C3.ai, Inc. Q4 FY2024 Earnings Call

Good afternoon and welcome to C3.ai's earnings call for the fourth quarter fiscal year 2024, which ended on April 30th 2024. My name is Amit Berry, and I lead Investor Relations at C3.ai. With me on the call today is Tom Siebel, Chairman and Chief Executive Officer, and Hitesh Lath, Chief Financial Officer. After the market closed today, we issued a press release with details regarding our fourth quarter results as well as a supplemental to our results, both of which can be accessed through the Investor Relations section of our website at ir.c3.ai. This call is being webcast and a replay will be available on our IR website following the conclusion of the call. During today's call, we will make statements related to the business that may be considered forward-looking under federal securities laws. These statements reflect our views only as of today and should not be considered representative of our views as of any subsequent date. We disclaim any obligation to update any forward-looking statements or outlook. These statements are subject to a variety of risks and uncertainties that could cause actual results to differ materially from expectations. For a further discussion on material risks and other important factors that could affect our actual results, please refer to our filings with the SEC. All figures will be discussed on a non-GAAP basis unless otherwise noted. Also, during today's call, we will refer to certain non-GAAP financial measures. A reconciliation of GAAP to non-GAAP measures is included in our press release. Finally, at times in our prepared remarks, in response to your questions, we may discuss metrics that are incremental to our usual presentation to give greater insight into the dynamics of our business or our quarterly results. Please be advised that we may or may not continue to provide this additional detail in the future. And with that, let me turn the call over to Tom.

