Thank you for standing by and welcome to the Umbrella's second quarter fiscal year 2027 earnings call. At this time, all participants are in listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you'll need to press star 11 on your telephone. If your question has been answered and you'd like to remove yourself from the queue, simply press star 11 again. As a reminder, today's program is being recorded. And now I'd like to introduce your host for today's program, Louis Gerhardy, Vice President, Corporate Development. Please go ahead, sir.

Thank you, Jonathan, and good afternoon. Thank you for joining our second quarter fiscal year 2027 Financial Results Conference call. The call with me today is Dr. Feng-Ming Wang, President and CEO, and John Young, CFO. The primary purpose of today's call is to provide you with information regarding the results for our second quarter of fiscal year 2027. The discussion today and the responses to your questions will contain forward-looking statements regarding our projected financial results, financial prospects, market growth and demand for our solutions, among other things. These statements are based on currently available information and subject to risks, uncertainties, and assumptions. Should any of these risks or uncertainties materialize, or should our assumptions prove to be incorrect, our actual results could differ materially from these forward-looking statements. We are under no obligation to update these statements, these risks, uncertainties, and assumptions, as well as other information on potential risk factors that could affect our financial results. are more fully described in the documents who filed with the SEC. Access to our second quarter fiscal year 2027 results press release, transcripts, historical results, SEC filings, and the replay of today's call can be found on the investor relations page of our website. The content of today's call, as well as the materials posted on our website, are Amborella's property and cannot be reproduced or transcribed without our prior written consent. Before starting the call, we hope to see you at one of the following investor events that we have scheduled in our third quarter. First, on September 8th, we'll host a D&B bus tour at our offices in Santa Clara. September 9th, we'll be at Citi's 2026 Global TMT Conference in New York. September 15th, we'll participate in Piper Sandler's Growth Frontier Conference in Nashville. September 16th, We will host Sanford Bernstein's 8th Annual West Coast Semiconductor Bus Tour. And during the week of October 4th, we will have a European NDR with cities to be determined. Also available to investors during the third fiscal quarter will be our booth and presentations at the AI Infrastructure Summit in Santa Clara on September 15th to 17th. We hope to see you there. where we will lead the physical AI track with a number of edge AI and robotics demos in our exhibit area. Fermi's now going to provide a business update for the quarter. John will review the financial results and outlook, and then the three of us are available for your questions. Fermi?

