Serve Robotics SERV Q1 2026 Earnings Transcript

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Ali Kashani: Thank you, Steve, and good afternoon, everyone. Thank you all for joining us. We are in the early days of this robotics revolution, but our first quarter results show how quickly this market and Serve are moving. Q1 revenue was nearly $3 million, above our expectations and up nearly 7x year-over-year and nearly 3.5x sequentially. Last year, our focus was deploying 2,000 robots across 20 cities while also seeding the work to open new revenue streams and new market opportunities for our technology. This year, those investments are beginning to compound. Fleet revenue grew by an order of magnitude from about $200,000 in Q1 of last year to nearly $2 million this quarter.

In addition, about 1/3 of our total revenue during Q1 was from software services, and just under half of total revenue is now recurring. Last quarter, I said that 2026 would be a year of compounding return. Three months in, we are on track to deliver the $26 million of 2026 revenue we guided to on our last earnings call. Q1 is a clear proof of Serve's evolution. We are at the forefront of physical AI, not by just making big promises but by launching real robots in the real world at real commercial scale. With this early mover advantage, our focus now is growing the revenue streams that we've already built while also creating new one.

At the same time, we are advancing our technology, deepening our moat, introducing our platform to new markets that expand our opportunity and strengthening Serve's data and AI flywheel with new proprietary data. So let me go a level deeper. First, our autonomous food delivery operation continues to scale. Our deployed fleet is now 7x larger than in Q1 of last year, while daily active robots are up 10x and daily supply hours are up 13x over the same period. Put differently, as we expanded the total sidewalk fleet over the last 12 months, we activated robots more quickly in each market and generated even more hours from each robot.

Combined, Moxie and Serve robots now provide over 10,000 robot supply hours to our partners every day with more than 800 robots active every single day. To be clear, I don't expect every quarter to look like Q1, where we increased the active fleet and the fleet revenue by an order of magnitude year-over-year. Periods of growth often follow periods of investment, and they often need to be followed by more investment to support future growth. We expect Q2 growth to be slower as we work on expanding our geographic coverage and partnerships and capabilities in anticipation of the second half of the year when the growth picks up again.

Case in point, in the first half of the year, we are not deploying additional sidewalk robots beyond the 2,000 that are already in the fleet. Our focus is on operational growth and efficiency instead. That is getting the full delivery fleet running daily and improving utilization by activating more merchants as well as integrating more delivery platforms and expanding into new cities and neighborhoods. That is the worst that's in front of us now, and we expect it to drive significant growth over the course of the year, in line with our $26 million revenue guidance for 2026.

Our health care business, Diligent Robotics, we joined at the start of this year, is also performing in line with the plan that we laid out at announcement. The combined company is generating revenue and momentum across 2 distinct domains as we build toward a single autonomy platform. Since this is the first quarter Diligent is reflected in our results, I want to spend a moment on that business. Since closing, I spent a lot of time with Andrea and the Diligent team. A few observations that stand out. First, the team is excellent. They have long-standing experience operating in some of the most demanding environments in robotics, and they're also already teaching us a lot about indoor environments.

Second, the financials are in line with the plan that we laid out and the hospital pipeline for new business is healthy. Finally, Diligent continues to operate and grow, and I'm excited about the possibilities that are ahead. First, to bring our technology to more hospitals and over time, to extend it to additional indoor and outdoor environments. Now looking at the overall business again. The combination of our sidewalk and health care operations now gives us a footprint across 44 cities in 14 states with nearly 2 million deliveries completed across these domains. That is a meaningful expansion from where we ended 2025.

The growth came from 3 sources: new autonomous delivery markets that went live, including Buckhead, Fort Lauderdale and Alexandria, which we previewed previously; the hospital networks that came in with diligence; and continued expansion in our existing markets. I also want to say a word about safety. Our robots share space with people every day and earning the right to operate in those spaces is the foundation everything else is built on. To put the scale in perspective, during our operating hours each day, our robots collectively travel a distance greater than walking from New York to Los Angeles. That's every single day. And they do that with a stellar safety record.