Thank you, Amit. Good afternoon, everyone, and thank you for being with us today. Hitesh and I are excited to share our results for the fourth quarter and the full fiscal year of 2024. Q4 was remarkable and capped off an incredible year for C3 AI. We surpassed all expectations for revenue, cash flow, and profitability. To be clear, there were no targets that we fell short of. This marks our fifth consecutive quarter of accelerating revenue growth. Our year-over-year growth rate for revenues has increased from 11% in Q1 to 17% in Q2, 18% in Q3, and now 20% in Q4 of fiscal year '24. Our subscription revenue growth has also significantly increased, rising from 8% in Q1 to 12% in Q2, 23% in Q3, and 41% in Q4 year-over-year. We wrapped up the quarter with $86.6 million in revenue, surpassing both our guidance and analyst expectations. This achievement marks the 14th consecutive quarter as a public company where we've met or exceeded our revenue targets. For the quarter, subscription revenue was $79.9 million, constituting 92% of total revenue, which is a 41% increase year-over-year. Our non-GAAP gross profit reached $60.9 million, yielding a 70% gross margin. Our GAAP operating loss stood at $82.3 million, while our non-GAAP operating loss was $23.4 million, which is better than our guidance range of $43.5 million to $51.5 million. Our non-GAAP net loss per share was $0.11. We produced a free cash flow of $18.8 million, concluding the quarter with $750.4 million in cash, cash equivalents, and investments, again surpassing analyst consensus. Full-year results also exceeded both our high-end guidance and analyst expectations, with record revenue of $310.6 million, a 16% increase compared to last year. Subscription revenue hit $278.1 million, a 21% increase over the previous year. With our shift to pay-as-you-go consumption pricing, we’re engaging in a larger number of smaller, shorter transactions, providing us with better revenue visibility and predictability. Our average total contract value has decreased from over $16 million in fiscal year '19 to $900,000 last quarter. As we transition our pricing model, we're seeing an expected decline followed by a return to accelerating revenue growth. We also anticipate a reduction in remaining performance obligations and expect this trend to continue in the next few quarters as we project revenue growth. This shift is mathematically certain due to our go-to-market model change, making me uncertain about the validity of RPO as a leading indicator of our business in the near term. Now, regarding the AI value stack, there's currently a market frenzy around AI infrastructure. At the bottom you have silicon, followed by infrastructure, then foundation models, and at the top, enterprise AI applications. C3 AI operates at the top of this stack, focusing solely on enterprise AI applications. We believe that over time, silicon and infrastructure will become commoditized while AI applications will come to dominate the value stack. If we consider the early personal computer market, the most value initially lay in the silicon and infrastructure. For example, in 1983, the IBM PC/XT was priced at $7,900, which would be about $22,000 today. In contrast, the software typically cost only $200 to $300. Today’s desk PC depreciates at around $200 per year for hardware and another $200 for infrastructure, but the applications running on it can total over $8,000 annually. The situation with AI will be similar, where the bulk of value is attributed to applications that leverage the entire AI stack and deliver value to businesses. Silicon will inevitably get commoditized. Infrastructure will also get commoditized. However, over the long term, applications won’t be commoditized, and this is where C3 AI is positioned. Looking at market dynamics in AI, while some companies face headwinds, we are benefitting from favorable conditions. Our main competitor is whether to build or buy AI applications. For enterprises, developing such applications is extremely challenging. Most CIOs are currently overwhelmed with issues like single sign-on installations and managing delayed, over-budget SAP upgrades. Building enterprise-scale application software is not what they are equipped to do. Many companies are stuck in trivial AI projects or rely on contractors for piecemeal solutions that ultimately fail. Enterprises don’t want tools to create applications; they want ready-to-use applications. This has been proven in the relational database, ERP, and CRM markets. At C3 AI, we’ve invested 15 years and billions in software engineering to develop a robust AI platform supporting some of the largest enterprise AI deployments globally, starting this journey in 2009 before Enterprise AI was a recognized term. We currently offer 90 Enterprise AI and Generative AI applications that deliver substantial economic benefits. In fiscal year '24, 88% of our bookings were related to AI application sales, while 12% were attributed to the C3 AI platform. Our annual pilot count surged to 123, with 191 agreements now spanning 19 different industries, demonstrating the effectiveness of our products in addressing various business complexities. In Q4, our bookings breakdown was about 50% Federal, defense, and aerospace; 15% oil and gas; 11% state government; 7% manufacturing; 6% energy and utilities; 5% consumer packaged goods; and 5% professional services. This growing diversity in bookings could indicate future trends for C3 AI. Our pilot distribution during Q4 was 29% manufacturing, 21% federal, defense, and aerospace, 12% agriculture, 9% chemicals, 6% life sciences, 6% oil and gas, 6% state and local, 6% energy and utilities, and 3% logistics and transportation, reflecting a promising future direction for the company. Now, let me provide a quick update on our recent product advancements. First, Version 8 of our platform and applications results in a significant enhancement in speed, efficiency, and overall performance. With Version 8, data ingestion, training of machine learning models, and time series feature inference are now over 20 times faster. Customers can run thousands of applications within a single C3 AI platform cluster for high scalability. The C3 AI Community is our interactive and collaborative ecosystem for developers and data scientists worldwide. This year, we enhanced the C3 AI community with the C3 Generative AI co-pilot, which instantly answers questions and generates code to significantly boost developer productivity. In terms of customer traction, we are seeing increased engagement among our clients. Cargill has expanded its operations from 13 to 18 production plants in the last year. Baker Hughes's sourcing optimization has been deployed across 855 sites and three business segments, engaging 2,000 users with potential savings of $100 million annually. C3 AI reliability is in action at 12 Petronas plants, overseeing 4,000 control valves and achieving $25 million a year in avoided losses. Dow has enhanced its predictive maintenance capabilities using C3 AI reliability, forecasting a 20% reduction in downtime for steam cracking furnaces. Holcim, a significant player in European construction products, started with C3 AI reliability production pilot in May 2023 and now operates 31 facilities, running over 200 machine learning models to monitor 3,000 sensors from essential equipment. Roze Wesby, Head of Plants of Tomorrow at Holcim, remarked that C3 AI is instrumental in their digital transformation, providing innovative AI solutions that enhance efficiency and sustainability. Con Edison, a C3 AI customer since 2017, utilizes the platform to improve various aspects like operational efficiency, public safety, billing performance, and customer satisfaction. Tom Magee, general manager for Con Edison’s advanced metering infrastructure project, shared that their AMI project, the largest in their history, involved deploying 5.3 million smart meters, resulting in significant benefits like improved outage management and energy efficiency. C3 AI's contributions have notably enhanced public safety and optimized grid operations, achieving substantial energy savings and emission reductions. We also saw a significant uptick in the US federal market, closing a remarkable year with revenue surpassing 100% growth in 2024. Our transactions in this vertical are increasing, making it a crucial growth engine for C3 AI. Last year, we secured 65 agreements with federal agencies, including 13 new and expanded agreements in Q4 with organizations such as the US Air Force, US Navy, and the US Intelligence Community. Our expertise in predictive maintenance is evident through our work with the US Air Force, which is broadening its C3 AI-related capabilities for predictive analytics across various weapon systems. This system, known as Panda, is the official platform for all predictive maintenance initiatives, enhancing fleet maintenance and aircraft availability. Jimmy Lawrence, Deputy Program Executive Officer for the Rapid Sustainment Office, stated that C3 AI's cutting-edge technology has significantly advanced predictive analytics and maintenance for the US Air Force. In partnership news, our partners are crucial to our growth and customer success. Last year, we closed 115 agreements through our network, a 62% year-on-year increase, including 91 agreements with AWS, Google Cloud, and Azure. Our joint 12-month qualified pipeline with partners saw a 63% year-over-year growth. Our collaboration with Google Cloud has intensified, culminating in 12 pilots with them during Q4. Support from GCP is immense for pursuing state and local pilots, with Google committing to significant investment in the first quarter. Additionally, we have expanded partnerships with Fractal and Paradyme for professional services related to our Version 8 upgrades and pilot deliveries, with plans to train over 200 qualified engineers and data scientists this coming year. Moving on to C3 Generative AI, we are experiencing tremendous opportunity and demand for our products. In fiscal year '24, we launched 30 Generative AI products and are seeing overwhelming interest. In Q4 alone, we received nearly 50,000 inquiries from 3,000 businesses, each generating over $500 million in revenue, all interested in our Generative AI applications. We expect this to rise to 90,000 inquiries in the first quarter of '25. C3 Generative AI has been piloted across 15 different industries, propelling our entry into new markets. The industries engaged include 21% Federal, Defense, and Aerospace; 12% Manufacturing; 10% Agriculture; 10% State and Local Government; 7% Financial Services; and more. C3 Generative AI is distinguished in the market by offering safe, secure, reliable information across enterprises while enabling retrieval and reasoning from diverse data types with deterministic, traceable responses. It incorporates robust enterprise controls, reducing cybersecurity risks and minimizing hallucination risks. In summary, we understand the long-term nature of building a significant enterprise AI software company. While market moods fluctuate based on inflation and demand for immediate profitability, we are focused on a long-term vision. Notably, it took Apple over 25 years and Amazon 29 years to achieve consistent profitability, creating substantial investor value. C3 AI aims to target a $1 trillion addressable software market, potentially the largest in software history. Since raising $1 billion in December 2020, our investments have been carefully considered, supporting growth, technology leadership, brand leadership, and market leadership. We anticipate additional revenue acceleration to approximately 23% in fiscal year '25 while continuing to invest in growth to secure and extend our market leadership. Our revenue guidance for Q1 of fiscal year '25 is set between $84 million and $90 million, and for the full fiscal year, we're looking at $370 million to $395 million. We expect our non-GAAP operating loss for Q1 to be between $22 million and $30 million, with a total annual loss projected at $125 million to $95 million. I will now hand the call over to Hitesh for further details.

