Good day and thank you for standing by. Welcome to the C3.AI's First 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 First Quarter of Fiscal Year 2024, which ended on July 31st, 2023. 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 Juho Parkkinen, Chief Financial Officer. After the market close today, we issued a press release with details regarding our first 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 this 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 the 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 the course of 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 joining our call today. We're off to a strong start for fiscal year '24. Our revenue came in at the high end of our guidance exceeded analyst consensus and we're seeing significant traction across our business. This is the 11th consecutive quarter as a public company in which we have met or exceeded our revenue guidance. Following the release of ChatGPT in November of 2022, we are seeing a dramatic increase in demand for enterprise AI adoption. In Q1, we experienced strong traction with our enterprise AI applications and especially strong traction with C3 Generative AI. Let's take a look at our revenue highlights for the first quarter. Total revenue for the quarter was $72.4 million, coming at the high end of guidance that was $70 million to $72.5 million and exceeding the analyst consensus. Subscription revenue for the quarter was $61.4 million, constituting 85% of total revenue. Gross profit for the quarter was $40.5 million representing a 56% gross margin. Non-GAAP gross profit for the quarter was $49.6 million representing a 69% non-GAAP gross margin. GAAP RPO was $334.6 million. Current RPO was $170.6 million. GAAP net loss per share was $0.56. Our non-GAAP net loss per share was $0.09, both exceeded analyst consensus expectations substantially. We finished the quarter with $809.6 million in cash, cash equivalents, and investments, exceeding the average analyst consensus of $774.3 million. Net cash provided by operating activities was $3.9 million and free cash flow was negative $8.9 million, significantly exceeding analyst consensus that was negative $38.7 million. The market interest in applying enterprise AI to business processes appears to be expanding exponentially, fueled by the interest in ChatGPT and other consumer generative AI tools initially released in late last year. CEOs, business leaders,…

Thank you, Tom. I will now provide a recap of our financial results, some color around the expected drivers of our financial results for the remainder of the year, and walk you through our second quarter and full year fiscal '24 guidance. Finally, I will conclude with some additional information related to the consumption-based revenue model we introduced a year ago. All figures will be discussed on a non-GAAP basis unless otherwise noted. First quarter revenue increased 10.8% year-over-year to $72.4 million, subscription revenue was up 7.6% and represented 85% of total revenues. As we discussed last quarter, we expected professional services to be within our historical range of 10% to 20% with our actual professional services coming in at 15% of the mix. Gross profit for the first quarter was $49.6 million and gross margin was 68.6%. I would like to remind everyone on the call that we expect short-term pressure on our gross margin due to a higher mix of pilots, which carry a higher cost of revenue during the pilot phase of our customer life cycle. We are pleased with our progress in managing expenses and our success in getting the entire employee base bought into a mission of managing our company with expense discipline. Our success in expense management is reflected in our first quarter operating loss of $20.7 million, which was better than our guidance of a loss of $25 million to $30 million. Operating loss margin was 28.6%. As Tom mentioned, the Generative AI opportunity is so massive that we believe it is in the best interest of our company and to shareholders, together it's our first mover advantage to seize the market opportunity by making incremental investments in sales, marketing, and customer success. As a result, we are revising our 2024 expense guidance…

Thank you. [Operator Instructions] Our first question comes from Patrick Walravens with JMP Securities. You may proceed.

Great. Thank you very much. So it's great to hear about the demand levels and all the activity. Tom, can you talk a little bit about how the linearity in the quarter, how that was and how things close out at your investor event, you told us that you had closed 16 agreements. You ended up with 32. But if you look back a quarter, you had 10 at the middle and you ended up with 43%. So it makes it seem like maybe the second half wasn't quite as good as you would have hoped, but I don't know. Maybe I'm interpreting that wrong, too?

Or maybe the first half was great.

Right. Okay.

It's like the half glass flow model. I would say that if the -- this might have been our best quarter ever in terms of linearity. I'm not sure, okay, in terms of being in terms of predictability. So we aren't getting too specific, I would say, the business volume in the course of the quarter was activity in the course of the quarter was quite consistent.

Okay. And then if we multiply the average TCV times the number of deals right then we get a total TCV number, which I mean, you guys are the only ones to disclose it, so thank you for that transparency. And if you look at that, that was around $26 million this quarter, and then last quarter again it was $52 million, almost twice as much. So I just want to make sure we understand what's going on here, is the TCV not a good indication of what you're actually doing in the quarter?

