Good day, everyone, and welcome to the PDF Solutions, Inc. Conference Call to discuss its Financial Results for the Second Quarter ending Sunday, June 30, 2024. At this time, all participants are in a listen-only mode. After the speakers' presentation, there will be a question-and-answer session. As a reminder, this conference is being recorded. If you have not yet received a copy of the corresponding press release, it has been posted to PDF's website at www.pdf.com. Some of the statements that will be made in the course of this conference are forward-looking, including statements regarding PDF's future financial results and performance, growth rates, and demand for its solutions. PDF's actual results could differ materially. You could refer to the section entitled Risk Factors on pages 16 through 36 of PDF's Annual Report on Form 10-K for the fiscal year ended December 31, 2023 and similar disclosures in subsequent SEC filings. The forward-looking statements and risks stated in this conference call are based on information available to PDF today. PDF assumes no obligation to update them. Now I'd like to introduce John Kibarian, PDF's President and Chief Executive Officer; and Adnan Raza, PDF's Chief Financial Officer. Mr. Kibarian, please go ahead, sir.

Thank you for joining us on today's call. If you have not already seen our earnings press release and management report for the second quarter, please go to the Investors section of our website where each has been posted. Before Adnan discusses the financials in detail, I have some comments to make about our observations for the second quarter and our view for the market for the remainder of the year. Our bookings in the second quarter were lower than the strong Q1. Due to the nature of some of the larger contracts, we expect lumpiness in any given quarter and therefore, find it meaningful to look at a rolling average. Since SaaS bookings started improving in Q4 of last year, we have been building backlog, which will support our future growth. The bookings in the quarter are mostly with customers that are either starting to deploy new systems like Sapience Manufacturing Hub and MLOps or expanding the usage of our platform. In both cases, we anticipate many of these contracts leading to expansion business in the future. Notable deals in the quarter include a large contract for Exensio Process Control for an advanced logic fab, a contract for initial deployment of Sapience Manufacturing Hub for a large logic manufacturer who's doing a significant SAP S/4HANA deployment. Successful completion of its initial phase is expected to result in a follow-on, much larger, more significant, multi-year license for SMH, tying all their manufacturing to the ERP system to facilitate new levels of productivity. That same customer, having already deployed Exensio and advanced packaging is also entering into a contract with us in the quarter to pilot Exensio for wafer fab analytics. We closed our first contract for MLOps, an AI-based product we announced in Q4 of last year. This contract is for a large fabless customer that is beginning their journey to deploy AI for testing of products. We anticipate successful application of AI for this use will result in their expanding the use of AI for most tests. A number of customers also expanded Exensio cloud usage. While increasing the annual run rate of these contracts, these expansions also set up for larger renewals, some of which we anticipate occurring in the next few quarters. Finally, bookings for Symmetrix connectivity run-time licenses showed modest improvements in Q2 over Q1 as our customers' equipment shipments increased. Overall, given the strong backlog and business model where most of our revenue is typically ratably recognized, we continue to deliver strong results in revenue and earnings. We were pleased with the business results in the quarter as it demonstrates the strength of our business model. Turning to DFI. As we stated before, we have two machines at one customer and another machine at a second customer. A third has the rights to send us wafers this year for us to analyze on the eProbe machine in our facility while they build their new fab. The machine will be shipped to them when the fab is ready. For the first two customers, usage in Q2 was very high. What is clear is that the direct scan application of the eProbe has very unique capabilities that we believe are valuable in bringing up logic product yields and eventually controlling the production of those products. In both accounts, we've begun discussions about expanding the number of machines. We anticipate those discussions may take the next couple of quarters to conclude. Now let me turn to discuss our view on the environment and our perspective on the second half of the year. As we talk with our customers about their business, some are experiencing weakness while others are growing. As a result, we believe that for the overall semiconductor market, growth will be unevenly distributed. It won't be the case that a rising tide lifts all boats. With that said, our engagement with customers remains high, driven by fabs developing advanced logic processes such as 2-nanometer; fabless customers deploying advanced test control software, often with AI/ML to augment conventional test methodologies; and companies engaged in digital transformations, attempting to leverage data, whether that is IDMs, fabless foundries, and equipment vendors. Given these trends and strong customer engagement, we continue to expect revenue growth for the second half of the year to be about 20% over the same period a year ago. I want to thank all the PDF employees and contractors for their efforts during the first half of the year. Now I'll turn the call over to Adnan who will review the financials and provide his perspective on our results.

