Hello, and thank you for standing by. I would like to welcome everyone to the Serve Robotics Q3 2025 Financial Results and Conference Call. Now, I would like to turn the call over to Aduke Thelwell, Head of Communications and Investor Relations. Please go ahead. Thank you, Operator, and good afternoon, everyone. Welcome to Serve Robotics Q3 2025 Earnings Call. With me today are Serve's Co-Founder and CEO, Ali Kashani, and our CFO, Brian Reed. During today's call, we may present both GAAP and non-GAAP financial measures. If needed, a reconciliation of GAAP to non-GAAP measures can be found in our earnings release filed earlier today. Certain statements in this call are forward-looking statements. You should not place undue reliance on forward-looking statements. Actual results may differ materially from these forward-looking statements, and we do not undertake any obligation to update any forward-looking statements we make today except as required by law. For more information about factors that may cause actual results to differ materially from forward-looking statements, please refer to the press release we issued today, as well as the risks and uncertainties described in our most recent annual report on Form 10-K and in other filings made with the SEC. We published our quarterly financial press release and our updated corporate presentation to our investor relations website earlier this afternoon, and we ask you to review those documents if you haven't already. With that, let me hand it over to Ali. Thanks, Aduke, and thank you, everyone, for joining us. We are at a pivotal moment for Serve. This past quarter, we crossed the threshold for 1,000 robots deployed. That is not just some round number; it is an inflection point. You can feel this in the sidewalks that we serve. The future of cities is autonomous, and we are at the forefront of this, turning it into daily reality in these neighborhoods across the country. This is not just swapping humans for robots. We are unlocking new possibilities for cities. We are rewriting the operating system of how cities function, how goods move, how spaces are shared, how businesses reach residents. When the whole system upgrades like this, everything gets better: safer streets, friendlier and greener cities, and more prosperous businesses and workers. So why now? What is possible today that was not possible before? There are four forces that have really converged. First is physical AI. It's really finally caught up with our ambitions. Advances in distributed training, also the better onboard compute that is now available, it lets us ingest orders of magnitude more sensor data. That leads to incredibly more capable AI models that can help machines really understand the world in real time. Our perception and planning models are improving on the streets every single day. Each mile traveled enriches our data set. Each model update expands where, when, and how quickly and how safely we can move. This all has a compounding effect. Second, every hardware component needed to create these advanced, inexpensive, and intelligent machines has matured. This includes powerful sensors that are now at mass scale and low cost, paired with electric motors and batteries that enable new vehicle form factors. Technologies like LiDAR sensors were unaffordably expensive just a few years ago, but now we have partners like Ouster who are shipping thousands of sensors each quarter in record numbers. That benefits everybody in the ecosystem because of the economies of scale. Third, consumers have adopted the convenience of online and on-demand ordering, and merchants need CapEx-light and labor-light capacity so that they can economically serve the demand. Restaurants have optimized their operations in the post-pandemic reopening, but they now need a way to unlock and realize that full potential. They want dependable, right-sized logistics that match their demand by the hour, and that's what our fleet can deliver. Last but not least, it's the cities themselves. Cities are asking for quieter, cleaner, and less congested streets. Smaller vehicles made for specific use cases can now replace those two-ton vehicles that we've become so addicted to. This is the future. Our robot footprint is small, with an electric powertrain and a friendly presence. We earn the right to scale when we operate with safety and transparency and community respect, and when we are working closely with the cities that we serve. We create these new jobs, full-time employee jobs in neighborhoods that we are serving. Our Q3 results prove that we are on the right track with all this. Our delivery reliability was nearly 100%, while our delivery volume increased 66% in a single quarter, and we continue to maintain a strong safety record. We now deliver for over 3,600 restaurants, which is an amazing 45% increase from the last quarter and more than a nine-fold increase since last year. This is all proof that autonomy can be safe, reliable, and predictable even as we scale rapidly. We did all this while also expanding faster than anyone in our industry. In less than a year, we grew our fleet size 10X, our cities 5X, and our major platform partners 2X. Last month, we announced partnering with DoorDash, the largest delivery platform in the US and one of the largest in the world. Combined, Uber and DoorDash serve over 80% of the food delivery market in the United States, which provides us an incredible reach to consumers and merchants. The scale that we've achieved in the last few months really changes things. Here's how to think about it. With a few dozen robots, you're running pilots. At a few hundred, you're starting to prove repeatability. Beyond 1,000, the system tips. We run more efficiently; the economics improve. The national partners really lean in, and our learning really speeds up, all of which makes every new city launch smoother and every new robot smarter than before. As we