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Presentation

Operator: Ladies and gentlemen, thank you for standing by. My name is Joyce, and I will be your conference operator today. [Operator Instructions] I would like to welcome you to AEye’s First Quarter 2026 Earnings Call. I would like to turn the conference over.

Keaton Olson: Good afternoon, and thank you for joining AEye’s First Quarter 2026 Earnings Call. I’m Keaton Olson, Investor Relations Manager for AEye. And with me today are Matt Fisch, Chief Executive Officer; and Conor Tierney, Chief Financial Officer. Earlier today, AEye announced its financial results for the first quarter ended March 31, 2026. A copy of the press release is available in the Investor Relations section of the company’s website. Before we begin, today’s discussion may include forward-looking statements as defined in the securities laws and regulations of the United States with reference to future events, operating results or performance and are based on our current expectations and assumptions. Any forward-looking statements are subject to inherent risks, uncertainties and changes in circumstances.

Our actual results may differ materially from those contemplated by these forward-looking statements. You can find more information about the risks, uncertainties and other factors in the reports AEye files from time to time with the Securities and Exchange Commission, including in our most recent periodic report. The statements to be made are as of today only, and AEye does not intend to update any forward-looking statements regardless of any new information, future developments or otherwise, except as may be required by law. In addition, we will be discussing non-GAAP financial measures on this call, which we believe are relevant in assessing the financial performance of the business. These measures are presented as supplemental information only and should not be considered a substitute for financial information presented in accordance with GAAP.

You can find reconciliations of these metrics to the most directly comparable GAAP measures within the press release. Now let me pass the call over to Matt.

Matthew Fisch: Thank you, Keaton, and thank you all for joining our first quarter 2026 earnings call. The quarter unfolded exactly as planned, steady execution, no surprises and a commercial pipeline that continued to grow. Our ecosystem partnerships and manufacturing capability remains strong, and we now have more commercial engagement than at any point in our history. Our funnel continues to be the best barometer to benchmark our progress as revenue tends to be a lagging indicator. As of today, our revenue-generating customer count has grown from 15 to 21 since our last earnings call. I’m also pleased to report that both our issued quotes and active engagements have increased by nearly 40% quarter-over-quarter. These leading indicators, new technical engagements, inbound RFIs and POC activity across automotive, trucking, defense, rail, infrastructure and ITS are all moving in the right direction.

These indicators are the data that investors should focus on to understand where we are headed. Quarterly revenue is up almost 60% year-over-year. This meaningful growth is driven by our software-defined architecture and long-range sensing performance and reflects the strong pipeline activity building behind it. AI’s technology gives machines vision, the foundation of physical AI and the prerequisite for every intelligent autonomous system being built today. The market is potentially very large and is accelerating. Barclays projects the physical AI market opportunity could reach as much as $1 trillion by 2035, and LiDAR is the enabling layer that makes it real. AI software-defined architecture positions us at the core of that ecosystem and the LiDAR sector’s ongoing consolidation has only strengthened our relative position.

AI is on stronger footing coming out of that consolidation than going in, better capitalized, leaner in structure and with a commercial pipeline that continues to expand. The automotive industry appears to be squarely shifting toward AI-driven safety and software-defined vehicle architectures. And we believe long-range LiDAR is becoming essential to that architecture, not optional. Apollo offers best-in-class detection range when operating behind the windshield and is the only sensor we know of to be customer proven to reliably detect objects at distances of up to 1 kilometer. Our OEM engagement has increased, driven by recent robotaxi investment announcements, growing trade policy implications and supply chain resilience concerns with OEMs in the passenger vehicle segment actively seeking domestically sourced alternatives.

AI’s manufacturing partnership directly addresses that demand. Multiple new RFIs arrived in Q1 across both passenger and commercial vehicle segments and OEMs have begun to reengage as L3 and L4 road maps are being reactivated and expanded. In ground mobility, evaluations by autonomous trucking companies are deepening. Multiple companies have programs underway, and we are now shipping sensors into those evaluations. Apollo should be well suited to serve this expanding addressable market. In transportation and infrastructure, Optus is now live at an active intersection in California in partnership with FlashEye and BlueBand. Additional U.S. smart intersection deployments are in progress. Our APAC expansion strategy is also progressing. An Australian ITS POC has advanced into a discussion of commercial terms.

