DSC

Good day, ladies and gentlemen. Thank you for standing by, and welcome to the DSC Holdings Second Quarter 2026 English Earnings Webcast. I am Gary Dvorchak, Managing Director of The Blueshirt Group, DSC's investor relations firm. I will be the host for today's presentation. I will go over a few logistical items, then turn the presentation over to DSC.

Currently, all participants are in a listen-only mode. After the speaker presentation, there will be a question-and-answer session. At that time, we will explain how the Q&A will work. Please edit your name in the webinar to show your name and firm name. We will need this to call on you for any questions. As a reminder, today's program will be recorded. The recording and associated transcript will be available in the IR section of DSC's website shortly after we conclude. The earnings release is available on the company's IR website now.

Please note that today's discussion will contain forward-looking statements made pursuant to the Safe Harbor Provisions of the U.S. Private Securities Litigation Reform Act of 1995. Forward-looking statements involve inherent risks and uncertainties. As such, the company's actual results may be materially different from the expectations expressed today. Further information regarding these and other risks and uncertainties is included in today's press release, and the company's public filings with the Securities and Exchange Commission.

The company does not assume any obligation to update any forward-looking statements, except as required under applicable law. Also, please note that all numbers presented are in RMB unless stated otherwise. Additionally, during the call, we may refer to non-GAAP financial measures. You can find a reconciliation of the most directly comparable GAAP measures in the materials posted on our investor relations website.

On the webcast today with me, we have Ms. Qin Zou, Director and Chief Financial Officer, and Nancy Wang, Director of Investment and Financing. Let me now turn the presentation over to our CFO, Ms. Zou. Please go ahead.

Thank you, Gary. Good morning, everyone, or good afternoon, wherever you are. Thank you for joining DSC's first earning webcast as a public company. A couple of hours ago, we held the Chinese language webcast, for our Chinese-speaking audience, where our founder, Mr. Junhong Yao, covered operating highlights, and I covered the financials. I will now deliver both in English, and prepared contents of the two webcasts will be identical. The Q&A will naturally differ, but the full bilingual transcripts of both sessions will be posted on our IR website.

Let me start with the operating highlights from Mr. Yao. In June, DSC completed its IPO on Nasdaq, an important milestone for the company and our formal debut onto the international capital markets. We are keenly aware that we must repay shareholders' trust with sound disclosure, solid execution, and long-term operating results.

In the second quarter, China's auto market remained under pressure, yet our key operating metrics stayed resilient, with substantially narrowed losses. Our revenue grew at 3.7% year-over-year, and our adjusted net loss narrowed by 61.5%. Two business developments in this quarter deserve particular attention. One, our AI products are now delivering real results in real economy. Two, China's used car exports are surging, where we have begun to prudently explore international opportunities. Before we address our business performance, let's take a look at the industry first.

Intense price competition in the new car market in China triggered rapid depreciation of used car inventory value. DaFengChe, which is the operating system we provide to the entire used car industry here in China, DaFengChe's data showed prices of mainstream models held by mid-sized and large-sized dealers fell by 10%-15% within just two months.

Industry experts estimate that more than 70% of China's used car dealers operated at a loss in the first half of this year. This upheaval is breaking the old way of running a used car business that was based on experience and gut feel. Leading dealers are now relying on real-time market data for purchasing, pricing, and inventory risk management. Data-driven is no longer just a fancy concept. To the dealers in China today, it is a matter of profit and, in some cases, survival. That pressure is rapidly deepening the dealers' reliance on our operating system and our AI services.

Even against this backdrop, the used car transaction volume in the entire country still rose about 1.5% in the first half. Now it's at a record 9.72 million units, according to the China Automobile Dealers Association, a semi-government association body.

In June is a very important month. In June, used car transactions finally surpassed new car retail sales for the first time in history. It is a historic milestone. We expect the turbulence in the industry to persist before a new equilibrium forms. When it comes to used car dealers, a classic Chinese saying sums it well, "Wildfire cannot burn them out. When a spring breeze blows, they rise again." Wave after wave of resourceful dealers will adapt and grow, and we will stand alongside them through this transformation.

