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.

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.

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…

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…

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?

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.

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?

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.

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 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.

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?

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.

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?

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.

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.

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. 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.

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.

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?

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.

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.

That concludes today's call. You may now disconnect.