Thank you, Louis, and good afternoon. Thank you for joining our call today. Driven by a new record level of AGI revenue, we reported fiscal Q2 revenue slightly above the midpoint of our guidance with non-GAAP EPS of $0.18 and with guidance for seasonal fiscal Q3. By product, we are in the midst of a very steep revenue ramp with our financial leader CB75 and CB72 AISOCs and by market, we have sequential growth in both IoT and OTO with automotive revenue driven by commercial vehicles. The market is increasingly recognizing the strategy value of AGI, as well as our AGI and the fiscal AI platform leadership. We continue to make significant progress with the expansion of our AGI platform leadership, including new go-to-market strategies and the engineering and market development for a number of new higher value SOCs, some of which extend our reach into entirely new markets. We remain optimistic about the long-term secular growth opportunities in the age AI market, and our R&D priorities are aligned with both the physical AI markets that represent a vast majority of our total revenue today, as well as the robotic and the age infrastructure markets that are in the early stages of developing. Altogether, our technology, product, and new go-to markets combined with the significant secular growth in AGI are increasing our five-year serviceable market forecast today. Before I review our new market forecast, I would like to step back and discuss the market environment we are in. Demand signals for the application of AGI remain strong. At the same time, it is obvious that memory vendors and the entire supply chains are prioritizing AI data center demand, which is resulting in raising supply chain costs for everyone. Surging memory price and the scarcity of a supply are impacting the entire industry. Related to this, we are providing significant assistance to customers who are attempting to create a wide variety of workarounds to the memory situation. And Verilock itself is also facing rising supply chain costs, and we plan to pass this cost to our customers to maintain our long-term gross margin target of 59% to 62%. Returning to our rolling five-year serviceable market update, I would like to remind you of our methodology. Our SEM for any given year is based on the products we expect to have available for production in that year, overlaid on the total available market projections from a number of third-party research firms. So our five-year SEM captures any revenue-generating products announced or unannounced on our roadmap in the next five years. Our prior five-year rolling sum was announced in May 2025 and projected a five-year fiscal year 26 to fiscal year 31 compounded annual growth rate of about 18%, with auto representing a slightly higher proportion over the terminal year. Our new five-year rolling sum from $8.5 billion in fiscal year 2027 to $22.9 billion in fiscal year 32 represents a CAGR of about 20% with IoT markets now representing about 70% of the terminal year. While there are several factors behind the strong growth and the underlying mixed change, I will focus on the most important change. In the last year, it has become clear that operational efficiency or the ability of an enterprise to generate more revenue and or to reduce expenses is likely to be a key driver of our emerging edge infrastructure business. Operational efficiency at the edge refer to the use of open weight and the distilled models running on on-premise inferencing hardware in contrast to the large frontier models that run in the cloud. Benefits of this approach include reduced latency Data protection, privacy, lower bandwidth costs, and high reliability. Target markets include security, retail, lodging, logistics, healthcare, and more. The on-premise operational efficiency use case has emerged with growing expectations for sustainable high-volume inferencing and increasingly for agentic AI and physical AI application that can perceive The key question has become, who can help the enterprise lower the cost per useful AI inferencing outcome? This is where Umbrella's superior performance per watt portfolio kicks in, providing the efficient edge intelligence needed to enable this next-generation authentic and physical AI workload at scale. With this perspective, in the last year, we have several new products in development targeting on-premise hardware or what is commonly called edge infrastructure. As you know, we already have our NY655 AI SoC in the market, and we have additional unannounced AI SoCs in development. We also are implementing a standalone AI accelerator product line targeting the edge infrastructure market. Together, this new H infrastructure product, both AI SOCs and the standalone AI accelerators, represent the single most important reason for the upward revisions in our scene. Before I introduce our first standalone AI accelerator, allow me to be clear about our terminology. We define HAI SOC as one integrating all of the accelerated computing functions into a single chip. Camera perception, AI accelerators, CPUs, encoding, and so on. We define an AI accelerator as an AI processor that is not camera-specific and targets a wide variety of digital or physical modalities. We believe this type of multi-modality is critical for each infrastructure applications by target operational efficiency. While not formally announced, I would like to preview one of the new AI accelerators that will anchor this new product category for us with another well-defined, well-performed product already behind it. We refer to this new AI accelerator as X7. This XOC is sampling now and expected to land initial design with the H infrastructure application where it can serve as an AI coprocessor for host processors such as ARM or x86. Together with our new product thrust, expanded market reach, and SAM, we expect our revenue growth to be supported with two incremental go-to-market strategies. First is the multi-step establishment of indirect sales channel, and the second is a semi-cousin chip strategy, both of which will augment our existing direct sales efforts. As a reminder, virtually all our revenue is generated by our direct sales teams, and today I am excited to announce two material partnership agreements to develop our indirect sales channel. Combined, these two partnerships plan to drive a significant amount of incremental revenue over the next seven years through customers who have largely been unserved by us so far. First, today we announce Embraer Strategy Partner with Capgemini. designed to help enterprises adopt AGI and the physical AI solution faster by reducing the complexity of moving from evaluation to scalable deployment. By combining Embraer's power-efficient AI software and the platforms we can optimize global engineering, system integration, and industry expertise. The partnership aims to help customers improve operational efficiency, enhance real-time decision-making, and deploy intelligent In our second partnership to develop our indirect channel, today we also announced a seven-year agreement with Magnica, a leading global technical distributor. Magnica will support both American's physical AI and the new age infrastructure products by developing and supporting an independent software vendor ecosystem. including onboarding, technical integration support, and joint go-to-market programs. With this ecosystem in place, Embraer's solution can be offered as individual components or as a complete bundle for multiple edge AI vertical markets, including video analytics, smart city, edge computing platforms, robotics, industrial IoT, intelligent transportation system, retail analytics, security, and surveillance. I want to emphasize the importance of the indirect channel to serve small and mid-sized customers and highly fragmented market like robotics. However, the indirect channel is also critical to support our more complex AISOC targeting the edge infrastructure where a broad network of partners is vital for our long-term success. Meaningful revenue is expected in two to three years and will grow as we introduce new products for the market. Our second incremental go-to-market is our semi-custom opportunity, which can enable us to gain more shares in existing markets and switch into new markets. We have our first semi-custom project underway, the 2nm CVA SOC, which is expected to generate first-part production revenue in fiscal 2028. And we are in discussion with other companies for additional semi-custom chip projects. Our representative customer engagement this quarter once again demonstrates Embraer's extending traction across a broad set of applications, robotics, automotive, security, trail cameras, and smart video intercoms. With a CD72-based quadruped robot validates Embraer's high-resolution, high multi-camera HDI capabilities in robotics. A major S&P 100 communication equipment company, announced an AI-based enterprise video intercom further extending our reach in the emerging access control market. We landed another win with Moultrie for AI trail cameras and a win with Canon, Suprema, IDIS, and C Pro for the strength, strengthen our AI monitoring pipeline with CV75, CV72, CV5 wins using our own AI ISP software. Through Tier 1s, we had two in-cabin vehicle wins, with Tier 1s in China, one for driver monitors and the other for more complex camera monitor systems used in Audi and VW vehicles. The breadth of these wins and the wide variety of corresponding AI workloads highlight the programmability and flexibility in both our AI SOCs and our Cooper development platform. This ease of use is facilitating the onboarding and expansion of our indirect sales channels. Very few competitors can offer this type of proven platform with more than 15 million HAI SOCs shipped. In conclusion, I've been very excited about the overall growth opportunity of the HAI market and our company's specific growth drivers put us in a unique position to benefit. And Broggi is expanding beyond low-power AISOC to deliver the complete foundation for physical AI, and we are becoming a full-stack physical AI platform provider. With that, I will now turn it to John.

