Good day and thank you for standing by. Welcome to the C3 AI's Third Quarter Fiscal Year 2024 Conference Call. At this time, all participants are in a listen-only mode. After the speakers' presentation, there will be a question-and-answer session. [Operator Instructions] Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Amit Berry. Please go ahead.

Good afternoon and welcome to C3 AI's Earnings Call for the Third Quarter of Fiscal Year 2024, which ended on January 31st, 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, Juho Parkkinen, Chief Financial Officer, and Hitesh Lath, Chief Accounting Officer. After the market closed today, we issued a press release with details regarding our third 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 our 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 time, 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 joining our call today. C3 AI had a great third quarter. Total revenue of $78.4 million grew 18% year-over-year, exceeding the high end of our guidance range. The total number of customer engagements was 445, an increase of 80% compared to 247 a year ago. Subscription revenue was $70.4 million, constituting 90% of total revenue and increasing 23% from a year ago. Non-GAAP gross profit was $54.7 million, representing a 70% gross margin. Our GAAP operating loss was $82.5 million. Our non-GAAP operating loss was $25.8 million. Better than our guidance for a loss of $40 million to $46 million. Our non-GAAP net loss per share was $0.13. We ended the quarter with $723.3 million in cash, cash equivalents and investments. All these numbers exceeded our guidance and exceeded analysts' consensus. This is the 13th consecutive quarter as a public company in which we have met or exceeded our revenue guidance range. None of this should have come as a surprise. The enterprise AI market is on fire. We have been predicting for some years that the market for enterprise AI would be quite large. Those predictions were subject to much speculation in the analyst community and media. As of February 2024, I believe it's broadly resolved that the enterprise AI market opportunity is substantially larger than anyone predicted, constituting a secular change in the composition and growth rate of enterprise software writ large. Cloud infrastructure is scaling rapidly, NVIDIA grew 265% year-over-year. NVIDIA's data center GPU sales grew by 409% year-over-year. Now, some believe that this capacity is being built to use LLMs to write Christmas cards in the style of Charles Dickens and write college application essays to Yale. But that's simply not the case. This capacity is…

Thank you, Tom. I will now provide a recap of our Q3 financial results and some additional color on pilot activity. Then I'll discuss factors that would drive our financials in Q4 and in FY'25. All figures are non-GAAP unless otherwise noted. Total revenue for the third quarter increased 17.6% year-over-year to $78.4 million. Subscription revenue increased 23.4% year-over-year to $70.4 million and represented 89.8% of total revenue. Professional services revenue was 8.0 million and represented 10.2% of total revenue. Gross profit for the third quarter was 54.7 million and gross margin was 69.7%. 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 lifecycle. Also, as we discussed last quarter, We expect short-term pressure on an operating margin due to the investments we're making in generative AI and upgrading customers to our platform version 8.3. Operating loss for the quarter was negative 25.8 million compared to our guidance range of negative 40 million to negative 46 million. The improvement in operating loss versus guidance was driven by our team's ongoing focus on disciplined expense management, as well as the timing of additional investments we're making to capture market share. At the end of Q3, our accounts receivable balance was 173.5 million, including unbilled receivables of 102.6 million. Total allowance for bad debt remains low at 400,000, and we have no concerns regarding collections. The general health of our accounts receivable remains strong. Six quarters ago, we announced a transition from subscription-based pricing to consumption-based pricing, a standard in the industry. We anticipated and announced that this transition would have a short to medium term negative effect upon revenue growth and RPO as the average sales price…

Thank you, Juho. I have been here at C3 AI for about three months. And I'm very excited to take on this role. These are great times for AI and for C3 AI. And I look forward to working with Tom and rest of the executive team and be a part of the growth story. With that I'd like to hand it over to the operator for Q&A.

Thank you. [Operator Instructions] Please stand by while we compile the Q&A roster. And our first question comes from Timothy Horan of Oppenheimer.

Thanks guys. Could you give us a little bit more metrics on the productivity improvements your customers are seeing or success stories and where is generative AI adding the most value to AI as you see it now? Thanks.