Thank you, John. Good afternoon, everyone, and good to speak with you all again today. We're pleased to review the financial results of the second quarter and to bring you up to date on the progress of the business. Our Form 10-Q has also been filed with the SEC today. Please note that all of the financial results we discuss in today's call will be on a non-GAAP basis, and a reconciliation to GAAP financials is provided in the materials on our website. For Q2, our total revenue was $41.7 million, essentially flat versus the same period a year ago and up slightly versus the prior quarter. Analytics revenue was up 3% to $38.1 million this quarter versus $37.1 million for the second quarter of 2023 and represented 91% of total revenues this quarter. The growth in our analytics revenue came from increased usage and upsized renewals by our Exensio customers as well as an uptick in our Symmetrix run-time licenses. As John said, we are excited about the level of engagement with our customers during the quarter, including Exensio adoption by a leading-edge fab customer, expansion of Exensio deployment by multiple merchant semiconductor customers, extension with a cloud provider for their internal use of Exensio, and an additional win on the Sapience Manufacturing Hub with our partner, SAP. We're also pleased with the engagement activity for our DFI system and eProbe machine, and you will see us investing further to continue to address the market needs. During the second quarter, revenue contribution from Integrated Yield Ramp was $3.5 million, down $0.9 million or 21% compared to the same quarter a year ago, driven by lower gain share from our Asian customers as a result of the low volumes. We're pleased with our backlog, which grew in the first half of this year from $229.8 million at the end of December 23 to $243.2 million at the end of this quarter. The trends John and I have been discussing and the level of customer engagement lead us to believe we will grow our backlog in the second half of the year as well. We reported gross margins of 75% for the quarter, up versus both 72% for the last quarter and 74% for the same quarter of the prior year. We are pleased with our gross margin performance for the quarter, which is in line with the long-term target financial model we shared at our Analyst Day and User Conference last year. On the operating expense side, our expenses for the quarter were slightly down versus the prior quarter driven by better utilization of our headcount resources, primarily in R&D, while SG&A expense was essentially flat compared to the prior quarter. For EPS, we reported a profit of $0.18 for the quarter, improving from the $0.15 we reported for the prior quarter. We ended the quarter with cash and cash equivalents of $118 million compared to $123 million for the prior quarter. We generated a small operating cash flow for the quarter. During the quarter, we used cash primarily for investment to support the development of our DFI system to address the market need and the build of additional machines we mentioned earlier. As we look to the rest of the year, we remain committed to our prior guidance for the year, with revenue growth returning to our 20% long-term target for the second half of the year compared to the matching prior year period. With that, let me turn the call over to the operator for Q&A.

Thank you, Mr. Raza. Our first question comes from the line of Blair Abernethy with Rosenblatt Securities. Your line is open.

Thanks. Nice quarter, guys.

Thank you, Blair.

Just two questions, I guess, for me. Just one on the DFI and the other one on the MLOps system. So on the DFI, you talked at length about it last quarter. I just want to see what you see as having advanced or changed over the quarter. And what is your manufacturing plan looking like? I see that CapEx is stepping up. So give us some sense of the ramp-up in capacity to be able to deliver equipment on the DFI. And then on the MLOps system, can you give us some sense of how big are these transactions? It seems like from the time of the introduction of the product, the actual sale is a pretty short selling cycle. Just maybe talk a little bit about that.