Next, I want to reiterate DSC's identity. We are the enabler of the used car industry. We are not a dealer. We do not have any consumer traffic, nor do we do any consumer sales. We provide dealers with our intelligent operating system, DaFengChe, and on top of it, the transaction services and AI services the dealers need.

According to China Insights Consultancy, DaFengChe's market share has remained above 90% for quite several years. This gives us two invaluable assets. Industry data that is massive, granular, and real-time, and exclusively ours. Plus, this long-term, very durable, and deep connection with the dealers nationwide. On that foundation, we offer the transaction services that are essential to their operations. We offer B2B matching, which includes China's number two online used car auction platform. We offer used car inspection with over 4,000 inspectors across 250 cities, the widest coverage in China.

We offer vehicle delivery with over 100 self-operated warehouses in every province in China, with collaborations with 40,000 car carriers and a reach into more than 2,600 counties and cities. This makes us China's largest single car delivery provider.

We also offer other dealer channel services, connecting dealers with traffic platforms or financial institutions, or whoever wants to reach Chinese used car dealer community effectively and efficiently. Our mission is to advance the digitalization of auto commerce. We firmly believe that a company's value ultimately lies in the value it creates for society, and DSC will be adequately rewarded out of the incremental value we create for this industry. Now, the two developments that are worth noting. The first one is, of course, AI.

We spent more than a decade digitalizing this industry. AI now gives us the opportunity to lead it into the intelligence age. As stated in our IPO prospectus, DSC is the AI application infrastructure for China's used car industry. Vertical AI depends on three elements: large language models, high-quality industry data, and digitalized application scenarios.

We exclusively own two of the three, the data and the application scenarios. This is why our AI products suit dealers' need very well, and they can be adopted rapidly through the dealers' existing workflows. Our AI products fall into three categories: tools, digital employees, and a platform agent that basically has the collective brain of the industry and our nationwide execution capability. Let's go down the list to have an introduction.

Among the tools that have already been launched, we have the Market Intelligence Assistant, which delivers hourly updated retail and wholesale intelligence on every car a dealer is considering acquiring, whether to buy the car, and at what price. Our prospectus included the story of Mr. Yang Hang, a dealer from Kunming, Yunnan Province.

His story was that he was facing a seller who demanded over RMB 50,000 for a Volkswagen Polo, and all of his four staff buyers said, "No. It's not going to sell. We're going to lose money on this car if we pay this price." Mr. Yang decided to trust our Market Intelligence Assistant, and he went ahead and did the purchase. The car sold within 48 hours with a 7% gross margin, and it was the fastest selling gas car of the month.

He even told us that he could have sold for more, but he wanted to make an example out of this to train his employees to no longer make their decisions based on their experience or their gut feeling, and they should adopt a new mode of thinking and rely on data, and rely on our Market Intelligence Assistant.

That's one of the many stories we have. Alongside our Market Intelligence Assistant, we also provide several others, like the Imaging Assistant, which can turn a very casual photo of a car taken on a parking lot into a polished version, like the photo was taken in a very professional studio, but without losing the details of the car. We also have a Sales Script Assistant that can summarize any vehicle selling points and pinpoint the consumer's needs from a conversation record.

We also have video assistants that can generate marketing short videos of different styles, just using some raw photo and video clips from the dealer's employees. As you know, different social media platforms have different personas, and to market on different platforms, you need the video to fit that persona. We can do that just with one click.

Since launching these AI-enabled assistants in March, we have seen very rapid adaptation, and now more than 4,100 dealerships are using them by the end of June numbers. The average daily token consumption, of course, went from zero to over 150 million by the end of June. The second AI application we have is we call it digital employees. It is a step up from the tools, right?

We have several digital employees already deployed, working, and we have a few more coming out. First, we have the social media operations specialist. It engages consumers in live streams and short video comments. It pushes the leads into the DaFengChe CRM. By now, we have over 3,215 paying deployments by the end of June. We also have the management assistant.

Once authorized to access a dealership's data, it can function as a real management assistant. It can pull data and gives the owner of the dealership real-time analysis and management advice. So far, we have 295 of those paying deployments. The industry employs roughly 800,000 to 1 million people. That is based on our assessment. We are assessing that role by role where AI can help. The biggest opportunities we see is in sales and procurement. Basically, buying and selling, right? These positions are the most important to the dealer, and also most costly.