In Korea, we recently concluded a successful customer roadshow engaging with more than 10 OEMs across ITS, rail and mobility sectors. Our business partnership with ATI in China remains strong, and we have 4 additional customers now evaluating our Apollo LiDAR product. In defense, active shipments continue with an existing U.S. contractor for UAV wire detection. Repeat business is emerging within that account, and Apollo is being evaluated for additional applications, including UGV and counter UAV with an expectation of multiple new RFQs. A significant development this quarter is our new commercial relationship with Syntech, a global defense systems company with established ties to leading defense prime. Syntech is actively promoting Apollo to its customers and initial shipments are already underway.

This partnership has the potential to unlock international defense and aviation market outside of the United States, meaningfully expanding our addressable pipeline while complementing the domestic engagements we have already built. What drives selection across all of these verticals is consistent. AI’s proven and reliable 1-kilometer detection range with unlimited software-driven adjustability. That flexibility is paying dividend. For example, a defense customer that initially engaged us for a single UAV wire detection application is now evaluating Apollo across 3 separate use cases without any change to the hardware they have already deployed in the field. This is a key differentiation factor that drives customers to select AI. Stratos, the newest addition to our product lineup, extends our capability up to 1.5 kilometers of detection range with 500-meter performance behind the windshield at a disruptive price point.

Through our manufacturing partnership with Lite-On, AEye’s supply chain is globally diversified, providing the flexibility and resilience to navigate geopolitical risk and shifting trade policies that we believe our peers cannot match. Our tech stack is derived from off-the-shelf telecom components, which allows us to compete on cost while delivering the mass manufacturability and high performance our customers require. We continue to build on our partnership with NVIDIA as it is the cornerstone of our automotive and industrial market positioning. Apollo is validated on DRIVE AGX Orin and has been demonstrated on DRIVE AGX, NVIDIA’s next-generation centralized automotive compute platform. In March, we joined the NVIDIA Halos AI Systems Inspection Lab, the world’s first ANAB accredited AI systems inspection lab.

ANAB accreditation is generally viewed by OEMs as a critical marker of confidence, reliability and quality assurance within their supply chain. Our Optus platform powered by NVIDIA Jetson Orin extend our reach into infrastructure and industrial markets via our diversified software ecosystem. We are giving infrastructure and industrial customers a ready-made path into physical AI without having to build perception capability from scratch. I will now turn the call over to Conor to review our first quarter results.

Conor Tierney: Thank you, Matt. Our strong commercial momentum is broad-based, showing up across our full addressable market rather than any single vertical. Our access customer base now spans defense, intelligent transportation, rail and logistics and security, a level of diversification we did not have a year ago. And the quality of that growth matters as much as the breadth. We are also seeing a growing pattern of repeat business across the customer base, a meaningful signal of product market fit and a direct validation of the performance advantages of our architecture. Our commercial progress is beginning to attract broader institutional attention. We added new sell-side analyst coverage this quarter, and we are seeing a meaningful increase in both sell-side and buy-side interactions.

— an external signal that the commercial activity we have been describing is registering with the investment community. The revenue ramp is in its early stages, but the underlying metrics building behind it give us confidence in the trajectory ahead. Before I move to the financials, I want to spend a minute on what we are increasingly hearing from customers. In my role bridging the financial and commercial sides of the business, this has become one of the most important strategic aspects investors are interested in right now. Customers today are not buying a sensor, they are buying a solution. The question they are asking is no longer whose LiDAR has the best specs sheet, it’s who can help me deliver the end-to-end perception capability that my application needs faster and with less integration risk.