Timothy, hi, it's Tom. Thanks for the question. I would, to the extent that you have time, either you or one of your associates, dial in next week to our users group conference. Because our customers are going to say what the productivity increases they're getting are. Michelle has stood up and said they're getting $2 billion in economic benefit. The United States Air Force, who will be presenting, has stood up and said that they're getting a 25% increase in aircraft availability from our predictive maintenance application that's deployed as a standard in the Air Force. So that's 25% increase in capability in the United States Air Force is a lot of capability. So, you know, those are two examples. Generative AI can be this, there's just no telling where this goes. Whether it's sitting on top of Workday, sitting on top of ServiceNow, sitting on top of SAP, sitting on top of Salesforce, writing contracts for lawyers, you know, the work we're doing at DLA Piper. I mean, one of the applications they're going to see, like, you know, for those of you that tune into our user group conference, they'll talk about the RSO application. This is the application, this is one of the largest AI applications on earth, deployed at the United States Air Force. And now we're putting, and this is, we fused the data from 22 weapon systems into a unified federated image, F-15, F-16, F-18, F-35, KC-135, et cetera, and including the telemetry from many of these devices. And a B-1 bomber has 42,000 sensors, and many telemetry at something like 8 hertz cycles. So there's a lot of data. I think it's an order of 100 terabytes of data. And like any application of this nature, it has a highly technical interface. When we put generative AI on top of it, it has a mosaic browser user interface. The mosaic browser, you guys know that, is basically the Google browser. Google copied it. And the mosaic browser came out of University of Illinois, I think in 1993. So now you simply, anybody in the Air Force with the proper authority can ask any question about any weapon system or any weapon systems and immediately get the answer. What have I rounded up levels for F-35 squadrons in central Europe? What's my cost of running the B1B program in each of the last five years? What are my biggest parts issues associated with the F-35 project? Whatever it may be. So it really is, as it relates to the, as we deploy these enterprise AI applications in mass across organizations, it provides a user interface, it makes the change management process much simpler. So these are examples in both of those areas. And I don't know how big this generative AI thing is, but it's bigger than a bed box, I can tell you that.

Thank you.

Thank you. One moment for our next question. And our next question comes from Sanjit Singh of Morgan Stanley.

Thank you for taking the questions. And sorry, Juho, to see you go and best of luck spending time with the family. Tom, I wanted to ask a little bit about retrieval of augmented generation. It seems like that's an AI access pattern that's getting really, really popular across enterprises and across AI companies. And so there's a lot of companies sort of pursuing this opportunity. I wanted to hear a little bit about how C3 is sort of differentiated in terms of providing this capability to enterprises, you know, that sort of differentiates RAG from C3 versus some of the other players that are trying to make this a reality for customers.

Sanjit, enterprise AI in general or specifically generative AI?

Generative AI, but specifically about the retrieval of augmented generation, like RAG being. It seems like one of these use cases has catching fire with enterprises and just wanted to see like how C3 is allowing customers to pursue RAG use cases.

Okay. Well RAG usually, what we're referring to is a technology that allows the answer to be traceable. Okay, it allows you to do, so when you ask the question, it tells you where the answer comes from. And most large language models will not do that. The C3 generative, by combining 15 years' worth of platform architecture with the large language model, we're able to solve the generative AI equation in a highly differentiated manner. The C3 AI generative AI, when we simply generate, all the answers are deterministic, not random. That means every time you ask the same question, you get the same answer. Go on to Bard or go on to ChatGPT. It doesn't work that way. Every time you ask the same, if two people ask the same question, you get different answers. Secondly, everything that we do is traceable. And this is where we use a RAG, retrieval augmented generation technology so we know exactly where the answer came from. And most large language model will not do that, okay, because we have the temperatures turned down to zero, okay, we don't hallucinate. If it doesn't know the answer, it doesn't tell you where the answer is. Most of these other solutions are unimodal. You know that. They can put anything you want as long as you put in text. That's not useful. Now they're thinking about multimodal. Multimodal if you ask Andrew Ng means text plus images. That's not that useful either. If we're going to do generative AI for example on the airport application, it needs to be omni-modal. Text, images, graphics, enterprise data, telemetry, voice, signals, what have you. And so we're omnimodal. Almost all of these other LLM solutions, whether they come from OpenAI or Anthropic or Google or whoever they…

That's a super comprehensive answer, Tom. I'm really looking forward to watching some of those sessions at a C3 transform on next week.

And there is a mention specifically on that with Nathaniel Christian, who you know, James Lawrence from RSO, and Rowan Curran from Forrester Research on exactly that. And at 9. 15 on March 6th, I highly recommend it.