On average, we estimate that they cost about 35%-50% of the dealer's gross profit just for their compensation. We are training digital sales employees, and we are training digital procurement employees, and they are progressing, and we should be able to deploy them for our dealers in the near future. We will update everybody, of course, when that actually happens.

The third one is, in my opinion, is most important and most exciting one, is what we call a platform agent. Or you call it a platform-level AI agent. It is more than that. Basically, you can understand it as an intelligent being with the collective brain of the industry, because we can analyze everything, and also it has legs and arms, because it has our nationwide execution capability. That one is very exciting to us, and we are working intensely on developing it, and we hope to share with you the progress soon.

The second of the two business developments I would like to share is the international opportunities. Right? China has the world's largest car park, and it is rapidly aging. Naturally, while we were exporting new cars, we are also exporting used cars. According to China Automobile Dealers Association, the export went up 61% year over year for the first half. Much of last year's volume, based on our estimate, were those zero-mileage pseudo-used cars.

The government quickly caught up on that, and a new regulation came out in January requiring automakers to consent to export vehicles registered under 180 days, effectively closing the loophole. This implies genuine used car exports grew several fold when you look at 2026. I believe there are two fundamental drivers underneath this trend. One is rapid price declines making Chinese used cars globally competitive. Two is the new rule that is pushing the exporters from the pseudo-used cars to real used cars.

As an industry enabler, our path is to fit our systems, our services, to export-oriented dealers. Through them, we can reach overseas used car dealing ecosystems. Today, there seems to exist an exceptional window for us to go abroad. To these exporters, we have two distinctive advantages. One is that we have China's largest real-time verified inventory pool. Over 1.7 million vehicles live on our system versus a fraction of that number on some other platforms. Together with a one-stop inspection service, logistics, and warehousing, we can service the exporters' needs pretty much seamlessly.

We also believe that given in a lot of these markets worldwide, used car dealing, we're still in a very under-digitalized state. The replication of our operating system, DaFengChe, in other markets is also highly possible if this export trend continues.

We are prudently exploring these opportunities, but how fast we proceed will be determined by a number of factors we will consider. Anyhow, to close, DSC, in Chinese we say DaFengChe, which is behind me, is in its 14th year. We're not a very young company. We have survived several black swan events.

We have had large-scale spinoffs and reorganizations and restructures, and we have started building most of today's business in the times of great adversity. Resilience is in our DNA. We have just set out on this new journey, and we're very pleased to have your interest. That concludes Mr. Yao's prepared remarks. Now onto the financial highlights I shared on the Chinese webcast. Despite a pressured auto market, our key operating metrics remained resilient.

Revenue increased 3.7% year-over-year and 14% sequentially compared to Q1, which is largely in line with the industry conditions and our seasonality. For our industry, especially in China, the first quarter is typically the slowest. Winter and Chinese New Year. The activities pick up in the second quarter, and then the third and the fourth quarter are the peaks. Our adjusted net loss narrowed by 61.5% year-over-year from RMB 19.2 million to RMB 7.2 million, reflecting our focus on the quality of revenue growth and on profitability.

Before the income statement, I would like to say a few words on the operating metrics we just started disclosing this quarter. We previously disclosed similar operating metrics, but that one covered both new car brokers and used car dealers.

Beginning this quarter, we will focus exclusively on used car dealers. This change also incorporates investor feedback from our IPO roadshows, and it is designed to help investors easily track the underlying drivers of our most important business segment over time. The framework has two components. On the first layer is user engagement on DaFengChe. We have the average monthly active dealership counts or dealership MAU. You just think of it as this is about the dealership, the stores, the businesses.

Then we have the average monthly active user accounts. We call it user MAU, and those are the individual accounts under the dealerships, but they're not consumers, they're basically the employee accounts. A large dealership could employ five people or 50 people or 500 people, and then those are the employee accounts. These metrics are intended for gauging the health of our digital infrastructure.

Since the operating system is so important to us and to our overall story, we want you to have the data to be able to easily track whether the foundation is healthy. Indirectly, you can also have a peek into China's used car industry by looking at those data.

