Serve Robotics Inc.SERVNASDAQ
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Operator: Hello, and thank you for standing by. I would like to welcome everyone to the Serve Robotics Third Quarter 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.
Aduke Thelwell: Thank you, operator, and good afternoon, everyone. Welcome to Serve Robotics' third quarter 2025 earnings call. With me today are Serve Robotics' Co-Founder and CEO, Ali Kashani, and our CFO, Brian Read. 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 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 have not already. With that, let me hand it over to Ali. Thanks, Aduke, and thank you, everyone, for joining us.
Ali Kashani: We are at a pivotal moment for Serve Robotics. This past quarter, we crossed the threshold for 1,000 robots deployed. That's not just some round number. It's 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 our 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, friendly and greener cities, and more prosperous businesses and workers. So why now? What's possible today that wasn't 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, lets us ingest orders of magnitude more sensor data. And 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 dataset. Each model update expands where, when, and how quickly, and how safely we can move. And 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 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 matches their demand by the hour. And that's what our fleet can deliver. And 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. And this is the future. Our robot's 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. And we create these new jobs, full-time employee jobs, in neighborhoods that we're serving. Our third-quarter 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 ninefold 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 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 a thousand, 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 3,000,000 population. And well over 1,000,000 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'd our fleet, we've 10x'd 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 DC 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 to 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. So this would actually improve utilization levels for robots. And we are 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. And while it's too soon to give details, we also expect to add another well-known national QSR brand to the lineup. So the partnership platform is growing nicely. And concurrently with that, we are also developing an unparalleled map of cities, the Kerck cuts and slopes and potholes and obstacles and patterns, a living atlas. That becomes a valuable asset and an operational advantage. And 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 Robotics 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 YU Robotics, our platform is now increasingly reinforced by AI foundation models and scalable simulation-powered data engine. Under the hood of all these is the physical AI flywheel that powers everything. Our third-generation fleet leverages the best-in-class sensors. Which creates these proprietary urban datasets. And that in turn leads to better AI models, which then creates more efficient and more autonomous fleets. A better fleet expands our TAM and increases our operating domain and verticals that we can do. And that, in turn, creates more pull in the market for more robots. So more miles, it's more robots, it's more data, it's better AI and the cycle repeats itself. The integration of YU 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 prey and detours it all provides the learnings that are applied network-wide. So every robot is learning from every robot. And 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. So 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. But we are not going to stop there. We envision a future where Serve Robotics' fleet reaches 1,000,000 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. It's not available. And we want to be the company that you will trust to run this. On the path to 1,000,000 robots, we are still early. But 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 Robotics 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.
Brian Read: Thank you, Ali. It's great to be with you all today. This quarter marked another step change for Serve Robotics. One defined not only by scale, but by strategic execution. We advance 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 integrated two key acquisitions that deepen our competitive moat. Acquiring YU, 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 YU into our autonomy stack, we expect it to create opportunities to enhance our leadership in 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 Robotics' 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 Robotics flywheel is accelerated. 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 run times 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 touch points 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 $30,400,000, 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 $21,800,000. R&D remained our largest investment area, totaling $13,400,000 on a GAAP basis or $10,700,000 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 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 literally increasing headcount or our overhead. Our approach remains consistent. Invest where we have clear line of sight to efficiency differentiation and scale advantage. While maintaining financial discipline and measured growth. On the balance sheet, we ended the quarter with $211,000,000 in cash and marketable securities. In October, we executed a soft sale that generated approximately $100,000,000, which will be used to fund working capital and expansion activities. CapEx for the quarter was $11,000,000 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 $24,900,000, driven by operational expansion in the quarter expected to accelerate efficiency through 2026. And 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 $2,500,000 in revenue for the full year 2025. Our underlying recurring fleet revenues, which exclude nonrecurring software, is projected to grow 3x year over year from roughly $600,000 in 2024 to roughly $2,100,000 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 an annualized revenue run rate of $60 to $80,000,000. We intend to update 2026 full-year guidance early next year. Initial indications show our expansion and operational plan positions Serve Robotics to deliver roughly a 10x inflection in revenue during 2026. Q3 marked another step forward in both scale and precision. Executing with discipline, expanding intelligently, and translating operational progress into tangible financial results. Each quarter, our fleet becomes more capable, models more refined, economics more efficient. The foundation we've built across technology, partnerships, operational excellence, position 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 Robotics 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.
Aduke Thelwell: 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 addition? Ali?
Ali Kashani: Thank you, Aduke. Yeah. I can take this one. So good question. We aren't going to share the specific numbers right now. Hopefully, we have more to share early next year. But I do want to explain how we are thinking about growth. As we are looking to get towards our 1,000,000 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 fleets 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. So in a way, being efficient and growth kind of line up together. So in that sense, it's the same type of effort that it takes to get there. So we are definitely going to push on growth, but we want to do it responsibly.
Aduke Thelwell: Alright. 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?
