small, tiny group of people living in a tiny place that somehow believes because they eat vegetables and they don't support war fighters, that they deserve to have the total means of production of this country. The rest of us should just sit back and absorb the cost of that revolution, which we're paying for. How are we paying for it? In the enterprise context, people sign up for token self-pleasurings, and that at a real cost like other forms of self-pleasuring, where you are paying for the right for them to migrate your IP, your know-how, your expertise to their model so that they can build a competitive business that doesn't require your business, your people. Why are they doing it? It's actually being done for what they believe are moral reasons. They are superior to you. They deserve to colonize your enterprise. You deserve to be colonized. Palantir, in A, it's interesting, it doesn't work as well or E is efficient purely on the alpha side as having an application layer, owning your compute. Witness, we built a partnership with NVIDIA. We're expanding our application layer. We are going to enter the market and already entering it in the classified space, as Shyam alluded to, of fine-tuning models. The model's actually fine-tuned by us in our enterprise on an NVIDIA stack, outperform frontier models, and you own the weights, you own the alpha. You own everything. Every single enterprise in this country is going to either look at doing this, find ways of doing it, or at least avoid the alternative of unprotected interaction with frontier models. This is very dangerous. You were warned about this in high school, and now you're learning about it in your enterprise. At Palantir, we are in the front of driving this revolution. I am driving the business to grow at a rate equal or above to what we have in U.S. commercial for the next 18 months, which is a very high goal, but it is one we can actually get to because we are fully aligned with what's right and what's good and what actually works well in an enterprise. For the first time, people believe us. If you didn't believe us, you can believe 149% growth in the U.S., a Rule of 40, that's 155%, 93% aggregate growth, and 90% growth in U.S. Comm with 62%-63% free cash flow margins. People thought we wouldn't be profitable. This is one of the more exciting times to be at Palantir. It's one of the more exciting times to participate in Palantir. For everyone on the sidelines, you got to get off the sidelines. This is a revolution that will affect the sovereign revolution. Where you stand in it will affect your livelihood, the livelihood of the people you care, and whether America and the West win. We cannot regress to a thin philosophical model where only a small group of people who think very differently than most of us actually absorb all of the revenue and value in our business and transfer all the dangers to us. That's what this revolution is about, and it's extremely motivating for those of us at Palantir. Thank you. Thanks, Alex. Our first question is from Dan with Yorkville Ives. Dan, please turn on your camera, and then you will receive a prompt to unmute your line. Where is the prompt? Well, while we are waiting, you can be entertained. Yeah. Maybe we can circle back to Dan. Our next question is from Mariana with Bank of America. Mariana, please turn on your camera, and then you will receive a prompt to unmute your line. I think I am good. Okay. Thank you. Can you walk through, at the Sovereignty Bootcamp, what did you learn with talking to customers that maybe you weren't expecting? Obviously, just an overwhelming sort of group of executives. Can you talk about that, Alex? First of all, for those of you not in the know, we did a Sovereignty Bootcamp after this kind of revolution exploded. Just to give the backdrop here, two years ago, we spent four or five months, Sasha, who runs this, organizing AIP Con. This was much more like, "Hey, let's invite our buddies over to lunch." All of a sudden, we start getting bombarded by people. People we invited, people we didn't invite, all levels of the business. When you're working in enterprise, it's really important that the operational people are interested. It was like CEOs, operational leads. There's a huge educational component, and Shyam talks about this a lot. People understand that they need a way of controlling their alpha. They understand broadly that token maxing is at their own cost, and they certainly understand that token maxing is leading to them transferring their data, their prompts, the way they run their business, their expertise to a third party. They need education on what they can do about that with us, preferably, but also without us. How do you do contracts? How do you work with open-weight models? How do you work with closed-weight models? How does this work in Ontology? Is Ontology the protective layer that they've been told? How would this look in their own business, and how would they work with the compute stack? There's just this massive demand, and we're in the business of educating people, both our customers and others. It was a super heterodox group of people, both in terms of the kind of people showed up, the demand for it, and also people we've not worked for. By the way, one of the reasons the NDR number is so strong, ridiculously strong. People always write these things about customer adoption and maybe, but the NDR number is anomalously strong. That is also going to shift and, as hard as it is to believe, become even more positive because some of our older partners we haven't really interacted with, they also showed up. They're like, "Oh, okay. Now we get why we would need you." Not just Foundry. They're migrating across our stack. Customers