The second part of our operating metrics is all monetization metrics. It has two levels, too. The first level is the dealerships. Because dealerships or dealers, they are our monetization units. You basically count heads. How many dealerships have you monetized? It's an important metric to assess the breadth of our monetization, these numbers in the sense of the coverage of our monetization. Our revenue is actually generated from transaction services. Each time we provide a service, we generate a fee. Dealerships are not all created equal.

One dealership could generate five inspection transactions for us, inspection orders for us a month. Another dealership could generate 50 inspection orders, plus 10 other orders for us. Dealerships are not created all equal in our monetization. In order to really get to the bottom of it, we need to go down to the transaction level. We wanted to give you the number of monetized transaction services for any given period. That's the logic behind designing those operating metrics.

Alongside these two metrics, we of course will disclose the average number, the average revenue per used car dealership, and the average revenue per transaction, both monetized. These are more on the unit economics level. Those are smaller numbers and much easier to digest and track and analyze. Together, we have the operating system engagement metrics, and we have the monetization metrics.

We want to give you those two metrics combined so that you can easily assess how stable our foundation or our moat is, and how fast our revenue growth is. Together, that's the complete picture. I'm going to finally talk about our second quarter numbers. Dealership MAU was over 65,000, and user MAU was close to 200,000. The exact numbers are on the website. Everybody can read them. The former, the dealer MAUs, actually went down a little bit compared to Q1, but the user MAU went up a little bit compared to Q1.

We think that it's actually just a reflection of the industry reality. Because the operating pressure was so great, certain lesser dealerships kind of just went out of business. The people in the industry didn't disappear. They just moved on.

They moved to another dealership, so we see more user accounts, but slightly less dealer accounts. We generated revenue from over 9,000 used car dealerships. The average per-dealership revenue is over RMB 6,600. We recorded 214,000 monetized transaction services, and average per-service revenue is RMB 259. Again, exact numbers are on the website. Our revenue-generating services are still mainly transaction services like B2B matching, used car inspection, vehicle delivery, and other B2B collaboration.

Our operating system and other digital solutions we have, they have never been, and they will never be, a main driver for our revenue. Actually, as our transaction services revenue grow, we expect the contribution share of any kind of digitalization solutions to continue to decline. Now let me turn to the income statement.

Our total revenue increased modestly at 3.7%. The used car business was generally stable. The incremental growth primarily came from our software services to OEMs. It was partially offset by our decision to discontinue certain OEM marketing services.

Here I would like you to have two takeaways. One is that our existing business remained stable and resilient against industry backdrop. Also we are actively improving the quality of our revenue mix. I would also want to note that the quarter's incremental revenue carried a lower gross margin than our company overall level, so the cost of revenue for Q2 grew faster than revenue.

Our disciplined expense management nevertheless delivered a sharp narrowing of adjusted net loss. Speaking of loss, our GAAP net loss was RMB 240.5 million, but that included approximately RMB 227.8 million of share-based compensation that was recognized upon the IPO, and some other IPO-related expenses.

The GAAP number last year was RMB 25 million when we did not have any of those expenses related to the IPO. Our adjusted net loss was RMB 7.4 million for Q2 2026, compared to RMB 19.2 million in Q2 2025, and that is down 61.5%. It was primarily driven by just across the board reduction in our operating expenses. Our G&A expense went down 14%, sales and marketing went down 14%, and notably our R&D expenses went down 29% respectively, excluding share-based compensations.

Two forces made this pretty significant OPEX reduction possible. One is our disciplined resource allocation. We continuously seek to optimize our business mix. Sorry, my computer was running out of power, so give me one second. Okay. All good. Sorry.

Two things made it possible. One is that we tried to improve our business mix, and we have become very disciplined with how we allocate resources, so we shrank some of the businesses. Also we are striving for a more streamlined organization. Two, very importantly, for this OPEX reduction, we had a company-wide AI adoption campaign. This is for real.

Starting earlier this year, we launched this company-wide campaign called AI Era: Race Against Time, Fast and Furious. The Chinese name of this campaign actually took after that famous movie. This campaign requires every single one of our employees, except for those in the front lines offline, like those who work in warehouses or on docks or in the markets, like they are in the field. Right?

Excluding these employees, everybody, everyone else in the company, whether you work for a business unit or you work in a finance department or human resources or PR, everybody had to participate in this campaign. What does it do? They have to present their AI application achievements. It is a competition and there are rankings. Then we reward those ranking high, and then we give a punishment to those ranking at the bottom.