Sure. So on the eProbe, what's developed in the quarter. As I said in my prepared remarks, Blair, usage was very high at both customers. And we have a pretty good customer base in the fabless community, too. And so we started hearing from the fabless community about how they've been seeing the results. Two, the machine is very good at understanding the relationship between the design and the manufacturing yields, and most inspection tools just understand that you compare one inspection result to another to find problems; just understands where it is on the design. Therefore, the manufacturer can talk to the designers about what specific design capabilities they're seeing, etc. I think that's probably why they've communicated with the customer base about it. So that's always good when you hear it from our customers' customer. And as we've had dialogues, I think we're starting to get some understanding or indication from at least the first two customers about what would be the potential number of machines they need. We don't think in the short term, we can meet both of their needs. It will probably spread out throughout all of 2025 if they were both to come in what they say. And there's a lot of ifs there, so let's not get too far ahead of ourselves. But as you could see from our CapEx build-out, trying to mitigate as much as possible contingencies around being able to respond to demand. The typical lead time for machines like this is quite long. So we're trying to do our best to pull it in, but you can pull it in a matter of a couple of months. You can't go and make this an instant lead time. So I think the lead times to those are not much different than the lead times for other machines of similar complexity, which is nine months to a year kind of timeframe. So we are very excited about where we are right now. We do think, besides the opportunities with these customers, we think it speaks more broadly. We've had a lot of incremental requests in memory and other areas around pilots because of this unique capability of the machine to know exactly where it is in the design and apply appropriate stimulus on each part of the design. So that's kind of my answer on the DFI eProbe. If I move on to the MLOps, again, we're seeing with customers, as they're doing more and more advanced packaging, there's many more test insertions and they want to be able to see models extracted from earlier test results up into later tests to get better performance, better test time, better quality screening, etc. And this has been the first application for this. This is a customer we started working with. It seems very short from announcement, but we started working with this customer before the announcement as we were getting closed. It was kind of an early lead customer. The initial deployment is on a relatively small number of testers. That's why I said it's really only a small portion of their total production. And we believe, as you would roll it out across a larger number of testers, as they would apply to more and more products, it could be a relatively meaningful contract. At this stage, it is a modest contract. It's not super huge. But it is, again, I would say, what would amount to being a couple percent of their test of a very complex product they want to prove this methodology works out for. And I expect them to roll it out more as they gain success with AI at test.

Okay. Great. Thanks for the color, John. And maybe just Adnan, just following on the DFI comments. What should we expect in CapEx going forward? I know you've got lots of cash. But $5.3 million this quarter, typically, you've been running $2 million to $3 million a quarter. What should we be looking for there?

Yes, a very reasonable question. To be honest, when we were ramping up DFI many quarters ago, we were also spending more than what we have in the quarters before this one. So look, I mean, for the next couple of quarters, at least, we think CapEx probably stays at similar levels. As John said, this is a pretty unique time for us with the engagement with multiple customers on leading edge, and we want to be making sure that we are well positioned to take advantage of that opportunity. So probably similar to where we saw Q2 come in is a fair estimate. I think the thing to keep in mind also is, look, we have been operating cash flow positive for a long, long time, and we intend to stay that way as well, and in between the other uses of cash we'll do from time to time as the opportunities present or going to relate to, for example, share purchases, which we have done in Q1.

Okay, great. Thanks very much, guys.

Thank you. Please stand by for our next question. Our next question comes from the line of Gus Richard with Northland Capital Markets. Your line is open.

Yes, thanks for taking my questions. Nice quarter. It sounds like you've got an exciting outlook. I was just wondering, on the DFI and your engagement with your two customers, what is the use case? Is it yield ramp? Is it bringing up a new product? Or is it actually in fab in production?

Yes. So far, because it's been applied to very advanced nodes, Gus, it's been used for bringing up nodes and bringing up specific products. So each product uses the process a little differently, the design layouts are different. We used to refer to these things in the industry as systematics or something unique about the design. But now the process windows are so tight. There's always something specific about every design. So they've been, I think across a couple of customers, using it on many different designs as they come into a node. We believe that even though the initial use is there, you tape out many designs in production for a long time. So it's going to give you a first kind of use level even in a production fab, not just a development fab. And we seem to hear that from the customer base. And over time, we believe it results in a control application as well just because the marginalities, the process windows are so tight, the need to monitor will remain. So early on, I think what's been happening over the last year, or I'd say six months, has been really around bringing up products. I think as you transition into 2025, I suspect that it ends up being not just to bring up the products but to control the technology.

Got it. And then I'll just stick with DFI. Can you add a little more color to your build plans for next year? And I'm assuming that the CapEx, because you effectively lease these products, the spending on building the tools and the various assemblies and with your sub-cons is actual CapEx?

We are increasing our build plans to produce more units. A reasonable expectation in the short term, over the next four quarters, would be to build between four and eight units per year. We believe our suppliers are capable of producing more than that, but this will likely serve as our next target. You're correct that the machines have been provided on a subscription basis, which means it's a capital expenditure for us. In the future, we may modify the business model with our customers, potentially allowing for equipment purchases and software subscriptions. There’s still some flexibility in how both our customers and we perceive the optimal approach. As you mentioned, if customers need to operate the machines throughout their lifespan, they might prefer to buy the equipment and subscribe to software. Our customers are significantly larger than we are, so we will take their input into account to determine the best collaborative approach. Over time, capital expenditure may decrease from our balance sheet if they decide to purchase the equipment, especially if the control application is involved.