Our robots have orders of magnitude less kinetic energy than cars. And to date, we've never had an incident resulting in a serious injury or anything approaching one. Every delivery completed by one of our robots is a delivery not made by a car. That matters for cities, for pedestrians and for our mission of making cities we operate in safer and more pedestrian-friendly. We are holding ourselves to a very high standard of safety across all environments we operate in. So to sum up, in operating terms, Q1 was a strong proof point.

We are running a scaled footprint, growing our revenue rapidly, improving margins, maintaining our reliability and safety records and expanding the markets that we are operating in. Stepping back and as we have discussed in previous calls, the foundation of everything we do is sales data and AI flywheel. Our fleet runs across more environments than anyone else in our category. The data those robots collect is richer than ever. The data trains better AI models, which makes every robot more capable. And as that suite becomes more capable, each robot can operate in more places and generate more value. Every robot will learn from every other robot even across different environments.

We have discussed our long-term vision for a self-fleet reaching 1 million robots deployed globally across cities and hospitals and other complex environments where robots and people share space. Over time, robots will become embedded in the core fabric of how modern cities and economies function. On the path to 1 million robots, we are still early, but we are building the platform across more fronts and more domains and a broader footprint than ever before. That gives us a stronger foundation to create a platform for robots of many future forms and functions and to navigate safely and effectively around people as the industry advances.

What we are building is genuinely hard, making one autonomy stack work across multiple physical environments at scale is one of the hardest problems in robotics today. We have always known this requires patience and persistence and rigorous execution. I'm really excited about the progress that we are making, and we'll keep sharing that progress with you every quarter. With that, I'll hand it over to Brian.

Brian Read: Thank you, Ali. Good afternoon, everyone. Q1 was an important quarter for Surge. Revenue scaled meaningfully. We began integrating Diligent Robotics, and we continue to broaden ways we monetize the autonomy platform through fleet, software, branding, data and health care automation revenues. Our focus this year is straightforward: improve robot productivity, increase revenue per robot and per operating hour, grow recurring revenue and translate those operating improvements into a stronger financial model. Q1 showed continued progress as we scale. Serve is building a network of robots that can operate across multiple real-world use cases, including food and health care today with opportunities for package delivery, health care logistics and other commercial tasks.

The common thread is simple, robots operating safely and reliably in complex human-centered environments. In Q1, our robot base continued to expand and our delivery network showed strong capacity growth. On an as-reported basis, daily active robots during the period was 812, up approximately 48% sequentially. Daily supply hours in the period averaged over 10,000, up approximately 54% sequentially. Those are strong capacity metrics, but the more important point is what comes next. Our objective is not simply to increase the number of robots in the field. Our objective is to convert every active robot in every supply hour into more revenue.

We are managing this through specific levers within the environments we operate in, whether that is market-level density, partner integrations, merchant coverage, speed, operational productivity and most critically, the autonomy improvements that reduce human touch points. The integration of Diligent expands the same platform into health care, where robots operate in hospitals and support recurring customer workflows. It gives us another operating domain, another data source and a revenue profile that is more recurring in nature. Strategically, this strengthens the autonomy flywheel Ali discussed. Sidewalks and hospitals are different environments, but both require robots to navigate safely around people, adapt to real-world complexity and perform reliably at scale. Put simply, 2025 is about proving we could scale the fleet.

2026, the focus is converting that scale into stronger revenue per robot and better operating leverage across the platform. Total revenue for Q1 was approximately $3 million, up 238% sequentially and approximately 578% year-over-year. On a pro forma basis, including Diligent, Q1 revenue increased approximately 28% sequentially and 30% year-over-year. Fleet revenue was approximately $2 million and software revenue was approximately $1 million, continuing to demonstrate the attractive margin profile for software and platform-based revenue layered on top of the deployed robotics base. This remains an important proof point for the broader platform model. Q1 included approximately $1.4 million of recurring revenue with the remainder from usage-based, project-based and other nonrecurring revenue streams.

The broader point is that Serve is no longer monetizing only food delivery. While that remains the primary growth engine, the revenue base now also includes branding, software, data and health care automation. This provides us more ways to monetize the same underlying autonomy stack and more levers to improve the long-term financial model. Gross loss for the quarter was approximately $9 million, and gross margin was negative 302%. That remains an investment-stage margin profile, but it improved materially from Q4 as revenue scaled and software revenue contributed positive gross margins. There are 2 different economic layers in the quarter.