The rewards include extra stock options, and the punishment sometimes can be as severe as termination of employment. Right? After several months, this AI application or AI adaptation is no longer just what the senior management dreams of or wants everybody else to do. It has already become how our employees operate and how they work.

Naturally, we reaped some of the benefits and we have better processes. We actually saw very good AI application tools being created by our own employees. That gave the management enough room to further reduce our OPEX.

Finally, let me turn to the balance sheet. The IPO proceeds obviously enhanced our financial flexibility and strengthened the foundation of our business. This flexibility will not change our discipline. Whether it is AI or overseas markets or other growth areas, we will invest cautiously and in stages guided by tangible customer value and monetization results.

Looking forward, management is focused on three things I can share today. First is still grow our transaction service revenue. We are always looking at potentially expanding our service types and deepening our per-dealer monetization and raise the average revenue per dealer.

Second, we would like to very quickly test out different ways to monetize all the AI applications we have created so far and the ones we will create in the future. Third, keep improving efficiency and maintaining our cost discipline, so that we can achieve overall profitability as soon as possible. That concludes my prepared remarks, and also Mr. Yao's remarks. Gary, back to you, and we are ready for questions.

Okay. Thanks, Qin. We are now going to begin the Q&A session. To ask a question, use the raise hand function and we will call on you and open up your audio. I think a couple of people had dialed in. If you dial in by phone, excuse me, either press star nine to raise your hand, then star six to unmute. When you start, please state your name and your firm before your question so we know who you are.

Alternatively, if any of you prefer, there is a question box, a Q&A box, and you can type your question into the question box that is part of the webinar, and we can then pose that question to Qin. We will pause for a couple seconds, to let the queue form, and then we will start the Q&A. Our first question is going to come from Ella Ji with CR Global. Ella, you can go ahead.

Yes. Thank you for taking my questions. I have two. First, it is quite interesting regarding your latest development in your AI-related business. I wonder, can you further elaborate on the business model of these AI products? For example, is it transaction-based and you do a take rate, or is it going to be subscription-based? Also, who is bearing the cost of the AI token training and usage? Also, what are some business targets relating to your AI products that you would like to achieve, for example, by end of this year?

Okay. Thank you, Ella. Let me address them one by one. The first one is AI monetization, right?

Mm-hmm.

Yeah. As I introduced, we have three types of AI products. Call them products. The tools, the digital employees, and the platform AI. I do not actually have a good name for it yet. For the tools, as of now, we provide them mostly for free to our used car dealers. The operating system itself, DaFengChe, also comes free for most of its functions. We do have membership fees, like subscription fees, for a higher level of functionality. Certain of these AI-enabled functions are embedded into the higher categories.

Largely, they are free for the tools. Actually, sorry, let me rephrase. Of the tools for the Market Intelligence Assistant and certain other agent, I think we do charge a small fee. It's still very small. It is not going to form any meaningful revenue source for us yet.

We are testing out the dealers' willingness to pay for intelligence, and so far, as long as the cost is at a reasonable level, we do see a lot of paying agents. For the digital employee, the AI employee part, the second of our AI products, most of them are chargeable. The dealers pay for the employee, and we deploy them, right?

The number I just shared, they are all paying deployments. For the last one, the platform level or industry scale AI, I will have more to share, but it is not going to be something that we charge anyone a fee for. We believe it is going to be more exciting than just charging a fee. That is the monetization part of the AI products. You also asked, who is bearing the cost of the training, right? The tokens, et cetera.

That's interesting because we have the data, right? We do use all of the frontier models that are available in China's market. Because most of the training happen on our data, to my knowledge, as the Chief Financial Officer, we're not incurring any significant cost in external token use. It's actually one of the advantages of owning your own industry data. Then the last one, Ella, sorry, remind me. The targets, right? The time [crosstalk].

Yeah.

Yeah. For the tools, we're just continuously rolling them out depending on what the dealers need. Then we have rolled out four or five so far. You're just seeing a few short months, the last four or five months. Then for the digital employees, we have already deployed two or three. Then as I just introduced, we're looking at the most costly and the most important critical functions of dealers' work. Then we're training those employees.