That shift is showing up in nearly every RFI and RFQ we see. A customer in the security industry recently put it to us bluntly. They don’t want to buy from a hardware company. They want to buy from the front-end solution provider that integrates everything. That dynamic applies across all of our target markets, and it is exactly the model AI has built. Financially, the implication is meaningful. We do not need to absorb the cost or balance sheet impact of acquiring or building those capabilities ourselves to deliver a complete perception solution, a real efficiency advantage as we scale. The proof is in the deal flow. We are seeing a healthy uptick in customer demand for a full end-to-end physical AI solution, not just a stand-alone sensor.

We have been able to assemble those solutions through our partner ecosystem with a speed and breadth that we believe our peers constrained by what they own internally cannot match. And as our recent customer additions illustrate, this model is working. Meaningful new programs in defense, infrastructure and adjacent mobility have come to us through or alongside our partners. Moving on to financials. The first quarter 2026 revenue was $101,000, up almost 60% compared to $64,000 in Q1 2025 and up slightly versus Q4 2025. First quarter GAAP operating expenses were $8.9 million compared to $8.3 million in Q4 2025, reflecting higher stock-based compensation and professional fees, alongside continued investment in go-to-market and deployment execution.

First quarter non-GAAP operating expenses were $7.4 million, slightly lower than $7.5 million in Q4 2025, primarily due to lower payroll costs, partially offset by increased professional fees. We reported a GAAP net loss of $8.3 million or $0.18 per share in the first quarter compared to a GAAP net loss of $7.3 million or $0.17 per share in Q4 2025. The increase was primarily driven by higher stock-based compensation and professional fees, partially offset by lower personnel costs. On a non-GAAP basis, our net loss was $6.7 million or $0.15 per share, essentially flat compared to a non-GAAP net loss of $6.8 million or $0.15 per share in Q4 2025. First quarter cash burn was $9.2 million, up from $7.5 million in Q4 2025, primarily reflecting Q1 seasonality.

Our manufacturing model built on Tier 1 partnerships rather than owned infrastructure continues to keep our cash burn among the lowest in the sector. We ended the first quarter with cash, cash equivalents and marketable securities of approximately $77.2 million compared to $86.5 million at the end of Q4 2025. The sequential decrease reflects the deliberate deployment of resources into commercial operations, the go-to-market investment and operational execution required to convert the pipeline we are building. This is planned resource deployment, fully consistent with the guidance we set at the start of 2026, and we are tracking in line with that plan. We are reaffirming our 2026 full year cash burn target of $30 million to $35 reflecting planned investments in commercial execution, sales and marketing and the operational build required to support customers as they move from evaluation into deployment.

On a brief housekeeping note, while we are discussing capital. In the days immediately following this call, AEye plans to file a new shelf registration statement with the Securities and Exchange Commission. Our existing shelf is expiring, and this filing is a routine replacement, standard course of business. Our strategy has not changed. Our capital framework has not changed, and the filing does not reflect any near-term financing intentions. The company remains well capitalized with runway well into 2028. Our capital structure also remains simplified and strong with AI virtually debt-free. That matters directly to the OEMs and industrial customers we are targeting, where multiyear program confidence is a prerequisite for selection. And the architectural point Matt made earlier compounds here.

The same software-defined platform that lets us tune Apollo to a customer-specific frame rate, range and field of view is what lets us extend our accessible markets without rebuilding from the ground up each time. Stratos makes that compounding advantage concrete, a third-generation sensor that reaches new performance tiers without a proportional increase in investment and one that drops directly into the same partner-led solutions model. Our peers with fixed sensor capability and internally owned software stacks cannot replicate that flexibility without absorbing significant development and integration costs. For customers who need capability without compromise, that equation continues to resonate. Our expectation for 2026 is unchanged. As technical engagements convert into program commitments, we are building the foundation from which a meaningful revenue inflection can follow.

Getting there doesn’t require out spending the field. Apollo’s performance lead, our software-defined architecture and a partner-led model, combined with a cost structure built for scale, not overhead, make ours a capital-efficient path to a meaningful revenue inflection. I will now hand it back to Matt for closing remarks.