Thank you, Fermi. I'll now review the financial highlights for the second quarter, fiscal year 2027, ending July 31, 2026. I will also provide a financial outlook for our third quarter of fiscal year 2027, ending October 31st, 2026. I'll be discussing non-GAAP results and ask that you refer to today's press release for a detailed reconciliation of GAAP to non-GAAP results. For non-GAAP reporting, we have eliminated stock-based compensation and acquisition-related expenses adjusted for the impact of taxes. In addition, this quarter, as described in our Q1 fiscal 2027 10Q filing as a subsequent event, We recognize the $9 million reduction in our GAAP research and development expense due to the cancellation of a customer's development project. We do not expect any impact on our non-GAAP outlook from this development. For fiscal Q2, revenue was $108.1 million, slightly above the midpoint of our prior guidance range of $105 to $111 million. of 7.7% from the prior quarter and up 13.2% year over year. Automotive revenue established a new revenue record on continued strength as the commercial vehicle adoption of AI remains strong, and auto revenue slightly outpaced the growth in our IoT business, where our enterprise-driven businesses outperformed our consumer-led businesses. Non-GAAP gross margin for fiscal Q2 was 59.3%, below the midpoint of our prior guidance range of 59 to 60.5%. Non-GAAP operating expense in Q2 was $57.4 million, slightly below the midpoint of our prior guidance range of $56 to $59 million. Q2 net interest and other income was $1.8 million. Q2 non-GAAP tax provision was approximately $344,000. We reported Q2 non-GAAP net profit of $8.2 million, or 18 cents per diluted share. Now I'll turn to our balance sheet and cash flow. Fiscal Q2 cash and marketable securities were $272.3 million, decreasing $5.5 million from the prior quarter, but increasing $11.1 million from the same quarter a year ago. The sequential decrease in cash and marketable securities was primarily due to higher payments for IP licenses. Receivables day sales outstanding decreased from 35 to 32 days. While inventory dollars declined 4% sequentially, the days of inventory increased from 145 days to 157 days. Operating cash outflow was 260,000 for the quarter. Capital expenditures for tangible and intangible assets were $6.8 million for the quarter. Free cash outflow was $7.1 million for the quarter. During the second quarter of fiscal year 2027, we did not repurchase shares of our stock. During the second fiscal quarter, Ambarella's board of directors authorized the new $50 million repurchase program valid through June 30th, 2027. The repurchase program does not obligate the company to acquire any particular amount of ordinary shares, and it may be suspended at any time at the company's discretion. WC Microelectronics, a logistics partner in Taiwan that ships to multiple customers in Asia, with 60.2% of revenue for the second quarter. Akuto, a logistics and distribution partner in Japan, with 11% of revenue in the quarter. I'll now discuss the outlook for the third quarter of fiscal year 2027. We are anticipating favorable seasonality in our fiscal third quarter with revenue in the range of $115 to $124 million, or $119.5 million at the midpoint. At the midpoint, we expect our growth to be led by fiscal AI demand from the IoT market. We expect fiscal Q3 non-GAAP gross margins to be in the range of 59 to 60%. We expect non-GAAP objects in the third quarter to be in the range of $56.5 to $59.5 million. We estimate net interest and other income to be approximately $1.9 million. Our non-GAAP tax expense to be approximately $700,000. And our diluted share count is expected to be approximately 44.9 million shares. Thank you for joining our call today. And with that, I'll turn the call over to the operator for questions.