Thank you, Tom. I will now provide a recap of our financial results and additional color on our business. All figures are non-GAAP unless otherwise noted. As Tom mentioned, total revenue for the fourth quarter increased 20% year-over-year to $86.6 million. Subscription revenue increased 41% year-over-year to $79.9 million, representing 92% of total revenue. Professional services revenue was $6.7 million. This represented 8% of total revenue in the fourth quarter of fiscal '24 as compared to 21.5% of total revenue in the fourth quarter of fiscal '23, demonstrating an improved mix of subscription revenue. Gross profit for the fourth quarter was $60.9 million, and gross margin was 70%. Gross margin for Professional services was higher this quarter due to a greater mix of higher margin Professional services like prioritized engineering services. Operating loss for the quarter was $23.4 million. Our operating loss was lower than guidance due to continued focus on expense management as well as the timing of additional investments we are making to capture market share. As we discussed last quarter, we expected fourth quarter free cash flow to be positive. Free cash flow for the quarter was $18.8 million. We continue to be very well-capitalized and closed the quarter with $750.4 million in cash, cash equivalents, and marketable securities. Please note that the Professional services mix in our revenue depends upon the nature and size of revenue deals in any given quarter. However, we expect the Professional services revenue to generally stay within 10% to 20% of total revenue. As a reminder, we continue to expect short-term pressure on our gross margins due to higher mix of pilots, which carry a greater cost of revenue during the pilot phase of the customer life cycle. We also expect short-term pressure on our operating margin due to additional investments we are making in our business, including in our sales force, research and development, and marketing spend. At the end of Q4, our accounts receivable balance was $130 million, including unbilled receivables of $62.3 million. Total allowance for bad debt remains low at less than $400,000, and we do not have concerns regarding collections. The general health of our accounts receivables remains strong. During the fourth quarter, we signed 34 pilots, a 79% increase from last year and up 17% from last quarter. At quarter end, we had cumulatively signed 172 pilots, of which 157 are still active. This means they are either in their original three to six-month term or extended for some duration, converted to a subscription or consumption contract, or are currently being negotiated for conversion to subscription or consumption contract. Seven quarters ago, we announced the transition from subscription-based pricing to consumption-based pricing, a standard in the industry. We also announced that this transition would have a short to medium-term negative effect on revenue growth. Accordingly, our GAAP RPO at the end of Q4 was $244.3 million, which is down 36% from last year. And our current GAAP RPO was $163.8 million, which is down 12% from last year. Now, I would like to turn the call over to the operator to begin the Q&A session.