that were only using Foundry now want Ontology, now want to be part of the sovereign AI stack. I would say last not least, you're asking the internal version, external version. Internally, recruiting, retention, excitement at Palantir. I'm very excited. I think the people around this table are very excited. The legal department is excited. That hasn't happened. That doesn't happen. They're out like, "Rock on." It's more fun. That's the way this went down, and I think this is the way beginning. The way at least we think about this internally is what portion of a market is available to people who want to create value, mean create value, and keep it? That portion of the market has gone from a small portion of the market, where we were doing to a large part of the U.S. GDP. That's why we need partners. Behind the scenes now we're trying to find partners. Partners we need technically exceedingly competent partners. Partners doesn't mean a vassal. We don't have to agree on every issue. We don't even have to agree on every client. They can occasionally compete against us. We've seen this in the defense tech stuff, Stack and Shyam, like the approach to defense tech where we partner with people. Partner doesn't mean we agree. Sometimes we compete, but it means we're marching in a similar direction. It allows us to scale. Those things are going to be a very big important part of essentially the guide. Why am I pushing the company to grow not to just the end of the year, but next year? It's because that also forces us to find ways to scale to meet the demand that's out there. Thanks, Alex. Our next question is from Mariana with Bank of America. Mariana, please turn on your camera and then you'll receive a prompt to unmute your line. Good afternoon, everyone. Hello. Hi. Afternoon. A follow-up to Dan's question. When all this AI revolution started, right? It was really clear for enterprises that data and proprietary data and how you train your models was going to be the key. We're three years into that revolution, and now everyone started to realize, oh, owning my data and where they are learning from my data is important. What happened there? Why you think that you position yourself back then in a different approach to AI that enterprises weren't able to see? Why these numbers that reflect that you are the winner of AI today, it wasn't that clear for any other software application back then? You can kind of divide it up into two parts. There's the first part is efficacy, the second part is efficiency. That's not the quite the right word, but it's like, how do you scale it? In the zero to one phase, it's much more important to focus on the application layer. Okay, this new thing has happened, how do we turn that into economic value? As people started to experience the economic value, and as time started happening, you started to see that some of the people who were partners out there were building things that were competitive to you. I think that took some time to kind of seep into the psyche and mindset of, Now I know this thing is valuable in the right hands on the right platform, but I also am going to need to control the weights. That the alpha that is being generated isn't simply the data that's resident in my enterprise. It's also the metadata, the reasoning traces, the exhaust, the usage of this, which I don't yet have mechanisms to control. Now I understand that's actually probably more valuable than just the data in my enterprise. That's been a clarion call, I think, for the market over the last quarter, two quarters. There's also the question implicit in your question is, why did we get this right? Again, I think it's we are actually fully aligned with our partners. Sometimes we make decisions that are against our economic interests. We're supporting lots of institutions in Europe. The growth sucks. I mean clandestine institutions. Without our products, they would have rampant terrorism and their migration problems, and the results would be 10 times worse. It's not actually in our economic interest anymore to do this, but we still do it. It's because we actually are believers, for better or worse. I would say also, this is a company that from beginning, from inception, has valued artistic insights, meaning you can't model something purely on science. You have to have an aesthetic or artistic appreciation for it. We've made huge bets. Everyone sitting at this table and many, many hundreds of people at Palantir have essentially artistic insights. We've always viewed ourselves, we've always said we're a colony of artists, and people assume that means we're just difficult. That's also true. It's also we value insights that are way before anyone else would see them. We build major parts of our business. That's very hard for normal business to do because one of the jokes running around Palantir is we can definitely meet our guide next year if we get paid for all the people copying us. We get a small portion of people copy of the funds for the copiers, we do very well. Normal businesses, again, no critique here, are built around there was a playbook, we execute on that playbook, and we're in a non-playbook world. Executing on a playbook that worked 5, 10 years ago, essentially build parasitic software and monetize it, that doesn't work now. There's hundreds of variants of that, but that is a central advantage we have. We are a colony of believers and artists that are very motivated to drive value, that sets us aside much more than I would have imagined 10 years ago if you'd asked the same question. Luckily for us, this is capitalism. I mean, DSA wants to get rid of it, but until they do, you got to look at the results. The other thing I'll tell you that's very special