Certainly, and ladies and gentlemen, we ask that you please limit yourselves to one question and one follow-up. And our first question for today comes from the line of Christopher Rowland from Sesh Wahana. Your question, please.

Hi, this is Dylan Olivier. I'm for Christopher Rowland. Thanks for taking my question. So it's nice to see your roadmap sort of expanding, and I know that you announced this X7 accelerator. I was hoping to hear a little bit more about this new chip. Is this a chip that you can bundle with your existing N1 portfolio, or does this address a different part of the stack? Thank you.

So, yes, Chris, for the X7, this chip is an accelerator which can be bundled with any host, including our own chip. So, in fact, that's our customer using a certain part number, and if you already need to have more AI performance for certain workloads, The X7 gives them a flexibility to upgrade the product without redesigning the board. So this accelerator definitely is a way to design that. But in addition to supporting our own SOCs, but any other CPU like ARM or Intel chip, Intel CPUs, we can also bundle X7 with that as an AI accelerator.

Great, thanks. Appreciate this. And for my second question, I wanted to ask about sort of the physical AI and humanoid opportunity. Is this responsible at all for this increase in SAM? Are there any new engagements or new designs that you can point us to? Thank you.

Yeah, so definitely that's a big part of that. And in the last earning call, we talked about 15 design wins for the robots, including for roughly $100 million. Although we didn't give you another breakdown, but I can say that we add more design win to that pipeline and the higher revenue target. So from that point of view, we continue to make progress. But in addition to robots, I also think that each infrastructure, and also Enterprise Security as well as portable video are all the reasons that we are increasing our SAN number.

Yeah, Bill, and we did, Fermi mentioned a quadruped robotic dog, the CB72 chip this quarter. So, you know, continue to add on to the robotics wins we've described before.

Thank you. And our next question comes from the line of Joe Moore from Morgan Stanley. Your question, please.

Yeah, thank you. I wonder, first, in terms of the broader ecosystem, you talked about some of the challenges of memory. You know, what does that mean for your business? Do you think is there a risk of pull-forwards or things like that because people are trying to get ahead of memory pricing pieces? Is there pressure on you? Just, you know, what are you seeing from that memory impact from your customers?

Right, so we continue to monitor this situation very closely by talking to customers all the time. So for Q3, we are comfortable with our related, the guidance we provide today. In Q4, we continue to talk to customers to make sure our customer will have, we can secure enough memory for a Q4 business. That's definitely the uncertainty that we are dealing with.

Okay, that's helpful. Thank you. And then in terms of Opening up to a broader ecosystem, distribution partners, things like that. I think you made the comment about, you know, that would take a couple of years to inflect. I guess I would sort of think that those customers would act a lot more quickly and that pipeline could build a lot more quickly than what you had seen previously in automotive. Just, you know, what was the comment that I maybe misunderstand there? And then, you know, what is the timeline to... to start to see traction from that kind of broader ecosystem.

Right. So when I say two to three years, we talk about meaningful revenues. And I agree with you that we, in fact, we already start seeing a small amount of design wind which can generate revenue next year. But when we talk about meaningful revenue that will have an impact to our revenue forecast, I think that will take two to three years. In fact, when we talk to both Capgemini and Mechanica, In fact, the range of revenue we are expecting from this collaboration is half a billion dollars with each one of them. So from that point of view, we're definitely looking forward to gradually ramp up the revenue for the next couple years and start seeing meaningful revenue behind that.