And our first question will come from Timothy Horan with Oppenheimer. Your line is open.

Thanks, guys. Congratulations. Can you talk a little bit about how you got the 20-fold increase in improvements in Version 8? And how sustainable are those types of improvements? How long did that take to achieve? And then, secondly, obviously, the sales inquiries are off the charts. I mean, how scalable are these inquiries at this point? Both, I guess, to deal with the sales operations and the implementation of these inquiries. Thank you.

Hi, it's Tom. Version 8 was a significant engineering project that took four years to complete. We essentially rebuilt the product from the ground up, making it a major release with extensive changes. It's difficult to cover all the details, but we were fully engaged in this effort for four years, resulting in a substantial architectural overhaul. We won't see performance improvements of this magnitude again for some time. As for sales inquiries, the response to Generative AI has been overwhelming. We reached 10,500 inquiries in February and nearly 50,000 last quarter. Currently, we believe we can handle about 90,000 inquiries per quarter. As for sustainability, it's uncertain if this level of interest will continue, but the Generative AI market seems to be expanding continuously, presenting a significant opportunity for us. It's also important to highlight that we have a product that stands out in this space, as we've addressed issues like hallucination, IP liability, access controls, and stochastic responses by combining the learning models with the capabilities of the C3 AI platform.

Thank you.

Thank you. One moment for our next question. And that will come from the line of Pat Walravens with JMP Securities. Your line is open.

Great. Thank you and congratulations. It's really impressive. So, I mean, 50% of bookings, Tom, from Federal, Defense and Aerospace, if you could drill into that more and talk about what you see for the pipeline for that vertical for this coming year, that would be great.

Federal appears to be a significant growth contributor. Business is thriving, and we have made substantial progress within the Air Force, Navy, and Intelligence Community. We are making large investments in the Federal sector, which is also heavily investing in AI. This situation has become crucial, as there is a competitive landscape surrounding AI between the United States and China, and we are aligned with the positive side of this effort. The scale of this opportunity is unclear, but it is considerable.

Yeah. As a follow-up on that, what partnerships with AWS, Microsoft, Google, and Booz Allen are yielding the most results in the Federal sector?

AWS is undoubtedly the company with the greatest presence in the Federal sector, and I would estimate that about 11 out of 12 of our applications are operating on the AWS GovCloud. Our connections with the AWS Federal group and the International Federal Group, which engages with allies like NATO and the Five Eyes, are very strong. In terms of hyperscalers, this is where we are seeing the most activity, and AWS remains the leading platform in terms of installations.

All right, great. Thanks. And congratulations again.

Thank you.

Thank you. One moment for our next question. And that will come from the line of Sanjit Singh with Morgan Stanley. Your line is open.

Thank you for taking the questions and congratulations on a strong close to the year. Tom, I would like to hear your favorite example of a customer that has come out of the Gen AI C3 pilot program and the role that C3 AI played in getting them into production. There seems to be a clear debate in the industry regarding whether many of these projects are experimental and if they can actually transition to production. It appears that your company is successfully helping customers move into production. Could you share one of the 58 pilots you signed this year that stands out and illustrates how C3 AI assists its customers in achieving production readiness for Gen AI use cases?