Matthew Fisch: Thank you, Conor. As we look ahead to the remainder of 2026, the focus is unchanged, convert engagements into deployment. The physical AI tailwinds driving this market are real and accelerating. Our technology continues to differentiate us. Our balance sheet provides the stability to execute and the partnerships we have built from NVIDIA to LiteON to Syntech and others lay the foundation for commercial scale. We are seeing the engagement activity and conversion momentum that give us confidence in our trajectory, and we look forward to demonstrating that progress in the quarters ahead. Operator, we are now ready to open the floor for questions.

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Operator: [Operator Instructions] Your first question comes from the line of Poe Fratt.

Poe Fratt: Can you just update us on the collaboration and partnership with NVIDIA? And then maybe give us a couple of milestones that we should be looking for over the rest of the year on furthering that partnership?

Matthew Fisch: Welcome back, Poe. Good to hear your voice. Look, I’d summarize the relationship at this point as strong and progressing. We talked about in Q1 that we had integrated with the latest platform, NVIDIA DRIVE AGX Thor as well as joining the NVIDIA Halos AI lab, which is — demonstrates our commitment in NVIDIA’s support to automotive-grade solution. Even today, we’ve got a team out at NVIDIA’s headquarters down in Silicon Valley. They’re testing — they start at lunchtime. They’re not even there until midnight. — testing the latest Apollo software update. And really, it’s just — it’s about validation, the horsepower and the technology that NVIDIA brings to the table. They’re so prolific what they’re app from the automotive industry.

What this is about is validating our capabilities and performance to be ready for that OEM integration phase. And if you check the NVIDIA ecosystem website today, we’re at the top of the list. Our performance is validated, and we’re the top performer on that list today. So what we can think about, let’s just say, between now and the end of the year, there’s a validation process. that’s the key task for us to be officially validated on NVIDIA AGX Drive Thor, and that’s going to be our focus. And for example, it’s one of the main reasons why we’re out there spending 12 hours today, so we can continue that validation process, get the feedback from NVIDIA, make the product stronger tune and better and be ready for that OEM integration on their platform.

Poe Fratt: Great. That’s helpful. And then when you look at your customer engagement up to 21 revenue generating, I think, shipments. Can you just give us a little more color or detail on the commercial traction within certain key markets? And then maybe, Matt, if you could highlight which markets have the shortest selling time versus other markets?

Matthew Fisch: Sure, absolutely. Thanks, Poe. Great question. Look, it’s — we’re super excited. We’re basically at the highest level of commercial engagement we’ve ever had in this company. And I will tell you, we’ve added in that 31% growth customers in every one of those 6 market segments that Conor talked about earlier. So let’s just jump into it. I mean there’s a lot of segments to cover, but let’s focus on really a couple of key highlights first. One is defense. That’s a real major standout. First of all, our detection range, we believe, is best in the industry. The defense guys and the aerospace guys and the ground vehicle part of that, they love that aspect of AI’s Apollo solution. And the software-defined LiDAR piece allows us to be super flexible across different use cases, let’s just say, in the defense market for today and really point out the evidence we talked about in the earnings call.

And we’re working with many major U.S. defense primes. There’s one in particular that we called out, where not only we’re getting repeat business, but they are scaling now Apollo across multiple of their business units, and we do that essentially with a new software configuration. There’s no hardware change required. And by the way, that expands to the 6 market segments that we mentioned. We can work across each of those without requiring a new hardware build or major hardware changes. And so that’s pretty big. I mean in terms of market velocity, we are pleasantly surprised by how fast defense is moving. There’s a new grade of players in the market also that are moving things along very quickly. I would just highlight that as a high-velocity market versus what we might expect traditionally.

But look, in other areas as well, we’re now — we have our Optus. This is our full perception solution. Conor talked about this earlier. It’s not just about the sensor. It’s about being able to collect data and then act. And we have our Optus solution up on a traffic intersection in the Bay Area today, demonstrating that end-to-end capability. There’ll be more to come in that space for sure. And we also just completed in the intelligent traffic system space, a POC in Australia, where they were trying to count trucks and delays in trucking and parking lots and manage fleet capacity, and they try to do it with camera radar and then they couldn’t make it work, and we’ve got them up and running now. The end customer has seen it, and they’re very happy with it.