Well, we used to compensate people on TCV, and that's back when we used to do $10 million, $20 million, $30 million, $40 million, $50 million deals, Pat. And now we're doing $250.000 projects in Generative AI and $0.5 million projects in for the balance of our enterprise products. The Generative AI products last 12 weeks, the other pilots last projects last -- generally last up to six months, generally six months. So it's a cost, I mean, it's a sure as -- I mean, it follows directly that TCV goes down, RPO goes down. I mean and by the way, gross margins go down in the short run, okay? Because the gross margin when you -- when we're doing these Generative AI pilots for $0.25 million, wherever it may be, I mean, there is no way we are not going to succeed at any cost, let's say, on the first 50 of these guys. And if we have to overinvest to make that pilot successful, we're going to do it. And so I'm not certain that RPO is meaningful going forward. I'm not certain that in TCV, I've been trying to drive that down as you're well aware, for well, 15, 20 quarters ago, our TCV, I think, was about $15 million. Average contract value, it was about $15 million. And our average contract value, I think, is less than $1 million, right? So that's -- this is a good thing.

Okay, great. And then lastly, Juho, probably for you. You have a footnote on the balance sheet where there is a related party presumably Baker Hughes that still has a $75 million, you saw $75 million in accounts receivable from them, that's the same as last quarter, are you guys okay with that?

It's a lot bigger than $75 million.

No, total. All right. Yes, we are okay with that. I'm not entirely sure how to interpret your question and we have no collection concerns from any of our customers. Our bad debt reserve is only at $359,000 and all of our customers are paying on time and in full, so no concerns there.

Okay, thank you.

Thank you. One moment for questions. Our next question comes from Mike Cikos with Needham. You may proceed.

Hey, I appreciate the new pronunciation of the last name. Thanks for taking the questions here guys. A couple of questions, first on the guidance and I appreciate this pivot you guys are trying to take advantage of this opportunity, where it really feels like the Gen AI has come online, right? I think my question is more around the guidance if you will, and where I'm going with this is, given the increase that we're talking to in the go-to-market investments, which is obviously acting as a drag on your operating losses, no question about it. But why aren't we seeing some sort of benefit when looking at the fiscal '24 revenues? Why maintain that guidance as we sit here today?

Hi, Mike. I think we've been -- we're doing the best we could do since we've been a public company to be credible in setting expectations and we have met or exceeded expectations in every quarter that we've been a public company, okay? Now, we are in unchartered territory still with the consumption pricing model and we're definitely in unchartered territory with Generative AI, okay. Now, let's take, I were to take all the spread sheets of all my product groups and business plans and you can be sure that they come to a larger number than we've talked about in guidance, okay, but we would -- our position is we feel where the guidance we're comfortable with the guidance that's out there today, okay, and at the same time, we feel comfortable that after a couple of quarters of acceleration, we're able to look straight in the eye and say, guys, we're planning on significantly accelerated growth, but I don't want to do it prematurely. I don't want to lose credibility and I think this is the responsible thing to do.

All right. Thank you for asking that out, I appreciate that. And I guess another one, I totally understand the commentary on RPO and even CRPO declining, I guess it's more for Juho here, but with the transition to the consumption model, shouldn't we be seeing CRPO remain more resilient as these consumption pilots starts to convert or are consumption pilots even when they move to production not necessarily going to be showing up in CRPO, can you provide any more color on that, please?

Yeah, absolutely. So effectively the CRPO is flat, right, and the way to consumption-based business model works is that we start with a pilot phase that pilot amount would be RPO in the given quarter that we signed that deal. The consumption phase unless the customer were to sign up for volume discounts is never going to be in RPO, because it's going to be after consumed invoicing, so you only see ever that in revenue.

So if it were a 100% consumption model, RPO would be zero.

That is exactly right.

Okay. And the expectation is that most of these customers would not be signing up for those larger volume commitments, so that is going to be an expected drag on the RPO and CRPO.

Yeah.

Yeah.

Okay, all right, thank you for that. Thank you.

And that's quite easier to buy rather than saying 10, 20, 30, 40, 50, I think one deal we did was $0.5 billion if I'm not mistaken, okay, pretty well it was $300 million plus a couple of things. We're saying, hey, it's a $0.5 million, if you like it, keep it, okay? And so after they pay their $0.5 million if it goes that way there is no RPO.

That's right.

Got it, got it. And maybe just one more if I could and apologies to be taking all the time here, but I did just want to circle up, I know that you guys are talking about the C3 Generative AI pilots being $250,000, 12 weeks and the remaining product lines, I believe, and correct me if I'm wrong, but you have typically about six months for those pilots, can you help us think through what -- is it just a ton of value on these Gen AI pilots is so much quicker than you think that these customers can convert that much faster?