It's very interesting. They're incredibly diverse. For example, there's a well-known large law firm that actively assists companies in going public. We integrated the entire corpus of SEC.gov Edgar into an enterprise learning model. This includes all the S1s, all the 10-Ks, and all the 10-Qs ever published. Their first application of this will be when they take the next company public. They can simply enter the company name and financials, and in an hour, they generate the first draft of the S1 instead of taking two weeks. This approach could also benefit your business. I can have the system ready and operational for $250,000 in 12 weeks. Just reach out to me, and we can get started. Another example is our application called Panda, which we've discussed previously. Here, we've included all the underlying information and telemetry from 22 U.S. Air Force weapon systems, such as the F-15, F-16, F-18, F-35, KC-135, and F-22. This helps us identify potential system and subsystem failures before they occur through predictive maintenance. For instance, we can predict when an auxiliary power unit or flap actuator may fail in the next 50 or 100 flight hours, allowing for repairs to be made in locations like Stuttgart or Munich to prevent aircraft failure. This results in a 20% to 25% increase in aircraft availability within the U.S. Air Force. The user interface is quite tactical, designed for highly skilled maintenance personnel managing sustainment and logistics for the Air Force. The implementation of Generative AI could significantly enhance the human-computer interface for enterprise applications. By incorporating Generative AI, it can operate like a mosaic browser, allowing users to ask questions in English or 131 other languages and receive instant answers. For example, a high-ranking official like the Secretary of Defense could inquire about the readiness levels of F-35 squadrons in Central Europe. Instead of sifting through extensive data, a minute later, they would receive a map indicating the readiness of each squadron and the source of that information, enabling in-depth follow-up immediately. In contrast, obtaining such answers currently takes days to weeks within the Pentagon. The broader consequence of this is that we can shift the use of the application from thousands of highly technical users to tens of thousands. Every pilot on the flight line, and even high-ranking officials, would be able to use this technology effortlessly. The interface would be akin to a Google user experience, accessible to everyone. We're witnessing diverse applications of Generative AI. One of our major customers, with 68,000 employees across numerous countries, decided to implement it atop their HR systems, such as ServiceNow and Workday. This allows any employee, regardless of their location—whether in Dubai, Qatar, Germany, or Houston—to ask questions about HR policies, vacation days, and other benefits. These are just a few examples of how we are leveraging Generative AI as a front-end for various enterprise applications like Workday and ServiceNow. Our offer remains to bring the application to life within 12 weeks for $250,000. If anyone is interested, feel free to reach out via email, and we would be glad to assist your organization.

No, that's great. The breadth of use cases is super compelling. I had one follow-up for Hitesh. As we're coming up on almost two years now on the transition to consumption and you guys are seeing accelerating subscription growth of 41% was a really, really nice number this quarter. What percent of that subscription revenue is now consumption? If you can sort of give us a sense. And is that what's driving that re-acceleration in revenue growth? Thank you so much.

Yeah, Sanjit, we are still in the early stages of our new business model. We haven't disclosed our consumption revenue separately before, but that is something which we continue to see a ramp in and it will be more meaningful in the future.

Thank you. One moment for our next question. And that will come from the line of Kingsley Crane with Canaccord Genuity. Your line is open.

Hi, thanks for taking the question and congrats on the traction. It's encouraging to hear. As we think about how some of the customer engagement metrics will translate to revenue growth, where would the dollar or that incremental dollar of investment be most impactful? Is it deployed sales engineers? Is it partner sales motion? Are you capacity constrained on the application development side? Just want to get a little bit more granular on the investment profile.

Good question, Kingsley. Regarding the concept of a land grab and gaining market share, which we intend to pursue, I would say that we are not limited by the market or competitive dynamics. Our limitations will come from our sales and service capacity to launch these pilots. That's where we need to focus our investment to achieve the greatest impact for each additional dollar. Great question.

Okay, perfect. Thanks for the clarity. And Hitesh, just on the gross margins, understand that we continue to invest, and there's a mix of pilots in there. You did improve in the quarter on the Subscription side, I mean, should we expect that we've already troughed, or is this still sort of we’re feeling it out on a quarter-to-quarter basis?

Yeah. You should expect our gross margins to decline from where they were in Q4 at 70% as we plan to significantly increase the number of pilots and make additional investments.

By the way, I need to correct a mistake I made earlier regarding our revenue guidance for Q1. The correct range is $84 million to $89 million. I mistakenly stated $84 million to $90 million, so I apologize for that error. Next question.

Thank you. One moment. And that will come from the line of Arvind Ramnani with Piper Sandler. Your line is open.