So look, it’s about, number one, customers are coming to us for that industry-leading detection range, 1 kilometer for Apollo and 1.5 kilometers for Stratso. And then secondly, that software-defined element of our product now only allows us to scale across market segments, but it also scaling within customers. And I think those 2 attraction and differentiation points are really propelling us forward here.

Conor Tierney: Yes. I think probably you also brought up the question about lead times. And what we would see is there’s probably 2 distinct patterns there. Certainly, on the automotive side, we’re seeing longer lead times. It could take maybe 2 to 3 years to get to SOP. But on non-automotive, that time line has certainly accelerated. That said, we’re still seeing at least 6 to 12 months. Now it can vary between customers, some customers, some sectors move quicker, other move slower. It’s just — it all depends on the end customer and what their goals and priorities are.

Matthew Fisch: Yes. And just probably forgot to mention Syntech as well, another commercial partner we’ve added this quarter, just further highlighting the expansion across multiple players in the defense space.

Poe Fratt: Great. Are you in discussions with any additional partners, Matt? Should we see an expansion like, say, the defense industry is huge. Are there others out there that you’re looking at partnering with?

Matthew Fisch: Yes, absolutely. I count that on 2 fronts. One is just the integrator or the end customer themselves. As we mentioned in the script, we’ve got like a 40% growth in our pipeline. So that’s just a leading indicator to entering the POC phase, absolutely across all of those segments. And then the second piece is let’s talk about Optus. This is where we have 4 partners today. And again, just if you take a step back above LiDAR into the overall perception and intelligence solution, that’s where those 4 partners are coming in, and they’re enabling us to drop into each of those segments very quickly. We have an open platform. It’s based on the NVIDIA Jetson platform. It’s very easy for developers to work with. And even more importantly, as Conor pointed out, in the finance section is we’re not having to — we’re not constrained by what software we develop in-house.

We’ve got these 4 guys that enable us to jump into these multiple market segments very quickly. And throughout the rest of the year, I think you can look forward to expansion of those number of software partnerships as well.

Operator: Your next question comes from the line of Casey Ryan of AMRX.

Casey Ryan: Thanks for the great update. There’s a lot to chew on here. I actually just wanted to jump into the trucking opportunity. I think independently, we’ve actually been hearing some good things about your sensor performance in that space. So with those opportunities in trucking, are they — would they ever be displacing internal LiDAR production? Or is all kind of greenfield new type of truck builds for various manufacturers? How would you describe kind of the nature of the opportunity with some of the truck possibilities?

Matthew Fisch: Casey, thanks, and welcome aboard new assignment here. We appreciate the coverage. Thank you for that. Look, it is true. We talked in the script about Apollo sensors now in evaluation with multiple L4 trucking players. And I think this has been further catalyzed by some of the announcements out there about big investments and capital being injected into that market. I would say that it’s a mix of both of those things. There are concerns out there in the market today about, we’ll call it, supply chain resiliency, where the sensors are built and where the IP comes from. And this has opened up new doors for us. There are transitions happening away from supply chains that may be considered much higher risk. That’s been one source.

And the second piece is, I’ll call it, more complementary where either one of those guys is sourcing — not sourcing, but now evaluating Apollo because of the range, we do really well and seem far ahead. As you mentioned, you need to do that for heavy vehicles because they have a longer braking distance. And in some cases, it’s complementing their existing LiDAR solution. Truck is a big object that has to worry about lots of different situations, not just driving down the highway, but maybe pulling off on the shoulder and then having to pull back on safely. And one of the learnings we see coming out of that space is they need more coverage from LiDAR, and that’s been helping us as well.

Conor Tierney: One thing to add…

Casey Ryan: Please go ahead.

Conor Tierney: I would just say, look, the natural conclusion is this is an L4 opportunity, but there has been some interest on the L2 side. Obviously, that’s a more cost competitive market, but we’ve seen a certain amount of interest there as well. So it’s — you’re talking about L4 and L2 potentially as well.

Casey Ryan: Got it. And then not to beat a dead horse here, but in many truck deployments or sort of architectures, there’s kind of a long-range sensor and a short-range sensor. It sounds like you guys might be able to fulfill both those needs with your product portfolio.