It is quicker Mike. In one case, we might have to add or load all the data, model supply chain, and build machine learning models that fit the -- that fit the scale of the enterprise of a Cargill, which is roughly $100 billion business or the United States Air Force, which is a pretty big business, okay? With generative AI, we don't have to do any of that, okay? We just load their data into a deep learning model and it kind of takes the learnings from those data, stores it in a vector store and we're kind of -- we're the Masters of the Universe at aggregating structured data, non-structured data, sensor data, enterprise data, images, what have you into a unified federated image, we have 14 years of that, we're really good at that, so that's easy, and then with all the mappings are worked out by one deep learning model, they are stored in a vector data store and then the -- so we don't have these huge data science projects that we have at all these other organizations. So, yes, the time to value is faster, the implementation effort is easier, and it's technically, honestly, it's an order of magnitude easier problem.

Awesome. Thank you very much, guys, I appreciate it.

And there is nobody who doesn't want to talk about it.

Great to hear. Thank you, guys.

Thank you. One moment for questions. Our next question comes from Kingsley Crane with Canaccord Genuity. You may proceed.

H. Thanks for taking the question, and congrats on the result. It sounds like your plan is to invest more in lead-gen branding market awareness, customer success, you've mentioned that you have more than 140 qualified leads in Gen AI, so it seems like you've done tremendously well in generating leads. So as we think about the incremental change to the profit guidance are you balancing investments between customer success and pilot conversion without lead-gen and brand awareness?

I'm sorry, what was the -- how we're balancing between customer success and lead-gen? Okay. A lot of this is branding and lead-gen, Kingsley, is what we're looking at. Kind of like we used to do in 2021 when we establish the brand for enterprise AI that worked out pretty well and we're going out to plant a flag on this Generative AI market and we're going to -- we're first to market, how many companies out there, have 28 enterprise Generative AI solutions in the world. I know how many, exactly one, and we're going to communicate that, we're going to make it available. So that's what the bulk of it is. At the same time, if we have a customer in any one of these markets where we need to really get resources to make them successful with their pilot, you can be sure, we're going to make them successful with their project. And as we get down the learning curve will get increasingly efficient at it and gross margins go up.

Okay, thanks, Tom. That makes a lot of sense. And so if I could ask one more, hoping you gain some clarity on the 28th domain-specific Gen AI solution, so for example, if you're an oil and gas customer you're building a solution in sales and this is ultimately linked into Salesforce is that requiring three separate apps or how would that be consumed and priced?

That will be in one, basically, it's price per CPU. I mean, that looks like it's going to be on a judgment basis whether it's a discrete projects or whether it's a -- whether the union out them is one generative AI application, whereas as you have described it, the union of them is one generative AI application, it will be a $0.25 million to bring it live in 12 weeks, and after that pay $0.35 per VCPU hour or VGPU hour.

Okay, very helpful. Keep up the good work. Thank you.

And as it relates to when it gets to runtime pricing, it doesn't really matter whether it's one application or whether it's three, it's going to be the same amount of run time.

Thank you.

Thank you. One moment for questions. Our next question comes from Pinjalim Bora at JPMorgan. You may proceed.

Hey, guys, this is Noah on for Pinjalim, thanks for taking our questions. So on the semi-pilots that are active at the moment, if we exclude the pilots that have been extended one or two months, is there any way to parse out how many of these pilots are under production licenses? And I have a quick follow-up.

I think -- thanks, Noah, for the question. So I think at this point, the way we are looking at this that there were 73 pilot deals that we've been doing, 70 are either converted or in the process of the pilot or we are negotiating a production license on those. I think the meaningful amount or a meaningful message you should take from this that out of 73 pilots, we only have three notes. So we have a pretty -- we feel very comfortable and very bullish about how that pilot program is currently progressing.

Understood. And then maybe just a double click on the gross margins, I know you commented that with the transition to function.

Let me comment on the nos. The no wasn't that the pilot wasn't successful. Okay. The no because I know exactly what they are and they are hugely successful. That said, what happened is the genius CIO went to the CEO and said we're going to build this ourselves out of a bunch of tinker toys, so let him go do that. He's going to go through that for about two years. They're not going to be able to resolve their cyber security problems, their IP infringement problems, they're going to have data exfiltration problems, they're going to have random answers and they'll be back. So the sales cycle there was just a little bit longer than we thought. They're not lost. They just -- they're just suspended. Sorry, could --

No. I appreciate that, appreciate the clarity. And just a quick follow-up on the gross margins. Just any way to kind of help us with our model going forward in terms of how to think about gross margins, I know you laid out your commentary about this quarter's impact, but just any additional thoughts there would be helpful for the year?