for us, we are outsiders. Outsiders like you're an outsider. You come to this country, you better have really good results. Like the same thing for Palantir. We know we need the best results because people aren't buying our product because we're swinging the golf club correctly or paying for the steak dinner. They don't even invite us to steak dinners. That outsider status has caused huge problems in the first 18 years, but a lot of benefits in the next 18 years. Other people don't like being outsiders. In fact, I'm struggling with our current popularity. Thank you. Our next question's from Gil with D.A. Davidson. Gil, please turn on your camera, you'll receive a prompt to unmute your line. Thank you. On the topic of sovereignty, you focused a lot on how dangerous it is to give the keys to the labs because they could choose to compete with you. Is there another aspect of this as well, though, that if you choose a lab and you buy the orchestration and the consulting and the harnesses from them, you're beholden to their models, and if something happens, if it's not the best model anymore, if the model gets pulled, then you as a customer are stuck, and you may have a mission-critical system fail. This isn't hypothetical. This happened a couple of times this year, where one of the Frontier models got pulled by either the government or the company, while if you work with Palantir, I would assume that when that happens, you can go to your customer and say, "Hey, if that model doesn't work, I can plug in another model for you. No, I'll let Ryan and Shyam comment here. We're already doing that across the USG, U.S. government. We have a product that allows you to switch out models. Look, at the end of the day, if you are locked into a product, that's the nature of monopoly capitalism. That's why people want the lock-in, because then they can raise the prices and reduce the quality. We're against that because we're on the side of the American worker, the American people, and its great institutions, and other institutions across the West. Yes, people who are running big enterprises in this country are very sophisticated. They're aware of these risks, and they don't like people who are flaunting, setting this up so that they feel they're being made fun of, or they're a sucker, basically. Honestly, there's a lot of anger here. I spent, interestingly, a fair bit of my time trying to explain to people that some of the people involved in these things are not the caricatures they think they are. Because the business setup looks like heads I win, tails I win, and American business people don't like that. I don't know, there's a lot of things on the contractual front that would support that. Yeah, I would say our whole focus is converting tokens to value. The example Shyam gave, that's happening across the board in the conversations with customers. That's why they're looking to expand, to convert how they position themselves in the industry with us, in their industry. We're seeing extreme alignment. It's not about being beholden to one model. It's about bringing the right models to bear for the right purposes, and our contracts, our structures are set up to do that, to support and compound their alpha in the organization. I think I mentioned it earlier, you're going to see this. We've been beholden to a small number of benchmarks that people have been designing models to, and then releasing models saying, "Look how well it does on this benchmark." The benchmark has actually almost nothing to do with your business. How do you figure out how to make the benchmark that represents your reality, what you're trying to succeed at, what you're trying to get better at, and then see what model makes sense? The natural consequence of doing that, even leaving aside all of your other arguments for sovereignty, is like, "Oh, how do I climb that hill? How do I figure out what it is that I do as a business that I feed back into weights that I can control?" Which presupposes an open model and sovereignty. You're not just going to do that where you're waiting, "Hey, maybe I'll switch it out when this model gets pulled, when the rug gets pulled out from underneath me." You're actually going to be leveraging the automation to do that constantly, to figure out when you have a next checkpoint that you can afford. Maybe there's a new model. I mentioned the example. I literally almost felt gaslit when within 24 hours of getting Nemotron up with no post-training, this is vanilla Nemotron Ultra, it did better than Frontier. If you just looked at the numbers, you would say, "Well, it's nowhere near the Frontier. That shouldn't even be possible." Of course, the benchmarks are wrong. The benchmarks are right for what the benchmark's measuring. That's not my business. Those are not the tasks my customers had that they were trying to solve. Moving this to an empirical basis is, I think, is how we're going to accelerate the realization of tokens to real economic value. Thank you. Alex, as always, we have a lot of individual investors on the line. Is there anything you'd like to say before we end? Well, your support was crucial to getting us this far and crucial to getting us to where we're going to go, which is a much, much, much, much larger company. This is one of the most exciting times to be involved in the Palantir mission. We are going to help transform, especially this country, but allied countries, both in commercial and government. This sovereign frame that we're using as our organizational principle is one that is inclusive of everybody who wants to have a better world today and tomorrow, and we invite everyone to engage with it in some form. Thank you. Thank you. That concludes Q&A for today's call.