Conor Tierney: Yes. I’d say one thing that we really have going for us is the tunability of the sensor itself, the fact that it’s customizable. And what customers really like is the fact that we can do both long range and short range. Obviously, when you’re on a highway, long range is paramount. It’s critical, right, that you have the braking distance. But sometimes, right, in urban environments, you need a wider field of view, right? You’re maybe looking 100 meters down the road. So the fact that we could have multi-scan patterns embedded on the device and you could toggle back between different modes is really a game changer. And I don’t think there’s anybody out in the market that can offer that level of customization. And so that’s something that appeals a lot to the customers that we speak with.

Casey Ryan: Yes. Okay. Terrific. Yes, that’s a very exciting — something that I think we all eye on…

Conor Tierney: Get the point I’m trying to make here is we don’t necessarily have to do a hardware change. That’s certainly something we could do, but we can solve the problems we solve. Yes.

Casey Ryan: Yes, which that’s sort of the good answer is that basically you guys can sort of address sort of a one-stop shop essentially for a customer.

Conor Tierney: Exactly.

Casey Ryan: Okay. So jumping over to automotive. It’s exciting to hear that people at least are thinking about L3 and L4 offerings at some point. Do you see LiDAR being consumed as part of sort of driver safety packages still? Or are you hearing and meeting customers who are talking about offering some sort of vehicle with L4 autonomy and sort of offering autonomy as a feature versus, say, just super good driver safety tools and safety packages?

Matthew Fisch: It’s a mix of both. And I think you’ll see that, again, I had mentioned earlier about the L4 trucking space that there’s been a lot of capital going in. Now you’re seeing these partnerships with Uber, for example, leverage some of those technology providers to bring capability outside of trucking into, say, robotaxis or other markets. We’re definitely seeing a catalyst there. And then I think there have been a number of OEMs out there that talked about what they call hands-off eyes-off driving. Maybe we consider that more in the L3 range. And again, I have to really call out that the concern about supply chain resiliency has really brought a number of customers to our front door because of concerns and risk in that area, certainly in the Level 3 space and also a little bit of L2 and ADAS, as Conor mentioned, to solve some corner conditions that currently aren’t efficiently covered by like ultrasonics and panoramic cameras.

So it’s a mix of all 3. The sweet spot is definitely on the L3 side, eyes off, hands off, but you’ve got all 3 in the mix.

Casey Ryan: Yes. Okay. That’s very exciting. I’m happy to hear about that. And yes, I mean, certainly, you’re right, kind of the news flow around robotaxi and L4 from a whole bunch of providers has certainly ramped up quite a bit. In defense and specifically in drones, I think there’s an issue around — it’s not an issue, a topic around the weight of a LiDAR sensor. And I wonder if you could just talk about the weight of your solutions and if there’s like a road map to make a certain model lighter or sort of where you guys sit on that weight front in terms of consideration for essentially all defense applications, but primarily drones, obviously.

Matthew Fisch: Yes. We’re really light and we fit into that envelope quite well. I’m not sure if we published the specs on that. but we’re definitely at the low end of the spectrum on weight. Also keep in mind that the kind of drones that you and I may sort of be directly exposed to may not be the kind of drones necessarily where you need long-range LiDAR. For example, drones that travel at very high speed, I’m talking about over 200 miles per hour. Because they’re at that kind of speed, they need to see a kilometer out or out, not the drones that Amazon uses to drop off packages. They’re much more sophisticated surveillance and other type of drones. So it’s — we’re absolutely fine in those, and we’re light enough to be considered for stronger drones as well.

The other hot topic that’s cropping up is drone detection. — and be able to assist intervention system to track when you have an inbound drone, which are pretty small. Those kind of drones tend to be very small coming in and you want to get them while they’re very far out. And that’s again where the defense primes are coming to us because of the long range that we have.

Casey Ryan: Okay. Good. Well, that’s very exciting, actually. And then just one last little smaller sort of, I guess, it’s not technical question, but you guys have talked about a $30 million contract opportunity over some longer period of time. I just wonder if that customer pulled some units or was part of the commercial count in 1Q and/or if you expect them to be part of Q2.