Great. Thank you.

Thank you. Thank you. And our next question comes from the line. Your question, please.

Yes, thank you, and congratulations, Cindy, and Capgemini Partnerships. I'm curious on those for me, you know, what are some of the early use cases that those two partners are going to be helping you with, you know, maybe you can call it some some markets or applications. And how should I think about that in the context of your Cooper platform? Are they going to be working with you on Cooper? Are they going to be providing some of their own software? Just curious how that's going to play out. Thank you.

Right. So let me answer the second question first. Yes, both of them will use Cooper. In fact, as a key driver for them to select to work with us because they see a very mature software platform they can immediately tackle on and start building around and generating infrastructure for their own product line. So that our mature AI SOC as well as a mature Cooper software platform is the probably most critical engineering aspect that we offer to our clients. Go back to the potential market that we are talking about. In fact, there are multiple of them. And in fact, when I talk to Mechanica, CEO. In that meeting, they are highlighting that they have already started winning design wins with our solution on drones, on retail channels, and also manufacturing. So that is definitely, you can see that it's really a large market. However, most of the design win is small and segmented at the beginning, but if they can ramp up to a large volume of business, that will take time. But we already start seeing our partners start talking about different applications.

Victoria's Lewis, you know, they can work together as well. As Fermi said, you know, Macnica can serve small to mid-sized markets that, you know, oftentimes are very fragmented. But really for Capgemini, it's large enterprise customers, and you can look at who they've talked about before. You know, those are the type of customers we'd really go after with them. So they're very complementary to each other.

Very good. And as my follow-up on the edge infrastructure market, this is obviously a completely new area. It sounds like that's the sort of biggest contributor to your increase, Sam. I'm just curious, you know, who's going to be some of your partners there? I mean, are these going to be your end customers sort of building their own infrastructure, or is there going to be like an intermediary company that's building it? Is it going to be the traditional server guys? Yeah, just curious how that's all going to play out. Thank you.

Well, I think obviously we're going to continue to talk to some of the large customers directly, but at the same time, we're counting on Capgemini and Magnica to help us to penetrate, because they're already in that market. They're already selling solutions to the existing AGI customers with their existing solutions. So working with them will help us to ramp up our revenue much faster than just we talking to direct customers directly.

Makes sense. Thank you.

Thank you. And our next question comes from the line of Quinn Bolton from Needham & Company. Your question, please.

Hey, guys. Thanks for taking my question. I just wanted to ask just longer term on the McNeek and Cat Gemini partnerships. Does that change the long-term gross margin target? I assume that there's probably some allocation of that would be attributed to those partners. And so I'm wondering if that has any gross margin implications as that indirect channel ramps.

Right. So today, I think our long-term gross margin is still 59% to 62%. We're definitely trying to continue to watch because we just started ramping up this business. If there's any change, we'll definitely inform our investors. But today, for us, after we talked to Capgemini and Agnika, we don't feel there's any need to change that target today.

I guess just a clarification on the $9 million charge for the project that was canceled. Was that a semi-custom project that was canceled, and does that have any impact on your expected revenue timeline for the semi-custom business?

Yeah, thanks, Quinn. It is not one of the semi-custom opportunities that we talked about. It was a A development project with, I guess you could say, an automotive customer, auto autonomy customer. And we've been negotiating the termination of that for quite some time. And in Q2, we finalized the agreement.

Understood.

Thank you. Thank you.

Thank you. And our next question comes from the line of Kevin Cassidy from Rosenblatt Securities. Your question, please.

Yeah, thanks for taking my question. Going back to the shortage on the memory side, and you've got near-term visibility, but I'm wondering on the designs, you know, I know a lot of your customers or the market out there is probably dominated by a GPU-based embedded product that uses much more DRAM than yours would. Are you seeing any additional interest because you're more efficient with DRAM content?

Yes, first of all, the memory situation is dire for everybody, but some of our competitors who have more money to buy multiple memories. However, any customer who comes to us for the AGI or physical AI, they probably only use GPUs for their first-generation products, and they understand. So the memory cost is just one reason, but more importantly is power efficiency. But the memory cost definitely is important. a driver for people to start considering what's the more efficient way to do the product. So I agree with you that almost all the customers who come to talk to us is because our power efficiency solution and the low-cost solution than the product they're using.