Got it. And then the last one for me is on the MLOps. Clearly, there's an expansion of chiplets and multi-die packaging, if you will. And I was just wondering, are those two related? And if so, are you starting to see increased interest into OSATs?

They are related. The interest is coming from the product companies, the know-how about chiplet matching is really the responsibility of the fabless companies or the product group because they own the test program and they know how to interpret that, how to build the model to interpret that result, effectively. And then know how to, let's say, reduce test time, downstream or add additional tests or match chiplets better, so you get an overall system performance that's better. This is one of the motivations for this customer as well as others that we've dialogued with. It is also having us go back and look at our DEX network. We've made an investment in having our machines at the OSATs connected to their testers, so they can push data from the cloud. And MLOps really allows them to manage all of that data traffic up and down their manufacturing flow in order to initiate running of models, let's say, features for upstream tests to be ready downstream, so they can combine that extracted feature from the upstream test with the testing that's going on in real-time to make, let's say, a bidding decision or a sub-bidding decision, etc. So yes, you're right that it is very much related to chiplets and complexities on testing as a result of that. The OSATs have an important role to play because you need to integrate with their MES systems. Customers need to be integrated with their SAP system because they need to know where the chips are going and therefore, where the data needs to be sent. So it does bring up the overall system requirements that are needed. But the buyer and the user of it is really still the fabless community more than the OSAT today. I think it will stay that way, too, Gus.

Okay, all right. That's it for me. Thanks so much.

Thank you. Please stand by for our next question. Our next question comes from the line of Christian Schwab with Craig-Hallum. Your line is open.

Thanks for taking my question. So can you give us an update? You've been working for some time on a meaningful semiconductor producer who is now going through a tremendous mess, for lack of any other description. Can you kind of give us an update of what the revenue opportunity over a multiyear time frame could be with that customer now that dates in production could be readjusted?

Yes. So Christian, thank you for the question. We're always very respectful of our customers' proprietary information and what's going on in any given customers. So we don't comment on specific customers per se. But I can tell you in general, though, right, our technology is used to help customers be more efficient and more effective. So we always are mindful of the economic situation every customer is going through and think about what's the best way to work with them. But often, our technology is very important for customers to drive transformation. And so we look at these as opportunities often for us and the customer to be more effective in how they use our systems. And often, it builds a larger business with us over the longer term sometimes. You don't know if the short term it does do. And then that's true for every case when we're in these situations. In general, our technology is very important for being much more efficient in manufacturing. And I think our track record of being instrumental for customers in change management is quite long.

So put another way, do you think this opens up an expansion of opportunity where things could happen faster than previously expected then?

Customers that are trying to move to advanced nodes, I think the complexity of the technology is opening up opportunities. When customers are really looking for that to happen now and often when customers are going through transformations, they're looking for that to happen now, I believe our systems are increasingly valuable for those customers. So we look for ways to be able to deliver value, mindful of the fact that when customers are challenged economically, we also have to sharpen our pencils and think of how to be flexible as well.

Fantastic, great. No other questions. Thank you.

Thank you. Please stand by for our next question. Our next question comes from the line of William Jellison with D.A. Davidson. Your line is open.

Good afternoon and thanks for taking the question. I wanted to start out by asking, amongst your existing Exensio customer base, what you're seeing with respect to trends, adopting the next incremental module for them, what are you seeing amongst those folks?