Perfect. I did have one follow-up, and it goes to some of the color that you provided on, the customers coming out of pilot and how they are choosing to license going forward. And so with the kind of more of a shift or more of a preference I guess for kind of subscription contracts, so what is that imply for like quarterly revenue over the next couple of quarters? Because we've been trying to think that there might be a headwind as customers move to consumption contracts and consumption will eventually grow and that becomes revenue accretive. So now with this mixed shift directionally how can I think about that impacting quarterly revenue? That trend continues from here on going forward.

Let's see, I'm trying to find a headwind in either of these stories. Okay, sometimes you'll have to like, offline, tell me where the headwind is. The bottom line is the customer has the option of licensing it, completely by it, say, okay, we'll take it month to month and we'll pay for the you know CPU hour, okay, or many of them, you know, want to deal with price certainty because they plan on expanding in a pretty big way and they say, hey guys, let's talk about a three-year commitment. We're going to make a certain amount of money in year one, year two, year three and there's a consumption pricing component. Now, the bottom line is, Sanjit, it's revenue neutral to us over 10 quarters. So it doesn't matter. And our business is to win the customer service business. However the customer wants to buy it, we're going to sell it. But it has really no meaningful impact on our revenue modeling. But it did come as a surprise. It's counterintuitive.

Yeah, that's great. I'll leave it there and give the floor to other analysts. Thank you so much, Tom.

Thank you. One moment for our next question. And our next question comes from Pat Walravens of JMP Securities.

Oh, great. I'd like to start with one sort of financial one and then Tom, I have a big picture one for you. So, Juho, maybe on your way out. I mean, this is your Q3, next quarter's Q4, and then you're going to give us some guidance for fiscal '25 just to keep us all in check, you know, a quarter ahead of it. Yeah, let's not get ahead of ourselves. Can we just get some sense of what, you know, some boundaries in terms of what we should think about for fiscal '25?

Pat, thanks, first of all for that question. But I mean, we're still planning for FY'25. I mean, we think the opportunity is massive. We're very excited about the generative AI opportunity, but it's too early for us to give you any sort of guidance as to what the FY'25 revenues look like. We are confident on free cash flow positivity for '25, however.

Okay, that's helpful. All right. Then Tom, the big one for you is, I'm just wondering about the sort of, I think, future demand curve for, you know, nation-states sovereign clouds, that sort of thing. I had breakfast with another AI executive this week, and one of the comments he made was, if you don't have access, if you don't have your own committed access to AI in country, you are dead. So, is he overstating the case, or is this another area where there's potentially a lot of work for you guys to do?

Who's you? You don't have access.

Pick whatever. Pick the Prime Minister or President of any of our allies.

Well, I think France, Germany, and the UK, we do have sovereign access. So we're not finding this a problem, data sovereignty a problem, because one or more of the cloud providers does guarantee data sovereignty. I think actually the interesting trend, Pat, that we're seeing, and this is really counterintuitive, I think we're going to see the return of in-house data centers. I think this, like what HP is leading with what do they call it? Green grass, greenhouse, with these super computers that'll be inside of Goldman Sachs and Bank of America and other firms. I think we're going to see a return to in-house data centers, believe it or not, where people have the GPUs inside. But data sovereignty is not a difficult problem to solve, and we're able to address it. We have customers all over the world. And I believe it's a level zero requirement and the -- our friends at Azure and AWS in particular do kind of nail that quite well.

Okay. Can I go a little deeper on your comment about why we're returning to in-house data centers?

Why do I think that?

Yeah, well what are you seeing that's driving that?

I'm hearing this in the marketplace and even my engineers have talked about it. Okay, that it's going to be cost effective for us to build. Now, the constraint is that you'd think, well, somebody needs to call up Jensen and beg for GPUs. Let's say we can figure out how to do that. Maybe we know somebody who knows Jensen. Okay, the hard part is we can't get power. So I think the constraint on this going for everybody sees with the constraint is availability of GPUs. I think it's straight on this soon is going to be the availability of power. You cannot get power to build the data center in Silicon Valley. You know this, right? Northern Silicon Valley is PG&E, which is, I have no comment on that. And Southern Silicon Valley is some other power company. I know not what, but they will not give you power for a data center. So I think this GPU constraint is ephemeral as soon as it's going to be power.

All right. Awesome. Thank you.

Thank you. One moment for our next question. And our next question comes from Mike Cikos of Needham & Company.