I don't have a specific target date yet, but once that happens, we will share with the market. Maybe on the next call. Then for the third one, the very exciting, the industry scale collective brains, super intelligent AI platform, we're also working very hard on that. I don't have much to share this time, but hopefully soon.

Okay. Thank you. My second question is, we actually get this question quite a lot from investors. How does the DSC compare to some, for example, U.S. online auto services companies such as Carvana, and who do you think your true comps are?

Thank you for that question. Yeah, it goes back to Mr. Yao's prepared remarks where he talked about our identity, right? Our identity. When people hear about us, that you're in the used car industry, so are you similar to Carvana, or CarMax, or AutoTrader, or some Chinese company like Uxin or Autohome? Because those are the names they know from the used car industry.

Again, we are an enabler for used car dealers. We are not a used car dealer ourself, and we never do anything that's in competition with the used car dealers or have a conflict of interest with them. In the past, we've never went down those avenues. Compared to Carvana is a used car dealer, right? It's a very successful used car dealer, even though it had some pretty scary moments post-COVID when the chip prices caused used car price to skyrocket, then it dropped, then we all saw how Carvana's stock price dropped.

Anyhow, Carvana, CarMax, and many others like Uxin, they are used car merchants. They buy and sell used cars. They are D2C. We're not. In terms of a comp, when you look around the world really, it's really hard to find one for DaSouChe which created a much difficulty during IPO process. When you think about it, pretty amazing that in the largest car park economy in the world, where about 90% of the used cars are sold by this large number of small-scale dispersed used car dealers, an army of dealers in anywhere between 200,000-300,000 dealers nationwide in this massive land, all of them are using the same operating system. Right?

You cannot find a direct comp anywhere. It's not in the U.S. To our knowledge, just for the operating system alone, we believe that in the U.S. about 200-300 companies, SaaS companies, provide different systems to different regions, different dealers. Right?

They're very siloed and very separated or segregated, but somehow we had this amazing opportunity in China to leapfrog and to be persistent, and to eventually have the whole market on our system. If you ask me who's my comp, it's a very difficult question because in the car commerce industry, we don't see anyone else in the world. This is one of a kind situation.

If you talk about business model, we do believe, and on the advice of our investment bankers, that our business model is actually quite comparable to several very established companies such as Shopify or smaller ones like Toast or ServiceTitan. In a sense that we're in completely different industries, but the structure of the business model shares some similarity that we all started out being the operating system provider. Right? Shopify provides operating system for small merchants worldwide, pan-industry, right? It is an operating system.

On top of that, it started providing layers of different types of transaction services. If you look at their financial history, you will see that in the very beginning, I think, the operating system generated most of their revenues. That's very different from us because it's very difficult to generate revenue from SaaS in this particular economy. Over time, though, their merchant solutions contributed more revenue after a while. If you just look at the structure of the business model, we do share similarities with these companies.

Got it. Thank you very much.

Okay. Thanks, Ella. Our next question is going to come from James Kisner of Water Tower Research.

Hi. Thanks for taking my questions. Really love the leaning into AI, so congrats on that. It sounds like you are really making a lot of early progress there. I guess maybe just stepping back, can you just talk about the next few years, just what you think the biggest drivers of revenue growth are. Maybe you can rank them if possible, like what is the most promising? What do you think is the highest impact?

Yeah. It definitely will come from transaction services, because that is where nearly all of our revenues should come from, and it is an amazing place because it is volume-driven, right? In a sense, it is like a stock market's or an exchange's business model. Like this past six months, the industry was facing so much pressure, and some dealers do go out of business, but the total volume was going up, right? It is like the stock market. Some people will make money, some people will lose money, and certain stocks will go up, and certain stocks will go down.

Just like the cars, some of them will keep their value very well, some of them will lose their value very quickly. Where do we monetize? We monetize from the transactions. Can these transactions be skipped? That is the ultimate question, and the answer is generally no. Because if any of you, if you are interested, please go look at our prospectus.

We have a very nice arrow, I personally drew that page, that shows the 10 steps of a used car's transaction process. Just from the beginning, locating the car to pricing it, to buying it, to inspecting it, pricing it, buying it, moving it, and then cleaning it, and then photograph it, and then price it again for sale, and then go market it, and eventually sell it.