Yes, that's a great question. Thank you for your inquiry. In my prepared remarks, I discussed the key drivers for our business, two of which relate directly to our customers. Firstly, I mentioned the increased automation in testing. The MLOps opportunity is something I have frequently highlighted. As I mentioned earlier, it involves a more sophisticated testing process, specifically moving from applying rules to utilizing models, often based on machine learning or artificial intelligence, in preparation for chiplet production, which enhances quality and efficiency. Secondly, I broadly classified another driver as digital transformation. We observe this driving two significant aspects of our operations; one being the Sapience Manufacturing Hub, which integrates the Exensio database. This serves as a connection point for our partners, linking operations from the shop floor to upper management. When businesses seek to undergo transformation, they must be able to utilize any AI or ML they implement effectively. Customers deploying ML models recognize the importance of understanding their ERP system, particularly how to track where a wafer should go when sending data to an OSAT for package testing. This connection is vital for financial teams to obtain accurate data and enhance predictability and economic awareness, while also being crucial for engineering operations teams to integrate increased automation, typically through AI, into their production workflows. We see considerable opportunity here with the SMH. Additionally, many customers are expanding their cloud offerings. As they embark on this journey, they often realize they need to consolidate their data in one location, ensuring it is properly aligned across the manufacturing supply chain. Since applying ML models often requires substantial time spent on data preparation, having organized data simplifies the process. If this organization is achieved with scripts, it can reduce the efficiency of moving the model online, relying heavily on the engineer who developed it. Creating a centralized data system, sometimes referred to as a data lake or warehouse, enables the effective development of AI and ML solutions. We’ve seen expansion contracts this quarter, with customers increasingly depending on Exensio for enhanced data orchestration and management capabilities. The MLOps product facilitates this greatly. In summary, we see significant opportunities with our customer base focusing on three key areas: enhancing testing processes, synchronizing engineering and financial operations, and ensuring all manufacturing and engineering data is organized centrally with a common API for further development.

Great. Thank you. And then as a follow-up, with respect to DFI, is it still the case that on the revenue generation side of the machines that it tends to scale over time? From the moment you ship a machine, the revenue generation starts out very small. And as the activity scales on that machine over time, it increases. Is that still the way you view it?

Yes, I think look, I mean, one thing to keep in mind is our DFI engagements aren't just ever about just the tool itself. So it's a combination of software, and it's a combination of the hardware. And even within the software, there's many pieces of software, obviously. We've talked about the Fire software, for example, which is used to inform our tool about the analytics that will be performed based on the design. And then there's obviously the other analytics software. So depending on the usage of those, some pieces may be accelerated. For example, if the machine is in the early stage, perhaps that one gets accelerated. We have talked about the lease treatment of the machine that can happen with some contracts. However, look, I mean, on a longer-term, our goal always is that the customer's usage of the whole system grows over time. And that is why some of the past contracts that they've been done have been on a token basis, such that we expect the customer to be utilizing. And hopefully, we are providing them more value over the time and therefore growing that opportunity.

Right. Thank you.

Thank you. Please standby for our next question. Our next question comes from the line of Andrew Wiener with Samjo Management.

John, at the start of the call, you mentioned two lead DFIs that you referred to as customers. However, I believe that one of them is currently undergoing a manufacturing evaluation and is not yet a DFI customer. Given your comments about ongoing discussions regarding the potential deployment of additional machines, can we conclude that the evaluation is progressing positively and that our confidence in converting this into a paying DFI customer has increased?

That would be correct, Andrew. We shipped the machine at the end of last year, came out beginning of this year. Second quarter was a very heavy usage period, as I said in my prepared remarks. And we saw good results there. They did as well. I think that really speaks to just the value the machine can create. We have a lot of hurdles we still have to get over in both customers. So we're not by any means, able to just sit back here. There's a lot of work to be done. But we've gotten very positive feedback from that customer. And yes, our confidence is increasing.

I just wanted to clarify something. When you mentioned that a few people inquired about your capacity and referenced a comment about not being able to support, I understand that these are discussions and not actual orders yet. However, could you elaborate on the needs of the two main customers and whether it means that, given the current capacity of four decades, it is insufficient? Are you considering ways to produce more than eight? I recognize this isn't a revenue or order forecast, but I'm trying to grasp the demand from these customers and what your perspective is on the type of capacity you might aim for in 2025.

Yes. So they've both given us ranges. And if it was both from the low end of the range, then I think we would be, okay. If they were in the middle of the range, we're probably a little short. And if on the higher end of the range, we probably have a bigger issue. And we're also mindful of the fact that we have customers that are asking for evals and potential demo machines, etc., that as we see a number of interesting applications in memory and in other logic manufacturers. So we need to have some slack in that capacity. If we just did everything that was good for them, then maybe we don't have a way to expand our business in 2026. So we have to be somewhat thoughtful about making sure we've got ability to expand out in the marketplace. So even under kind of their modest or the low end of their requirements where I think we'd be pretty okay. We've also got to look a little bit at where we would be in terms of being able to do manufacturing evaluation, etc. We've kind of also squeezed ourselves internally to support the three customers we're supporting right now. And so we don't really have much capacity as we would like necessarily internally for demos with other customers and some other things right now. So we're a little bit hamstrung. So yes, we are looking to see what we could do to increase that number. We will make that decision as we get through this year to see how things kind of build out with the customer base. One of them could decide they don't want to do it, right, so we've got to keep a lot of contingencies there.