scale with precision, we've gone from one market to five fully operational hubs covering over three million populations and well over one million households. That's nearly a 70% increase in a single quarter and more than a tenfold increase in our coverage compared to the same time last year. Not only have we 10X our fleet, we've 10X our reach. And as importantly, each neighborhood adds to our reach data sets with new and novel edge cases, which really accelerates our ability to learn across the network and it compresses our timeline for future city launches. On that note, I'm excited to share with you our next three expansions. We've just been greenlit to expand into Buckhead, Georgia, Fort Lauderdale, Florida, and Alexandria, Virginia, before the end of this year. Alexandria also gives us a toehold in the Washington, D.C. area. We're building the first truly national interconnected autonomous delivery network on a common AI software platform and operations stack so that a single partner integration would light up multiple metros and thousands of restaurants at once. For example, in Q3, we announced our partnership with DoorDash. Coming in addition with our existing contract with Uber, this allows our existing robots to unlock an incredible amount of additional volume. A robot that's completing a delivery for DoorDash could do a delivery for Uber on its way back. This would actually improve utilization levels for robots. And we're not done yet. In addition to our existing partnerships with Shake Shack and Little Caesars, we've also started delivering for Jersey Mike's Subs, the famed sub sandwich chain with over 3,000 locations nationwide. While it's too soon to give details, we also expect to add another well-known national QSR brand to the lineup. The partnership platform is growing nicely. Concurrently with that, we are also developing an unparalleled map of cities: the Cape Cods, and slopes, and potholes, and obstacles, and patterns, a living atlas that becomes a valuable asset and an operational advantage. While we do that, we are also deepening our community bonds at a very hyper-local level. With merchants and landlords and HOAs and precincts, we need to integrate respectfully into these neighborhoods as we grow. Now, let's take a step back. Serve is pioneering a robotics and autonomy as a service platform that packages the full power of our autonomy stack, our hardware, and our urban robotics operation playbook. With the last quarter's acquisition of Vayu Robotics, our platform is now increasingly reinforced by AI foundation models and a scalable simulation-powered data engine. Under the hood of all this is the physical AI flywheel that powers everything. Our third-generation fleet leverages the best-in-class sensors, which creates these proprietary urban data sets, and that in turn leads to better AI models, which then creates more efficient and more autonomous fleets. A better fleet expands our time and increases our operating domain and verticals that we can do, and that in turn creates more pull in the market for more robots. More miles, it's more robots, it's more data, it's better AI, and the cycle repeats itself. The integration of Vayu will actually accelerate this loop because it turns data into better models faster, and that leads to tangible gains in our delivery speed and autonomy and the market reach. Our library of long-tail edge cases is expanding faster than ever, and the latest data that we gather on weather and obstacles and parades and detours, it all provides the learnings that are applied network-wide. Every robot is learning from every robot. This AI flywheel that we are building, the flywheel that's now accelerating, in turn attracts exceptional talent. Our rare data scale and this real-world fleet presence that we have is pulling in elite builders, and they in turn ship better systems, and better systems attract even more elite builders. The talent flywheel is also compounding. All the forces that I mentioned are helping us execute our vision. I'm really proud of our team for reaching the 1,000 robot milestone last quarter. In September alone, we shipped over 380 robots. That is in a single month. That means we launched more robots in a single month than the prior quarters. This was a pivotal milestone. We promised to ship 2,000 robots by the end of the year during our IPO, and we are on track to do it with robot number 2,000 planned to deploy in Miami in mid-December. We are not going to stop there. We envision a future where Serve's fleet reaches one million robots deployed across cities globally. They will travel billions of miles annually. They become embedded into the core fabric of a modern city, and they unlock new possibilities. Our conviction is simple. We are entering the age where things will move at our will, but on their own. Autonomy will become this essential infrastructure in our lives. It's rarely noticed because it just works, but it's sorely missed when it's not available. We want to be the company that you will trust to run this. On the path to one million robots, we are still early. With 1,000 robots operating from coast to coast, we've really just crossed that chasm where the technology and the market all say go. From here, every additional robot, every additional hour, every additional block makes the whole Serve ecosystem more essential and more valuable to the entire network. We're building something durable, and we are just getting started. With that, I'll turn it over to Brian to cover our Q3 results in more detail. Thank you, Ali. It's great to be with you all today. This quarter marked another step change for Serve, one defined not only by scale, but by strategic execution. We advanced in every meaningful area, expanding our fleet, strengthening our technology base, and executing with greater precision across operations, engineering, and finance. We've also been extremely opportunistic. During the