I mean, I think, Noah, the punch line is that we are still expecting some margin pressure on it and as there is going to be more pilots, it's going to be margin pressure until the consumption becomes a more dominant portion of the revenue stream, which would then offset it and start picking up that margin, so continue to expect some pressure still on the gross margin.

Thank you. One moment for our next question. Our next question comes from Sanjit Singh with Morgan Stanley. You may proceed.

Thank you for taking the questions. I had one for Tom and one for Juho. Tom, what's the vision around sort of multimodal? I know there's a lot of interest around the language models that as you think about the different diffusion models, video, audio, image, what's the -- what's the vision around supporting those types of models if multimodal becomes the dominant deployment architecture for enterprise AI?

Are you talking about data, Sanjit? I'm not sure I understand the question.

Yeah, what I was referring to is like obviously like the GPT models or language models and they've taken the world by storm, but there other AI models that deal with image, audio, video with other sources of data as we think of --

So you are commenting on the fact that these large language models tend to be almost exclusively limited to text, HTML, and code. So other sorts of data they don't know how to ingest. Okay, good, good. So let's talk about this. We are the Masters of the Universe at ingesting what you call multimodal data images, okay, images from space, trajectories of hypersonics, high-speed telemetry, trading volume, the rate at which electrons are going across the grid, enterprise data free text, and so we're using our standard architecture to ingest those data. We're using one of our standard deep learning models to basically parcel this data and store all the relationships in a vector data store, okay. All the large language model we're using for is interacting with you and me to handle the natural language, to understand what we're saying and it takes the answer back from the data and give it to us in pros rather than some gibberish that might be spewed out of SAP.

Right. It makes perfect sense

That is one of the reasons why people find our generative AI solution attractive as we're tried, tested, and proven at ingesting any kind of data they can think of.

Understood. And then the question for Juho is if I sort of look at the presentation and we sort of look at where we are in the sort of transition Phase 1, Phase 2, it sounds like we've just started sort of Phase 2 and the glass sort of implies that we'll put to get to revenue neutral by seven quarters in, we're about four quarters in and then revenue accretive about eight quarters in, so about three or four quarters away, is that still the timeline should we should be thinking about in terms of revenue acceleration, any color around that would be hugely helpful.

So, Sanjit, the chart that you're looking at, I think you should think about this as a kind of per-customer basis, right, like it's not necessarily the entirety of how our business is going, but the idea is that as we now have some of the regional early pilots from last year's Q2 and Q3, they're starting in the Phase 2 category. And as I mentioned on my prepared remarks, we have preliminary data on actual VCPU consumption for that first three quarters and it's slightly above what we've modeled before. So we are in this fourth quarter of the transition and we are starting to see some very positive indicators with respect to how the consumption will run for these consumption-based deals.

Got it. I appreciate the context. Thank you.

Thank you.

Thank you. And we have time for one final question. Our final question comes from Michael Turits with KeyBanc Capital Markets. You may proceed.

Hey, thanks for taking the question. This is Eric Heath on for Michael. So I wanted to ask on Baker Hughes, two-part question, just one of you can give us some color on what changed with the relationship that they are no longer considered a related party? And then secondly and I hope this isn't too nuanced, but if I take that $16.5 million of Baker revenue contribution for two months in the quarter and kind of extrapolate that out for an additional month, I get about $24 million versus what we're thinking of around $20 million, so I guess my question is how did the Baker Hughes contribution in the quarter compared to your expectations and anyway to understand how the non-Baker Hughes did relative to your guidance. Thanks.

First of all, Baker Hughes is not a related party because they monetize some of their stock. Remember they bought some stock some time ago for about 3 bucks and they sold it for I forget what the rough number was. It could be half by a buck or 2, I don't know but for nothing and they sold it for a lot, so it's pretty darn good trade. And today, because they own less than 5% by definition they no longer related party. As it relates to the Baker Hughes revenue, you should actually know that, didn't we provide that in the memo, in other words -- that we wrote like three quarters ago. I mean it's -- I'm sorry, I forgot to ask the question.

What was your name?

Hey, Tom, it's Eric from KeyBanc.

Okay. We were actually -- it's on our website. It's on our IR site. You're going to be able to see what the minimum Baker Hughes revenues is. We provided that in great detail and it's on the IR site.

Anyway to just kind of quickly frame how it wasn't that quarter relative to your expectations and contribution. Sorry, it's something that I forgot about.

Exactly what we expected.

That's right.

Exactly what we expected.

All right. Thank you.

Thank you.

I guess that was our last question. Ladies and gentlemen, so, Tom and Juho are out. Thank you for your time. Thank you for your attention and we look forward to providing an update at the end of our second quarter. So thanks a lot. Stay tuned and hopefully we'll have some exciting things to report.

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