This is a long process, and regardless of which market you are in or whether the car is powered by gas or electricity or solar, the whole process doesn't actually change. Back to your questions. Our revenue will most likely come from the transaction services along the way. It is essentially, in a way, indispensable.

Especially for B2B matching in a market like China, 80%, anywhere between 80%-90% of a used car dealer's cars came from another used car dealer. It doesn't directly come from a consumer. There is a very vibrant transaction community there, a market there. Then at the very tail end, when a consumer buys a car, the used car dealer kind of functions as the one and only, and the most important router for the financial institutions.

Because only the used car and the consumer, those two people know that, oh, there is a need for a loan. The used car dealer is the router, and then he gets to route this demand to whoever pays him the right channel fee, service fee.

There are, along the way, there are naturally these places where as an industry vertical, digital, and internet company, with all the data and the connections and the AI capabilities, we can go in and kind of just reform and benefit from upgrading the whole process. That's one. Two, another revenue generator. This might be a little too premature to share, but we do believe that the third AI application or the industry-wide, the platform-wide agent could present some pretty significant revenue source for us. I say that with a caveat because it is still premature. We will share more when we have more.

Okay. That's fair. It seems like you have had some sort of extra special items, some favorable OPEX savings. Can you kind of give us a little more detail on what's driving that? I assume it is not agentic, but is it just very broad, sort of cost-focused? Was there headcount reduction? How are you doing that? Maybe talk too about incremental kind of margin on revenue going forward if not [crosstalk].

Sorry, I did not catch the first part of your question. Were you asking about the CapEx? Sorry, the OPEX?

Yes. I believe you said you had some good cost control, and I just wondered if you could provide more detail on how you are achieving that, and what kind of incremental margin you might see on revenue going forward. Perhaps what kind of leverage there might be in the model as revenue growth.

Okay. Two parts, right? The first part, the OPEX reduction. Nearly all of our expenses are people, just salaries and wages and commissions, nearly all of them. We do have cloud expenses and de minimis rental expenses and all of that, but the absolute bulk of our expenses are just people. Right? That raises the question of how efficiently we are running our business. How lean and how efficient the organization is, right? That is where we put the AI application focus on because people collaborate with each other.

There could be 10 people completing something, along a long process. Or, with the right AI application help, you can reduce that to two, and even faster and better results. Right? Just to put it more straightforwardly, that is where the, whether it is G&A or sales or R&D, that is where reduction came from.

The second part of your question about revenue growth margin and expectations. I apologize, but we are not prepared to give business outlook yet on this call. Hopefully after we are a new public company, right? After we get the hang of this and get more familiar and comfortable, we will start adopting the business outlook practice going forward.

Okay. Totally appreciate that. One last one I can sneak it in, just on agentic, and just AI adoption in general. What do you think is the biggest barrier to that and to kind of accelerate? Is it model maturity or is it cultural in the dealers? What has to happen for that to kind of take off?

For what to take off?

Artificial intelligence and agentic adoption amongst your customers.

Ah, good question. We have the data, and we have all those wonderful models we can access. How fast can we go? I would put it on user acceptance, right? Even with some of our already deployed agents, we have to give it in stages, right? Because everything happens so fast. Even for some of the products we gave to our dealers, we have to give them a half-stage product first for them to know what's going on and what is behind this. Oh, so this is the incremental version, and then we can move to the next stage. To answer your question, I think it's still the acceptance pace.

Great. Thank you for taking my questions.

Yeah. Thank you, James.

Okay. If there are any other questions, please use the raise hand function and we will call on you. We will give a couple of seconds to see if we have any others. Also, there is the Q&A box to type in a question if you have anything you want to put there. Okay. It looks like we are done. I do not see any-

Yeah.

-other questions. Let me just conclude. I want to thank everyone for participating in today's webcast. Replays of both the Chinese and English sessions with transcripts are going to be posted on the IR section of our website pretty soon. If you have any other further questions, please contact the IR team by email. We also invite you to join any of the investor events that we have, which will always be listed on the IR section of our website. This concludes the webcast, and everyone may now disconnect.

Thank you. Thanks, everyone. Okay. Bye-bye.