quarter, we've integrated two key acquisitions that deepen our competitive moat. Acquiring Vayu, a pioneer in urban robot navigation using large-scale AI models, we're expanding our physical AI capabilities by accelerating our roadmap. As we further integrate Vayu into our autonomy stack, we expect it to create opportunities to enhance our leadership and autonomous delivery, as well as to reduce data infrastructure costs and improve operational metrics over time. These integrations allow us to convert more of our operational data into faster model improvements and richer monetization layers, all while reinforcing Serve's position as the category's innovation leader. Our focus remains clear: to scale efficiently, deploy capital strategically, and translate our growing operational advantage into sustainable financial performance, all in service of building an enduring business in this new age of autonomy and physical AI. As Ali described, the Serve flywheel is accelerating: more robots, richer data, smarter AI, and stronger economics. Let's dig into our Q3 results, showcasing how these effects translate into measurable financial impact and expanding leverage across our business. Total revenue for Q3 2025 was $687,000, an increase of 210% versus last year, and in line with our guidance provided for the quarter. Fleet revenue was $433,000. Significantly, this quarter, we saw branding revenue jump 120% sequentially over Q2. As we've mentioned previously, the growth of our robot fleet into the thousands unlocks a pipeline of large-scale branding opportunities, and we delivered on that in Q3. Software revenues continued to transition from one-time to recurring and were $254,000 in the quarter. We delivered exactly what we said we would. Fleet revenue is becoming the predictable growth engine we've envisioned, and we're now meaningfully stacking platform and data services on those same routes. Gross margin performance this quarter reflected the balance between rapid fleet expansion and deliberate investment in our long-term efficiency infrastructure. As planned, we continue to build capacity ahead of 2026 scale, expanding our operations footprint, onboarding new cities, and integrating the systems and teams from our recent acquisitions. These near-term investments are already yielding returns in the form of measurable operational gains across reliability and autonomy. Average daily operating hours per robot increased another 12.5% sequentially from Q2, driven by the growing mix of Gen 3 hardware across our fleet. This is a strong leading indicator that each unit is capable of contributing more value. Robot intervention rates saw a meaningful reduction through the quarter, and further, our best-in-class sidewalk autonomy is getting more and more capable. We saw a consequential increase in the proportion of miles driven in autonomous mode in the last week of Q3 compared to the first week of the quarter, indicating the return on continued R&D investment. Taken together, these factors drove higher autonomous runtimes, which in turn drive improvements in our average speed. This leads to compounding gains. Even a small increase in the average speed corresponds to an increase in our potential delivery volumes. These efficiency improvements are compounding. Each additional robot, each additional mile, and each new market contributes data that sharpens our models and reduces human touchpoints across the network. On the expense side, we remain disciplined, investing in the capabilities that drive our competitive advantage. GAAP operating expenses for Q3 were $30.4 million, increasing from Q2 from deliberate investments in new market launches, M&A integrations, and expanded operational capabilities to support our national scale. On a non-GAAP basis, operating expenses were $21.8 million. R&D remained our largest investment area, totaling $13.4 million on a GAAP basis or $10.7 million on a non-GAAP basis, primarily directed towards advancing our autonomy stack, expanding our AI foundation models, and integrating new data and hardware capabilities from our recent acquisitions. These initiatives are accelerating our pace of innovation while positioning us for a long-term cost structure. G&A and go-to-market spending remain disciplined and aligned with our city expansion cadence. We're executing with leverage, adding cities, partners, and robots without linearly increasing headcount or our overhead. Our approach remains consistent: invest where we have a clear line of sight to efficiency, differentiation, and scale advantage while maintaining financial discipline and measured growth. On the balance sheet, we entered the quarter with $211 million in cash and marketable securities. In October, we executed a stock sale that generated approximately $100 million, which will be used to fund working capital and expansion activities. CapEx for the quarter was $11 million tied to robot production, market launch, and expansion infrastructure. Our strong liquidity and debt-free balance sheet remain a competitive advantage, providing us flexibility to scale responsibly and invest opportunistically. Adjusted EBITDA was negative $24.9 million, driven by operational expansion in the quarter expected to accelerate efficiency through 2026. Now to our outlook. Once again, we delivered results at the high end of our Q3 guidance range. Building on this momentum, we now expect to generate more than $2.5 million in revenue for the full year 2025. Our underlying recurring fleet revenues, which exclude non-recurring software, are projected to grow 3x year over year from roughly $0.6 million in 2024 to roughly $2.1 million in 2025. 