Fleet gross margin remained negative as we supported a substantially larger fleet, integrated our health care fleet and built the operating structure required for a multi-domain robotics platform. Software gross margin was positive, which highlights the benefit of layering software and platform revenue on top of the robotics base. We believe the path to an improved margin is clear and measurable, more revenue per robot and operating hour, better operational productivity and a greater mix of recurring software and platform revenue. This is why our focus this year has evolved. Total robot count is still relevant, but it is not sufficient. GAAP operating expenses were $42.8 million in Q1.

Excluding stock-based compensation of $7.4 million and amortization and acquisition-related expense of $3.6 million, non-GAAP operating expenses were approximately $31.8 million. As expected, R&D remained our largest investment area. GAAP R&D expense was $19 million or approximately $15.5 million, excluding stock-based comp. This investment is directed towards autonomy development, AI model improvements, fleet softwares, data infrastructure and integration across our platforms. G&A expense was $15 million or approximately $8 million on a non-GAAP basis. Operations expense was $7 million or approximately $6.7 million on a non-GAAP basis. Sales and marketing expense was $1.9 million, approximately $1.7 million on a non-GAAP basis. Our discipline is not about underinvesting in the opportunity.

It is about aligning investment with the operating milestones that matter, revenue quality, margin improvement and platform differentiation. Every dollar should strengthen the autonomy platform, improve our fleet productivity, expand our commercial reach or increase the durability of revenues. GAAP net loss for the quarter was $49 million or negative $0.65 per share. Non-GAAP net loss was $38 million or negative $0.50 per share. Net cash used in operating activities was $41.4 million, while investing cash outflows were $19.6 million, driven primarily by acquisition activity. Capital expenditures were approximately $1.4 million in the quarter. We ended the quarter with $197.4 million in cash and marketable securities. This liquidity position remains a strategic advantage.

It gives us the ability to continue investing in autonomy and new market opportunities while maintaining discipline around the timing and scale of capital deployment. Turning to our outlook. We reiterate a total 2026 revenue guidance of $26 million. We continue to stay focused across the company with a priority to grow sustainable revenue quality and margin progression. We want to increase the mix of recurring revenue while continuing to bring down our unit costs through focused investments in autonomy and operational efficiencies. Accordingly, we maintain our previously communicated non-GAAP operating expense guidance of $160 million to $170 million during 2026. Let me close with this. Q1 was a quarter of integration and continued scale.

On a reported basis, first quarter 2026 revenue was greater than our total 2025 annual revenues. Curve is building a robotics platform, not a single-use delivery fleet. The investments we are making today are designed to improve autonomy, expand monetization and compound the value of our proprietary data across domains. We believe this, in turn, will improve robot monetization, capitalizing on our early leadership in physical AI to create a durable operating and financial model. With that, we'll open the line for Q&A.

Operator: [Operator Instructions] And your first question comes from the line of Colin Rusch of Oppenheimer.

Colin Rusch: Guys, you talked about the cadence of delivery times and speed of delivery being a key lever for you guys. Can you talk a little bit about the cadence of improvement in autonomy and how much is coming from scheduling and how you see that evolving over the course of the balance of the year?

Ali Kashani: Yes. Thanks for the question, Colin. This is Ali. We are improving a number of pieces, a lot of investments going into things like autonomy, which is a big factor because robots move faster than they are using their kind of capabilities and sensors to perceive the world than any other mode. The autonomy and speed basically going hand in hand. So as the robots become more capable, they can move more quickly. And that's one of the biggest areas of investment that we've continued to make from early days, but especially now.

Colin Rusch: Okay. I'll follow up off-line. And then with the communications platform that you guys have built and put together, it's clear that you've got a differentiated capability there. Can you talk a little bit about your potential to monetize that capability outside of your own internal usage?