Ali Kashani: 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. So this both cuts down the cost of the material, but also the cost of assembly. At the same time as we improve our design, we've also benefited from our scale manufacturing. Obviously helps bring the cost down as well. And 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 bringing these advanced LiDAR sensors to market at scale. They're shipping a record number of sensors right now, I think thousands per quarter. And we are directly benefiting from that. And I think a lot of folks in the autonomous space would benefit from more affordable LiDAR sensors that just didn't seem within that realm just a few years ago. So 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. And, you know, we are going to keep pushing these improvements forward.
Aduke Thelwell: 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?
Ali Kashani: Yeah. We are working very closely with our partner 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 a thousand robots right now and soon 2,000 that can deliver for those customers. So the timing is perfect. And 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 multiplatform app approach. I think, you know, a single robot being able to alternate between the device from each platform from DoorDash and Uber, it's really, really important that we are able to do that, and I think we are now proving that we can. And this kind of interoperability actually increases our utilization, which in turn lowers the cost per day rate. And that actually benefits all of our partners as well.
Aduke Thelwell: Perfect. Thank you. We have a question on acquisition. Can you quantify the autonomy effect from YU? For example, with average speed increase or with the ratio of robot to operators improve? Brian, do you want to take this one?
Brian Read: Yeah, good question. And, I mean, I think the simple answer to start here is, you know, we're very early in this integration process to dive into those results exactly. And this is the type of integration that can take months. But, you know, we're actually doing the call here today from YU's office, and the excitement from the teams to hit the ground running as soon as the merger was completed was tremendous. And 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. You know, 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. And that, in turn, then drives efficiency and utilization ultimately landing in unit economics, and overall the benefit for these acquisitions.
Aduke Thelwell: 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?
Ali Kashani: Certainly. Yeah. You know, each city has its own distinct personality. It's like they're different in ways that's actually very helpful for us and honestly, 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, you know, what we had in Los Angeles before. They have different widths in their sidewalks, different nuances about how, you know, the best routes traversing would actually look like. Or our new market in Chicago, it's 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. So a lot of things that we tried to test in advance now are being put to test in real life. And 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. And the data in this new environment actually helps the model across the boards for the entire platform. And 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. So it kind of proves that the playbook is working well and the robots are getting smarter.
Brian Read: And just 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. So we're seeing, you know, shorter payback periods with the expansion. We're seeing the higher utilization as we deploy into new markets and neighborhoods. To continue the expansion. And that's exactly what we're building towards. So we've been, you talking internally about, you know, describing this as being sharper with our scale, and we believe all of these technology improvements are going to compound which will show up in our financial results. So, you know, that is really what's positioning us to expand in a disciplined capital-efficient way in 2026.
Aduke Thelwell: 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?
Ali Kashani: Yeah. This is a good question. You know, 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 robot. 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. And think, you know, we are trying to be smart and selective, in terms of who we engage with. And, you know, apply some filters there to pick the right partners. But the amount of inbound interest we're getting really reinforces that what we have is quite differentiated. And I'm hoping that as we move some of these conversations forward and, you know, have more updates to share, we'll actually tell you more about those relationships as well.
Brian Read: And if I can to also wrap a financial aspect into this question is, you know, 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. So that's going to enable our team to look at opportunities for, you know, adding more recurring software as we go throughout '26 and focus on that robotics and autonomy as a service offering. So it's really a long-term vision. Right? This is a balanced model. We're focused on diversifying revenue, and fleet revenue is that foundation. With software and data as that real high-margin accelerant. That we're focused on as we enter 2026.
Aduke Thelwell: Okay. And our last question, you mentioned the $60 to $80,000,000 run rate. When do you expect to reach that run rate? Brian, can you take this one?
Brian Read: Yeah. Let me give a little bit more color on, you know, in the script, we did mention the, you know, outlook for 2026. So we'll point everybody back to that commentary, but, obviously, this is a good question to end on here as we think about this Q3 update. So the path to hitting $60 to $80,000,000 is underway. Right? And that's really the final step when we think about the ambitions we laid out a few years ago to deliver 2,000 robots. Right? $60 to $80,000,000 is the, you know, the endpoint. But along the way, we've exceeded a lot of expectations. Especially as we near the end of 2025. And that's 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, you know, 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, you know, top-of-the-funnel orders into our pipeline. But last but not least, we have the acquisition. So across all of these, you know, 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, you know, great. But, critically, we're maintaining the safety and the reliability throughout that network as we're building. And so the final boss, as Ali likes to say, is to achieve that financial milestone is continuing to improve the utilization across the fleet. And so we have that momentum through 2025 and accelerating into 2026. To approach that $60,000,000 run rate target. Be clear, I think we're still more than twelve months out and we'll certainly, as we indicated, we'll have more to say on this in the next call. Early next year.
Aduke Thelwell: Okay. Thanks so much. That's all the time we have for today, and that concludes our session. Thank you for your thoughtful questions and participation. And with that, I hand it over to the operator.
Operator: That concludes today's call. You may now disconnect.