2025 was a pivotal year focused on establishing our national footprint, deploying 2,000 robots, expanding into new markets, and deepening our partnership portfolio. With this groundwork in place, we remain confident in our ability to generate annualized revenue run rate of $60-$80 million. We intend to update 2026 full-year guidance early next year. Initial indications show our expansion and operational plan positions Serve to deliver roughly 10x inflection in revenue during 2026. Q3 marked another step forward in both scale and precision. We're executing with discipline, expanding intelligently, and translating operational progress into tangible financial results. Each quarter, our fleet becomes more capable, models more refined, and economics more efficient. The foundation we've built across technology, partnerships, and operational excellence positions us for sustainable growth through 2026. We're proud of what the team has accomplished this quarter and even more excited about the opportunities ahead. Serve is defining this category, and we're confident in our ability to lead it for years to come. With that, I'll hand it back to Aduke for Q&A. Thank you, Ali and Brian. We will now move into the Q&A session. First, I'd like to say a big thank you to all the investors and analysts who submitted questions via email. We really appreciate your engagement. First question, I think this might be for Ali. Do you expect to add more robots in 2026? If so, what would be the timing and magnitude of the additions? Ali? Thank you, Aduke. Yeah, I can take this one. Good question. We aren't going to share the specific numbers right now. Hopefully, we have more to share early next year. I do want to explain how we are thinking about growth. As we are looking to get towards our one million robots goal, what we want to do is make sure we grow quickly, but also with precision and discipline. We've been really laser-focused in getting the fleet really efficient and effective every day and driving utilization, while at the same time layering new partners, going to new geographies. All of this makes that scale-up easier. In a way, being efficient and growth kind of line up together. In that sense, it's the same type of effort that it takes together. We are definitely going to push on growth, but we want to do it responsibly. All right. Thank you. Next question is about robot design. Could you provide details on robot design simplification and cost reduction beyond economies of scale? Ali, do you want to take this one? Yeah, I'll take this one too. I think there's a few different factors here. First of all, there's a ton of progress that we've made when it comes to the robot design. We've made it a lot more modular, easier to manufacture, fewer custom assemblies. We've also really strengthened our supply chain to get better parts and at lower prices. This both cuts down the cost of the material, but also cost of assembly. At the same time as we improve our design, we've also benefited from our scaled manufacturing, which obviously helps bring the cost down as well. While all of that is happening, the broader kind of ecosystem of suppliers, they're also getting more mature. I think a really good example that I'm excited about is Ouster. They have done a phenomenal job of bringing these advanced LiDAR sensors to market at scale. They're shipping a record number of sensors right now, I think thousands per quarter. We are directly benefiting from that. I think a lot of folks in the autonomy space would benefit from more affordable LiDAR sensors that just didn't seem within that realm just a few years ago. Combining our improvements to the design and our improved supply chain and our scaled manufacturing and the maturity of the ecosystem, that per unit cost of the robots is definitely coming down substantially to the point that, as we've shared in the past, our Gen 3 robots are a third the cost of our Gen 2 robots. We are going to keep pushing these improvements forward. Okay. Thank you for that. Next question. What are the next steps in your DoorDash relationship? How do you see that helping the business? Ali? Yeah, we are working very close with our partner at DoorDash. First and foremost, it's about integrating the robots into the fleet in a thoughtful way and planning the market rollouts over time. DoorDash obviously unlocks an enormous network of restaurants and consumers for us. We have over 1,000 robots right now and soon 2,000 that can deliver for those restaurants and customers. The timing is perfect. I expect that in the next few months, we will start to really grow the volume under the new channel with DoorDash, basically. I do want to emphasize this is a really important milestone for us because we've always envisioned this multi-platform approach. I think a single robot being able to alternate between deliveries from each platform, from DoorDash and Uber, it is really, really important that we are able to do that. I think we are now proving that we can. This kind of interoperability actually increases our utilization, which in turn lowers the cost per delivery. That actually benefits all of our partners as well. Perfect. Thank you. We have a question on acquisitions. Can you quantify the autonomy effect from Vayu? For example, would average speed increase or would the ratio of robots to operators improve? Brian, do you want to take this one? Yeah. Good question. I mean, I think the simple answer to start here is we're very early in this integration process to dive into those results exactly. This is the type of integration that can take months. We're actually doing the call here today from Vayu offices and the excitement from the teams to hit the ground running as soon as the merger was completed was tremendous. There's just a lot of excitement on both sides to go faster and deeper into that roadmap to bring those new capabilities into the fleet. I think we think about it as part of a flywheel where over time, that integration will allow our robots to be faster and smarter while maintaining the safety and reliability that we focus on daily. That in turn then drives efficiency and utilization, ultimately landing in unit economics and overall the benefit