Okay, thanks. And maybe along the same lines as with the AI accelerator, you'd be competing against a GPU that uses A lot of memory also. What is the memory architecture inside your X7?

Well, in fact, we need a much smaller footprint. For example, we only need 4 megabytes memory for the accelerator running, you know, large language models. So just to show you, and more importantly, the accelerator, the power envelope, you have to fit in. is anywhere between 4 to 5 watts in the current design. So all of the power efficiency, memory size, and also cost is really helping us to penetrate this market right now.

Okay, great. Thank you.

Thank you. And our next question comes from the line of Suji De Silva from Roth Capital. Your question, please.

Hi, Fermi, John Lewis. Just a clarification, Fermi, on the X7 chip. Is that competing really only with edge GPUs, or is it other AI specialty chips, or how should we think about the competitive landscape for this new offering?

Right now, well, in addition to NVIDIA and Qualcomm having similar products in this market space, there are probably 50 startup companies doing similar chips. So it's a crowd space, but however, at the end, it's really about The power efficiency. Because I just talked about, you know, to run a certain workload, you have to have a mature, not only a power efficient solution, but a mature hardware and software, which I think we are one of the very few that can do that today. Okay.

That's helpful for me. And then my other question is, you're talking about customization now, projects. I'm just wondering what's precipitated the demand from the customers or your push to provide customization? What's newer versus your standard product history now that's...

I think you're talking about the optimization for the memory situation. Is that correct? Semi-custom, I apologize. Yeah, for semi-customers, in fact, we basically allow our customer to give us a spec, and we build on the spec. However, when we negotiate a spec with a customer, we need to make sure that we can sell the spec to somebody else. So for the semi-custom chip, we pretty much build a purpose chip for the one customer, which they benefit from this. But at the same time, we can sell the chip to others that are not competing with the key customer. That's the business model and how it works on the engineering side.

Okay. We'll try to offer as much of our own IP in those semi-custom chips as possible. For example, We have our own IP for the AI accelerator, the NPU for all the perception capabilities, including the ISP and encoder, the CPUs. All of those functional blocks are available for a customer to develop a semi-custom or custom chip with. Okay, great. Thanks, guys.

Thank you, and our next question comes from the line of Liam Parr from VOA. Your question, please.

Hi, yes, thank you for taking my question. Is there a way to frame how much memory concentration you're absorbing this quarter, either in basis points or maybe what gross margin would have been without any memory concentration? And is a pass-back above 60% feasible while memory prices stay elevated, or does that require pricing to come down? Thank you.

Right, so first of all, the memory price doesn't impact our gross margin. It really only have a potential to impact how many chips our customers can buy. So memory costs, because we don't buy memory, and we don't resell memory, so the memory price has no impact to our gross margin. So I think that answers your question. But the real question for us is how that memory cost can because our customers need to increase the price, whether that will reduce the total volume they can sell and therefore reduce the total ordering to us. That's something we need to continue to observe. In Q2 and Q3, we see little impact on our revenue because of memory situation. We continue to watch for the Q4.

Thank you. And then I guess for my follow-up, Q3 has died up 10.5% roughly sequential versus 13.5% last year. How much of, you know, this next quarter is normal seasonality versus, you know, underlying end-demand strength? And given you flagged Q4 memory supply, you know, obviously, you know, changing the demand picture, how should we think about Q4 seasonality and whether the full year 10% to 15% is still, you know, reasonable for the guide? Thank you.

Right. So, I think the outcome this year is still a little uncertain because of the memory constraint that you talk about. and like I said, we continue to talk to our customer for that to monitor how that impacts our performance in Q4. Barring for any memory impact to our revenue, I think that you should expect a Q4 of the regular seasonality.

Thank you. And our next question comes from the line of Gus Richard from Northland. Your question, please.

Yes, thanks for taking the question. Robotics architecture is looking an awful lot like an autonomous car in terms of what it needs to do. And I'm just wondering, you know, you have a domain controller for autos and you have the CV products. Are you seeing any traction in the domain controllers and, you know, and then any clarification on, you know, where you're seeing the strength? Is some of this coming out of China?