Hi. Thanks for taking my question. I wanted to ask about the high number of inquiries for your product. Do you think that could lead to increased revenue in the next year or two, or are some of those inquiries less qualified, making your guidance more realistic?

I don't have any comments on guidance beyond fiscal year '25. We are currently processing a significant volume of inquiries and using Generative AI to qualify these leads, which has some interesting applications. However, it's still too early to provide guidance for fiscal year '26.

I’m trying to understand how the significant interest in the product will affect your income statement, revenue growth, and margins. With 50,000 inquiries, I want to clarify the implications of this commentary for both growth and margins.

We are encountering a remarkably large addressable market. Our goal is to secure a leading position in this market. The current stock price may be around $20 or $30, but if we succeed in establishing a market leadership position in Enterprise AI applications, it will be valued significantly higher than that. It could be several times that amount, potentially an order of magnitude greater. Of course, there's a risk that we may not succeed and end up in a lower position. You can do the calculations, but I understand that it may not fit neatly into your models. Relying solely on spreadsheets isn't the best approach to assess this opportunity. The potential market is vast, we hold a first-mover advantage, and we have a solid technological foundation, which we are fully leveraging. An accurate way to evaluate our business would be to focus on our revenue projections, as our revenue forecasts have been quite reliable over the past 14 quarters. That's likely the best indicator to consider.

Terrific. And then, if you can maybe just double click on kind of margins. Right? There's some margin degradation by kind of next year because of the number of pilots. How does that work? Like, when you do pilots, do you charge less or do the professional services go up more? Like, what drives lower margins by making a choice?

Good question. Essentially, our market offering today is for an Enterprise application, such as stochastic optimization of supply chains, demand forecasting for large agribusinesses, or predictive maintenance for large manufacturers. We aim to implement that application at a multi-billion dollar corporation in one of their facilities, bringing it live in six months for $0.5 million. The alternative would be to work with firms like Accenture or Deloitte, who might charge $100 million or $30 million over two years to achieve the same result. My goal is to have the application live in just 12 weeks for $0.25 million using Generative AI. We will do everything necessary to ensure that the customer goes live. I don’t focus on the profitability of individual pilots. If I'm working with a Fortune 50 company to launch their first Enterprise AI application, I will invest whatever it takes, even if it involves a loss, to ensure their success. This is what leads to margin degradation. While I'm confident these projects are profitable overall, at any one instance, our priority is to succeed and we have the resources to support that.

Thank you very much.

That's where the margin degradation is coming from. I understand it's difficult to model, but we recognize that this is part of who we are and what we do.

Thank you. One moment for our next question. And that will come from the line of Mike Cikos with Needham & Co. Your line is open.

Hey, guys, this is Matt Calitri on for Mike Cikos over at Needham. Thanks for taking our questions. I wanted to ask how have newly converted customers ramp consumption versus customers who adopted the consumption model in previous quarters? Are you seeing consistency across cohorts?

I'm not sure I understand the question. We provided very specific guidance on that last quarter. In the supplemental last quarter, we detailed what we're observing in revenue consumption from the first quarter of production to the tenth quarter. If I recall correctly, in the first quarter of production, they're using about 300,000 to 400,000 GPU hours. By the tenth quarter, that usage increases to about 1.4 million. To clarify, in the first quarter of production, actual usage was 370,000, ramping up to 1.3 million in the tenth quarter. Our supplemental from last quarter also includes this information.

No, we did not…

Last quarter, we said it was what? 3.5 months. I don't have the hard data before me, Matt, but I don't think it's changed appreciably.

All right, appreciate it.

Thank you. We do have time for one final question, and that will come from the line of Pinjalim Bora with JPMorgan. Your line is open.

Thank you for your question. This is Jaiden Patel filling in for Pinjalim Bora at JPMorgan. I have a brief inquiry. Last quarter, you indicated that you anticipated positive free cash flow for the entire fiscal year '25. I wanted to see if there are any updates on that. Thank you.

As we have the business plan right now, we are expecting positive free cash flow for fiscal year '25.

Great, thanks.

Thank you.

Thank you. I would now like to turn the call back over to Mr. Siebel for any closing remarks.

Thanks, everyone, for your time. I appreciate your continued attention. Please stay tuned. I believe we're just getting started here. Next year is looking promising, and we look forward to keeping you informed about our progress. Thank you for your interest and for following us. Wishing you all a great day, and thanks again for your time.

This concludes today's program. Thank you all for participating. You may now disconnect.