Conor Tierney: Yes, they’re certainly in that count number. So the 2 customers — what I would say is that customer itself is probably not going to be a meaningful contributor to revenue this year. I think the revenue is probably a little bit further out in time. And that said, what I would say is since we made that announcement, it was almost over a year ago now, there’s been more customers that have come into the mix and more customers that have moved pretty quickly through that POC phase. So what we’re seeing now is probably more near-term opportunities with other customers. And that’s probably what’s going to really drive revenue potential for this year.

Operator: Your next question comes from Richard Shannon of Craig-Hallum.

Richard Shannon: Jumped on a little late, so I may have missed some of the prepared remarks here. So I hope I don’t repeat some past questions here, but I did want to touch on one of the key themes here in the press release here today about engagement on the automotive side here, particularly with OEMs that are reengaging on L4 and L3 road maps here. Would love to get some dynamics and understanding of those dynamics going on here. And maybe you can elaborate on how many RFIs and how fast do you think they’ll move to RFQ in later stages.

Matthew Fisch: Yes. Let me start with this, and I think Conor probably pile on here. What I mentioned earlier, Richard, this did come up in the Q&A, which is what is driving some of this increase in attention I think it’s 2 pieces. Mainly one is that you see a lot of funding coming into tech providers that they have to deal with Uber, for example. There’s quite a few of them that are driving increased interest and velocity in Level 4 robotaxis. So that’s one part of it. The other is we see definitely a growing concern over supply chain resilience and taking risks in those areas, and that’s shifted business, shall we say, as those passenger vehicle OEMs start waking up and their L3 programs are coming online. Those are the key drivers.

I think we said earlier in the script, the number of RFIs coming in has definitely increased. And we’ve got out of the business of predicting OEM schedules because there — some of these have come and gone. And we’re just going to keep an eye on it quite honestly. We’re not — we’ve got enough in our manufacturing pipeline and readiness to hit the switch and get going with the device production when that time comes. We’ll expect a little bit of heads up on this, but our lead times and our risk guides are lined up with any earliest possible time line that we can imagine. But we just — we don’t know. It’s been very unpredictable, quite honestly.

Conor Tierney: Yes. The only thing I’d add to Matt is just the fact that we can go in cabin behind the glass, right? That seems to be a big value prop for the OEMs, obviously, the aesthetics of being able to do that have the windshield basically as a way to protect the sensor itself and obviously clean it. So those are — that’s a really interesting value prop for the OEMs and something that certainly differentiates us.

Matthew Fisch: Yes. Two other things, Richard. One is what the activity is happening today is data collection. A big part of integration of LiDAR is training the AI and integrating to the software. And that’s what’s been unpredictable in terms of conclusion of those activities. And then secondly, we just came through a major supply chain audit in the last 6 months and really digging in, in some cases, down to glass and sand where raw materials and intermediate components are coming from just to make sure that they have options on the supply chain side. We’ve been very busy with those 2 activities of late.

Richard Shannon: Okay. Great detail there, guys. Second one is just on the general customer engagement here. Glad to see the customer count moving up nicely here from, I think, 16 to 21 here. I ask roughly the same question in a couple of different ways here, one of which is specifically on the customer count, if you can elaborate and describe which end markets, the incremental 5 have come from here? And then where would you describe where the biggest dynamics around engagement have been going that are filling the early part of the pipeline here as well.

Matthew Fisch: Yes. I mean I think if I would — you could probably do the math, but the — if you take those new 5, they’re pretty much spread evenly across all the market segments we mentioned during the prepared remarks. I’m going to take a look at Conor here for the second part of the question.

Conor Tierney: Yes. I mean, look, I think defense, obviously, as Matt mentioned, is a big driver, and we’re seeing a lot of interest. And it’s not just in the defense sector. I would say it’s also in the commercial aviation space as well. So we have some customers in that particular vertical as well. And I think the unifying factor is high performance, range, resolution and then obviously, the ability to tune the scan pattern. And I think what’s interesting is even in the defense sector, customers have different needs, different use cases. And so this is really where the tunability of the sensor, the ability to customize the scan pattern becomes really important. And even in some cases, for even just one use case, there might be different variants or different kind of performance factors that the customer is trying to solve for.