Right. You know, first of all, you're 100% right that a lot of robot design in my system architecture looks just like a automotor driving car, which I totally agree. And however, I think the robotic market situation really reminds me of automotor driving seven years ago, when at that time, all of the automotive customers were trying to just using individual modules and put the solution together and start demoing and selling the first generation product. I think this is how we act with the current robots. We see a lot of customers are rushing out their first generation product by putting individual components together to demo their capabilities. However, we do believe that integration paths of the robotic will be very similar to what happened to the atomic driving car. It is, there will be People go to buy perception systems, but down the road, people want to buy domain controllers. We do see both opportunities today, but I will say the majority of our customers today are asking for perception modules, perception solutions, but on their roadmap, they want to have a way that can buy domain controller in the long run. So I think we have a complete roadmap. We can sell just perceptions to send to a customer today. If people want to buy a domain controller for the brain of the robots, we have the solution too. But our plan is we're going to continue to develop solutions for both so that we can cover the total space of robotics.

Got it. And then just If I think about, again, robots, you know, cars are 2D and robots are 3D, and I'm just wondering, you know, is one of the limitations of penetration training, and can you help your customers, you know, train robots? You know, I'm thinking about, you know, humanoid, but go ahead.

Sorry. Right. So in terms of training, it's really about how to collect data. One thing we help our customer is we build a platform for people to collect data easily. And also we provide a platform that can provide them a service to help people to label those data. if automatically, so people can use our system of reference design to collect data. In fact, some of the, I would say the people doing mapping, generating the CT mapping are using our system to collect data. And also, we are providing service to some of our automotive customer that we can, using our tools to auto-labeling all of the data they generate. Those are two things we can help to provide assistance on the training side. Got it. Thanks so much. Thank you.

Thank you. And our final question for today comes from the line of Martin Yang from Opco. Your question, please.

Hi. Thank you for taking the question.

Fermi, you sized the potential revenue from Capgemini and McNema pretty similarly, but they face different and a variety of customers. Can you maybe talk about the methodology you arrive at those dollar figures? Is it a similar methodology or a very different approach to size those potential markets?

Yeah, go ahead. Hi, this is Muneyb, just jumping in there. I think both Fermi and Lewis were, you know, commenting earlier about how complimentary they were, right? One, on the Magnica side, I think Louis has commented, you know, it's large-scale, you know, medium-large kind of customers we haven't addressed in the past. So, think of them as a large volume play where, you know, we typically directly engage with high-volume customers. These will start aggregating a whole bunch of small, mid-sized customers that we did not have access to in the past. So, it's a volume play, and I think Fermi already indicated that we're starting to see some small design events come through with these distributions. And then if you think about Capgemini, it's more of a value play. And I think Louis indicated before, these are large enterprises and customers who will bring complex solutions, deploy at scale to enterprises. So, the modeling is, you know, on both slightly different. One, the situation channels reseller scaling with, you know, small designments, so building up small volume. The other ones are large customers and logos, which have much larger opportunity deals, but complex opportunities. So, On both sides, the modeling is done on value versus volume. And I think the earlier question was also you should see different timelines on this. So we do expect faster timelines on the distribution side and more longer timelines and the more larger complex opportunities. But the modeling has been built out for seven years of how this will come to fruition. And of course, they are some of them new to our products. So initial ramp up, market making, pilot opportunities is what we are allowing for. But we'll keep you updated as we start winning some large deals and, you know, meaningful revenue, as Fermi pointed out, you know, in future quarters.

Great. Thank you, Muneyb. I have a follow-up on X7. Is that accelerator chip primarily targeted for as a channel product, or is there no distinction between for channel or for direct?

There's no distinction, and in fact, I'm expecting that Both Capgemini and Magnica will do product rapid design for that and targeting different customers. Thank you, Fermi. That's it for me. Thank you.

Thank you. This does conclude the question and answer session of today's program. I'd like to hand the program back to Dr. Fermi Wang for any further remarks.

And thank all of you for joining our call today, and I hope to see you and talk to you next time.

Thank you, ladies and gentlemen, for your participation in today's conference This does conclude the program You may now disconnect Good day