Great. Thanks, guys. This is Matt [indiscernible] on for Mike Cikos over at Needham. Good to hear that the consumption transition is tracking in line with your initial target. On that note, what can you tell us about the size of your sales force, the ramping of these reps, and the number of pilots being signed per sales rep relative to your expectations.

Hi, Matt. This is Juho. So, the sales, we are still hiring actively in all of our sales functions, but not as fast as we'd like. So our sales force is not as high as we initially projected when we provided these sort of assumptions, but we continue to ramp up on that. As it becomes to the ramping up the sales force, I think previously we've said that everybody should make some sort of expectations and assumptions in their models until they close their first pilots. But a reasonable assumption would be 1.5, 2 quarters before they get fully ramped up and get going on closing their first pilots. And then, Matt, what was your third question?

Just if anything has changed as far as like how many pilots you're expecting each rep to close. I know that was part of the initial assumptions.

Yeah, once again, we lead with the pilot sales motion. So all the sales reps, when they close new business is expected to lead with a pilot. So we would expect each of the sales guys to bring in at least a pilot a quarter once they're fully ramped up and everything's at scale, but we're not quite yet there.

Okay, great. Thanks for that. And then has the company noted any change in the length of sales cycles this quarter versus the prior quarter given management's comments on customer considerations for AI governance?

I think we published that, did we?

We took it out from the queue. So but the sales cycle is about the same.

It's about the same. It's about the same, Matt. It hasn't changed.

Yeah, which is about 3.5 months.

All right. Beautiful. Thanks so much, guys.

Thank you. One moment for our next question. And our last question comes from Kingsley Crane of Canaccord Genuity.

Great. Thank you for taking the question. I commend you for the great Q3 and really strong momentum in the business. With respect to your comments on NVIDIA and Enterprise AI, I think what we're all trying to figure out is when does NVIDIA's 200 plus percent growth and hardware investments start flowing into the software layer? And we're seeing some of it already, but is that more like one year, five years? I think we see the tidal wave coming, but we're all trying to time it.

Well, you know, Kingsley, it's a good question, you know, but I can tell you all this infrastructure is not being put out there to like play games, okay? It's being put out there to run enterprise AI applications. And so these guys are out there building the highway for us and thank goodness for that. And I think that, you know, we, in terms of, you look at the, I think you're generally aware of the market interest in AI applications and I think you're generally aware maybe more than generally probably specifically aware of the interest in generative AI applications and that's what those GPUs are going to be doing, they're going to be running. And the good news is they'll be there. So it's, you know, there's a lot of things coming into place.

Thank you. That's really helpful. And so last one is just that we're seeing so much investment domestically. You've had such great success both with federal and state and local. How are you doing the international opportunity today, both in Europe and then in regions like APAC?

Well, I disclosed, I think, last quarter that our performance in EMEA was significantly substandard and that was pretty clear about that. And come as a big surprise to everybody on this call that maybe we made some organizational changes. And the, I'm pleased to report that those changes have been quite positive and we're seeing the levels of sales activity and customer engagement increasing dramatically in the EMEA theater and interesting enough the South American theater too. So that thanks for the question and we're seeing you know very positive news there.

That's great. Thank you and Juho it's been fantastic work with you I wish you the best of luck. Thanks again.

Thanks, Kingsley.

Thank you. I would now like to hand it back to Mr. Sebel for closing remarks.

Ladies and gentlemen, thank you for your time this afternoon. We appreciate the opportunity to update you on the state of our business. I can tell you that, you know, for those of you who have visited us, you know this is a very unique place. We have the only full parking lot in Silicon Valley. There are 500 or 600 people here working with us today shoulder to shoulder. They're here Monday through Friday. And we're working in Chicago, Atlanta, Tyson, Washington DC, London, Rome, Paris. We're all at it. We have a very unique high performance corporate culture that I think is going to serve as a real strong competitive advantage in the long run. So this place is just kind of vibrating with excitement. And I think for all of us involved, it's the professional experience of a lifetime. And we thank you for the opportunity to share it with you. And we look forward to bringing you up to speed next quarter. And let me just last thought, for those of you who have time, I really encourage you to dial into C3 Transform next week because I think you'll find it these are professional presentations that are quite substantive and it will be a good use of your time if you have time. Ladies and gentlemen, thank you very much and we look forward to talking again soon.

This concludes today's conference call. Thank you for participating and you may now disconnect.