Ali Kashani: Yes, that's already in progress. Hopefully, we'll have more to share about that soon, too. But there are a number of customers already using that service. For folks who are not familiar, one of the first pieces of software that we are commercializing in our robotic platform as a whole is the connectivity layer because having robots in the field in thousands that can reliably connect to the Internet so that they can share their data, but also receive support when they need it. It's a pretty important piece that pretty much every robotic and autonomy team or company needs. And we have a piece of technology that we believe is really superior to whatever is out there.

So we have been commercializing that. There's investments made, and there will be more to share in the next few months.

Operator: And your next question comes from the line of Alex (sic) [ Mike ] Latimore of Northland.

Mike Latimore: Great quarter, guys. I just want to start from the top with some broad strokes here. Can you talk about demand as you're seeing it? Will the market still take pretty much as many robots as you can deliver? Anything there would be great.

Ali Kashani: Alex, yes, again, I can take this. This, to me, feels like the closest thing to infinite TAM because it's such an expensive thing to move things in last mile right now. And we are seeing a lot of opportunities for new use cases or new customers that have never used the service. So we haven't really seen any constraint as far as demand goes. I think the parts of the problem that has to be solved as we scale has to do with policy and societal acceptance, obviously, building, deploying robots and getting it operationalized. Also integration into services that people use every day that takes effort and time.

But as far as the TAM and the total kind of opportunity, I'm very bullish on that.

Mike Latimore: Great. And then also now that you're moving towards optimization more trying to increase the daily revenue per robot, what are some of the key takeaways that you've learned just from going through head down on optimization flywheel here? And are there any notable changes given that experience?

Ali Kashani: I guess I'm trying to understand the question. Do you want to maybe state that differently?

Mike Latimore: Yes, yes. Just from focusing on optimization, I was wondering if there are any key learnings that you can take going forward towards incorporating new robots that you manufacture or just optimizing the rest of the fleet.

Ali Kashani: So from an operational point of view, I mean, the learnings come every day. It's about where do you send a robot in the morning. It's about where do you send a robot after it completes the job. It's about what's the range of deliveries you accept because if you accept longer deliveries, that means the robot is spending more time on that delivery. So you need to always kind of balance what's the distance of jobs that you accept and where do you put the limit on that. So there's a lot of interesting variables that are actually very market dependent.

And as we go to new markets, we basically have to customize that per market and sometimes even per neighborhood. So I wouldn't say there's anything really large as a learning because we've been out in the market for 7 years or something doing deliveries. It's mostly kind of ongoing learnings and then enabling the platform to do those customizations, so we can make neighborhood-based adjustments.

Mike Latimore: Awesome. And then just one more quick one. As you're looking to add robots in the second half, is it mainly going to be current city expansions or through adding new cities?

Ali Kashani: Yes, that's a really good question. So we are looking at basically both in the markets we are, but also in new cities and even international. So we are exploring all of them. For example, just last night, City of Vancouver in Canada approved the motion to enable the robots to deploy there in a pilot. That's not a done deal yet. We still have to work with them in the province, but it's very exciting. It would be the very first such deployments in Canada. So we are very actively working on unlocking these new markets and new cities, including some international auctions. And then as any of them firm up, we would obviously make announcements.

Operator: [Operator Instructions] And your next question comes from the line of Taylor Manley of Guggenheim.

William Taylor Manley: Kind of expanding on that. So you mentioned Vancouver, which is very exciting. More generally, there are some markets that you are in that kind of have established regulatory frameworks such as Los Angeles? Kind of on the flip side, you've highlighted ambitions to enter cities where AV delivery doesn't exist like New York. So kind of how does regulation inform your thinking on which markets to expand to or not, if at all?

Ali Kashani: Yes, it absolutely does. Our thinking is if you look at, again, the broader size of the opportunity, there's a lot of places to go and a lot of options to choose from. So we don't need to force ourselves anyway. We want to go to places that are receptive. There are really 3 kind of legs of the stool. You have the permit to operate. You have the demand, say, partners and platforms that we are working with. And then, of course, you have our operational side. We are pretty good at getting our operational set up in a new city.

So the other 2 variable is what we focus on to open a new market, which is, are they receptive? Is this a place we want to be? Do they have a framework? Do we need to help them develop it? So there are a lot of investments we are making to kind of create a strong pipeline of markets. And again, that includes both in the U.S. and international. And then at the same time, working with platforms, including new platforms besides Uber and DoorDash, to access the demand in those markets. So these are all investments that we are making simultaneously.