Has there been any conversations with the third customer that you haven't shipped the tool to yet, but I guess you're running wafers internally, as to what their demand could look like or would look like? I mean, I know in the past, you've talked about sort of most customers who are going to be using it in any real volume would likely want at least a second tool just for redundancy purposes?

We've not had very many conversations with them about that yet, Andrew. It is something we need to do as we kind of think about 2025 and beyond. So it will be something we'll do in the second half of this year. We've been pretty busy in the second quarter, just in early third quarter, just kind of understanding the first two.

And then for some of those other applications you're talking about, whether it's other logic players or memory, are they actually currently shipping you any sort of wafer so that you can run internally to demonstrate capabilities? Or is it more, right now, sort of technical conversations?

Yes. We have at least one customer that I know off the top of my head that's already shipped those wafers and the memory applications. We have others that are interested in doing that. We are mindful of bandwidth, right? So we're trying to kind of swap them in a way that we don't take our eye off the lead customers. But yes, we've already gotten memory wafers and starting to show them results.

Okay. Let's discuss MLOps. Initially, the focus was on the test application, and several pilots have been conducted. Can you provide more insight into whether you are currently taking on more pilots or if you are waiting for existing pilots to convert into commercial engagements, using those as proof points to attract other potential customers? Additionally, I believe you mentioned the importance of consolidating all data in one place to create machine learning or AI-based applications, with MLOps serving as the enabler. Are there any plans to empower customers to utilize MLOps independently and develop their own use cases?

Yes, that's a great question, Andrew. I'll address the three-part question you raised. Firstly, there are additional pilots underway with customers and various sectors of the industry. We're also taking a moment to evaluate how we can improve our offerings for customers. MLOps fundamentally consists of two elements: the operations involved in orchestrating your data for model building and managing it once it's deployed in the field. One of the main challenges lies in the testing phase, as customers may use separate companies for wafer sort tests, package tests, and card-level tests. Many of our fabless customers are evolving into system companies by developing entire cards or systems now. Hence, managing the data flow once a model is in place, along with monitoring production and test results, allows customers to set rules for when they want to initiate a model update or modification. This is where MLOps provides a solution. Of the two challenges, we believe the second aspect is more critical in the long run. We're working on enhancing that to better serve our customers. Regarding your question about empowering customers, the goal of MLOps is precisely that. Customers can utilize our environment to create their own models using default example models we offer, or they can leverage other systems. They can orchestrate their data through Exensio, extract it from the APIs, adopt different systems to develop their models, and then reintegrate those models back into MLOps throughout their manufacturing process. They are not obliged to utilize our learning environment if they prefer not to. We've designed our approach with these three levels of flexibility in mind since the market includes all types of engineers. Some early adopters have developed their own model-building workflows but prefer not to handle the daily management of systems. They want software solutions to streamline these processes, which is the role of MLOps. Other customers, who are further along their journey, might prefer using our environment but still want to create their own models due to their expertise with their products. Then there are those who, with a predefined pipeline for test time reduction or quality assessment, simply wish to adjust and customize our default model for their specific applications. All three functionalities are available within our product today, and we plan to enhance them. At SEMICON, for example, we showcased smaller start-up companies making ML presentations at our booth because we're eager to collaborate with the broader community. We're not aiming to monopolize modeling; our objective is to assist a wide range of individuals in successfully deploying models.

And I guess maybe my last question is, have you made any progress on any of the battery pilots? You made a position in that space.

We have been collaborating with battery manufacturers and consumers, launching a pilot this month, which will actually begin in about a week. This is similar to our project with the eProbe, where customers provided us with sample materials. We demonstrated in our lab the capabilities of our image pipeline and the insights it could offer regarding their battery cathodes and anodes. Now, we are in the process of implementing that software and system at a manufacturing site, allowing both the manufacturer and the battery consumer to work together on production control. This pilot marks a significant step forward as we transition from handling a limited amount of material in our lab to a real production environment where there are various challenges, including noise and vibrations, while handling cathode and anode films at high speeds. We are currently at a crucial milestone and are very excited about the progress we’ve made.

Okay. Great. Thank you.

Thank you. At this time, there are no more questions. Ladies and gentlemen, this concludes the program. Thank you for joining us today. Have a wonderful day.