It could be long range, even shorter range, increasing the frame rate. So the ability to just dial up, dial down the sensor is really important. And I think that when we’re chatting with customers and we’re chatting with investors, one thing that we really try and guide people on is when you look at our sensor, think about it as a performance bucket, and you can kind of basically adapt that performance bucket to what you want to achieve, right? So if that means going longer range, you can put the performance there. If it means higher frame rate, you can do that. And so we’re giving that level of customization that you otherwise can’t get in the marketplace.

Richard Shannon: Okay. Probably my last question here is on Optus. So your press release mentioned that’s live in an active California intersection. I think I saw something on maybe your LinkedIn page not too long ago, which is great to see, which is a good excuse for me to ask about general maturity and kind of breadth of engagement pipeline with Optus here, where you’re seeing this in terms of application set and geographies would be a great update.

Matthew Fisch: Yes. Again, I think it covers a fair part of our market segments and in the remarks, we talked about we’re seeing a growing number of customers. The trend is definitely, we’re looking for partnering perception and sensing and data analytics that’s becoming a bigger part of our pipeline. The examples that we pointed out, for example, the traffic intersection — we also mentioned the completion of a POC within — out in Australia with kind of — we call it smart intelligent traffic systems where we were tracking for a fleet management company trucks going in and out of weigh stations and payloads and things like this. And again, we’re seeing as we’re talking with those customers, they don’t know a lot about LiDAR.

They just came to us and said, well, we tried working with an integrator that does cameras and radar and it doesn’t work. Can you help us make it work? And we’re seeing more and more of those type of customers where their level of sophistication and knowledge of the underlying sensor piece isn’t quite there. They just want help to get an end-to-end solution. It’s a growing part of that number that’s increasing. maturity, we’re — we’ve been out in the wild for almost a year now on that second example and a few months on the first one. We’re going to see more intersections going online this year. So I think things are maturing nicely, and you can definitely expect to see a higher percentage of those end-to-end solutions coming in the back half of the year here.

Conor Tierney: And just one thing to add. I think there’s really what makes us unique in the ITS space, especially when it comes to intersections, one thing we’re learning is there’s a dilemma zone, and that’s maybe looking back 100 meters from the stop bar. And the fact that we have the range and capabilities to do that is a differentiating feature in the solution that we’re offering. And that’s something that definitely getting positive feedback from the DOTs. It’s something that nobody else can do right now. So that’s a classic case where we’ve built a solution, and we’re leaning into our capabilities and performance factors.

Matthew Fisch: And hearing increasingly the narrative is the other sensors just couldn’t see far enough.

Conor Tierney: Really that simple. So I think customers are going beyond — they’re looking more towards next-gen LiDAR solutions, high-performance solutions that can give them that level of range and customization that they need.

Richard Shannon: Makes a lot of sense. Last quick question, Conor, since I didn’t hear your prepared remarks, I just wanted to make sure that or ask whether you’re still using the same language used on the last earnings call about seeing an acceleration in the second half of the year. Is that still your thought process there?

Conor Tierney: Yes, for sure. Look, I think we’re definitely going to see an inflection in the revenue. I think we’re already seeing more units in the pipeline here for Q2, and we think that trend is going to continue on into Q3 and Q4. So I think all in all, yes, we’re still guiding to that narrative.

Operator: [Operator Instructions]

Matthew Fisch: I think it’s okay. We can wrap it up if there’s nothing else.

Operator: That will conclude our question-and-answer session. I will now turn the call back over to Matt Fisch for closing remarks.

Matthew Fisch: Thank you all for your time today and for your continued interest in AI. We remain focused on executing against our commercial pipeline and converting this momentum into a durable revenue ramp, and we look forward to updating you on our progress next quarter. Thank you.

Operator: Ladies and gentlemen, that concludes today’s call. Thank you all for joining. You may now disconnect.

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