William Taylor Manley: Helpful. And then second, any insight on how to think about kind of revenue contribution from fleet services versus software services for the balance of the year? Obviously, software services was pretty strong in the first quarter. So just anything -- should we expect kind of similar mix or any changes there moving forward?

Brian Read: Yes. Taylor, this is Brian. So yes, we had a really strong Q1 with respect to software services. And I think we're going to continue to invest in some of those opportunities. In the back half of the year, as we continue to scale up with the revenue per robot per supply hour focus, I think we're going to see more growth on the fleet side. Obviously, we're not going to give guidance with respect to fleet versus software, reiterating and anchoring on the $26 million overall is the objective and monetizing those robots the best we can is our first focus.

Operator: And your next question comes from the line of Jeff Cohen of Ladenburg Thalmann.

Unknown Analyst: This is [ Destiny ] on for Jeff. I was wondering if we could talk a bit about Moxie and the hospital segment in general. Can you just talk about how you plan on maximizing revenue per hospital or robot and then how that may contribute to the top line and the cadence of how that will contribute to the top line going forward?

Ali Kashani: Yes, happy to. There's a number of, again, parts to this. So if you think about it very first principle, the main question is how much are the robots helping the staff in the hospital. So we have very explicit KPIs that we track to make sure that not only are we doing enough, we are improving and increasing the number of tasks and really deliveries that these robots complete, and that's trending always in a good way. And then, of course, as we do that, we can continue to work on the pricing with the hospital networks that we are working with.

Often, what we like to do is increase the number of robots because the more productive they are, the more they can support the staff in different ways. So one of the ways to maximize that revenue is to actually increase the fleet size.

Brian Read: And Destiny, this is Brian. Just to add on to that. I think to Ali's last point of increasing the fleet size, I think that's an opportunity we have for the remainder of 2026 to support the diligent efforts of the team through additional robots and thus ensuring we can grow that top line throughout the rest of the year.

Unknown Analyst: Okay. Perfect. And then one more for me. You've been very successful with M&A over the last several months. I'm wondering if you could hypothesize on what other verticals you think your autonomy stack would be suitable for, but recognizing that you've been clear that you're focused on optimization, not necessarily expanding into other verticals, just theoretically.

Ali Kashani: Yes. No, I appreciate that you calling that out. So we, even in the past, haven't been kind of proactively trying to look for expansion. It's been that we are very conscious of where the market is right now. A lot of investment on the private capital side has been made into various sectors in robotics. And right now, it's a very good time for consolidation. So we've been opportunistic, and we found some really amazing opportunities, obviously, Diligent being one of them.

So if you want to look at it more broadly, it's really anywhere where robots and humans have to coexist in an environment, but you don't really have control to limit that environment in any way for the robots. For example, in a warehouse, you have a lot of control over the environment, you can tell people how to behave next to the robots because they're all your employees, but in a shopping mall, you don't have that choice; at an airport, you don't have that choice; on a sidewalk, in a hospital. So I would say actually most environments that we are in would classify as that.

So any place where robots can help, whether they're moving things or monitoring things or just accessing in general would be a good place for this. And we'll keep our ears to the ground and when good opportunities show up, we'll react.

Operator: [Operator Instructions] And there are no further questions over the audio. I would like to turn the call back over to Steve for any e-mail questions.

Steve Webb: Yes. Thank you. We have one e-mail question, which is, what is the status of DoorDash? What's your relationship with DoorDash?

Ali Kashani: I can take that one. So a lot of great progress there. Our delivery volume with DoorDash has been growing faster than other partners. It's been about 6x in terms of merchant count just since the beginning of this year. So we are seeing really good momentum, and we are going to continue to build on that momentum.

Steve Webb: And that wraps it up. Thank you, everyone.

Operator: That concludes our session for today, ladies and gentlemen. Thank you, everyone, for joining. You may now disconnect.

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Serve Robotics SERV Q1 2026 Earnings Transcript was originally published by The Motley Fool