for these acquisitions. Okay. Thank you. Our next question. What are some differences between deployments in different cities? What have you learned from new deployments and expansions that will help you scale further? Ali, can you take this one? Absolutely. Yeah. Each city has its own distinct personality. It's like they're different in ways that's actually very helpful for us and honestly quite fun for our team as we've been expanding, seeing, for example, in Atlanta and Miami, learning about humidity and the different kinds of pedestrian intersections and city design compared to what we had in Los Angeles before. They have different width in their sidewalks, different nuances about how the best routes for traversing would actually look like. Our new market in Chicago is an incredible place for getting data on really dense urban environments with cold weather where you have to look at battery efficiency and snow detection and traction. A lot of things that we have tried to test in advance now are being put to test in real life. We are learning a lot from that. What's really powerful, I think, is that as we go to these new cities, it really enriches the models. The data in these new environments actually helps the model across the board for the entire platform. That actually means that every subsequent city launch, as I mentioned earlier, gets more reliable and better. In fact, we saw this in Chicago when we first launched. It was the fastest market for us to get to our SLAs that were comparable to our more mature markets. It kind of proves that the playbook is working well and the robots are getting smarter. J ust to finish that from a financial standpoint, I think too is we're using these learnings. We're translating them directly into efficiency through our operations teams. We're seeing shorter payback periods with the expansion. We're seeing the higher utilization as we deploy into new markets and neighborhoods to continue the expansion. That's exactly what we're building towards. We've been talking internally about describing this as being sharper with our scale. We believe all of these technology improvements are going to compound, which will show up in our financial results. That is really what's positioning us to expand in a disciplined, capital-efficient way in 2026. Okay. Thank you. Next question. What can you share about the pipeline for software and data sales? How are you looking to accelerate software revenues in 2026 and beyond? Yeah, this is a good question. The revenue pipeline for these other opportunities, like the delivery platform, the software that's powering the robots, as well as the data that's generated by the robots, it's been a really strong pipeline. We are in substantial discussions with multiple partners that want to basically use the platform or the data that we are creating. I think we are trying to be smart and selective in terms of who we engage with and apply some filters there to pick the right partners. The amount of inbound interest we're getting really reinforces that what we have is quite differentiated. I'm hoping that as we move some of these conversations forward and have more updates to share, we'll actually tell you more about those relationships as well. If I can also wrap the financial aspect into this question, as the fleet scales, these data and AI insights are going to become more valuable, right, to all of the people Ali just mentioned that we're talking to and the substantive discussions we're having. That's going to enable our team to look at opportunities for adding more recurring software as we go throughout 2026 and focus on that robotics and autonomy as a service offering. It's really a long-term vision, right? This is a balanced model. We're focused on diversifying revenue. Fleet revenue is that foundation with software and data as that real high-margin accelerant that we're focused on as we enter 2026. Okay. Our last question. You mentioned the $60 million-$80 million run rate. When do you expect to reach that run rate? Brian, can you take this one? Yeah. Let me give a little bit more color. I know in the script we did mention the outlook for 2026. We'll point everybody back to that commentary. Obviously, this is a good question to end on here as we think about this Q3 update. The path to hitting $60 million-$80 million is underway, right? That is really the final step. When we think about the ambitions we laid out a few years ago to deliver 2,000 robots, right, $60 million-$80 million is the endpoint. Along the way, we've exceeded a lot of expectations, especially as we near the end of 2025. That has been a testament to the team and how we've delivered. I mean, to summarize what we've talked about on a lot of the earnings calls, we are on track to deliver the 2,000 robots. We've expanded into multiple markets with more coming. We talked about new partnerships and adding top-of-the-funnel orders into our pipeline. Last but not least, we have the acquisition. Across all of these verticals, we are firing and we're really exceeding what we set out to achieve in 2025. I'd like to remind investors and anybody that wants to understand our story that that's all great. But critically, we're maintaining the safety and the reliability throughout that network as we're building it. The final boss, as Ali likes to say, is achieving that financial milestone, is continuing to improve the utilization across the fleet. We have that momentum through 2025 and accelerating into 2026 to approach that $60 million run rate target. To be clear, I think we're still more than 12 months out. We'll certainly, as we indicated, have more to say on this in the next call early next year. Okay. Thanks so much. That's all the time we have for today. That concludes our session. Thank you for your thoughtful questions and participation. With that, I hand it over to the operator. That concludes today's call. You may now disconnect.