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spk18: Good afternoon, and welcome to C3.ai's earnings call for the fourth quarter fiscal year 2023, which ended on April 30th, 2023. My name is Amit Berri, and I lead investor relations at C3.ai. With me on the call today is Tom Siebel, Chairman and Chief Executive Officer, and Juho Parkinen, Chief Financial Officer. After market close today, we issued a press release with details regarding our fourth quarter results, as well as a supplemental of 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 be caused that could cause the 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 and response to your questions, we may discuss metrics that are incremental to our usual business 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.
spk15: Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. We finished the fourth quarter strong. and the coming year looks stronger. I believe that it is generally agreed that the overall market for enterprise AI now appears substantially larger and is growing at a much greater rate than most analysts and experts predicted. We have been working since 2009 to develop product leadership and establish thought leadership in enterprise AI. assisting private and popular sector enterprises to apply AI to improve operational processes. C3.AI has been at the vanguard of enterprise AI of the enterprise AI market for over a decade, as the market has developed from its roots in IoT to supervised learning, unsupervised learning, NLP, deep learning, reinforcement learning, and now generative AI. In the past 14 years, we have developed and enhanced the C3 AI platform and now offer over 40 enterprise AI applications developed with that platform that allow our customers to rapidly take advantage of AI to improve their business processes. We have been communicating for over a decade that we believe that the market for enterprise AI solutions would be quite large. And now, as we enter the summer of 2023, has become a dominant theme in technology discussions. AI has become a dominant theme in technology discussions, government discussions, media reports, defense and intelligence imperatives, and government and business imperatives. I do not believe that it's an overstatement to say that there is no technology leader, no business leader, and no government leader who is not thinking about AI daily. AI chip makers like NVIDIA are accelerating production to try to keep up with the very real demand that's out there. And all of this is being accelerated by the advent of generative AI. The interest in AI and in applying AI to business and government processes has never been greater. Business inquiries are increasing. The opportunity pipeline is growing. Demand is increasing. And C3 AI is well positioned to serve that increasing demand with our tried, tested, and proven AI platform, our applications, our global footprint, and our large global ecosystem. The world is, in many ways, now coming to us. The interest in applying AI to business processes is substantially greater than we have ever seen. In the fourth quarter, we increased our customer base, expanded our work with existing clients, and saw especially strong growth in our federal business. In the fourth quarter, our total revenue was $72.4 million. Our free cash flow was $16.3 million. And we ended the quarter with over $812 million in cash and cash equivalents. Importantly, we have a well-defined plan to be sustainably cash positive and non-GAF profitable by the end of this fiscal year. For fiscal year 2024, I'm sorry, for the fiscal year 2023, total revenue was $266.8 million, an increase of 5.6% over fiscal year 2022. Subscription revenue was $230.4 million, representing an 11.4% increase over the prior year. Let's talk a little bit about the AI applications market. Now, as the enterprise AI market has developed, it appears that the bulk of the demand is increasingly for turnkey enterprise AI applications rather than for development tools. This thesis is supported by an evaluation of our bookings for the past fiscal year that indicates that 83% of our bookings were driven by application sales. 17% of our bookings were driven by the sales of the C3A platform. Importantly, we are seeing increasing diversity in the industries we serve. For fiscal year 23, an analysis of our bookings includes oil and gas was 34%. Federal defense and aerospace was 29%. High tech was 13%. Energy and utilities, 11%. Manufacturing, 4%, food processing, 2%, chemicals, 2%, life sciences, 1.5%, and other industries made up the remaining 3%. An important leading indicator of our increasing industry diversity is evidenced by the trial and pilot agreements closed in Q4. Federal defense and aerospace made up almost 37%. Manufacturing comprised approximately 16%, and high-tech made up more than 10%. Oil and gas also made up more than 10%. When we look at ag, state and local, chemicals, energy, and financial services, each made up approximately 5% of our bookings. As a result of the increased demand for enterprise AI, Helped by our transition to consumption-based pricing, we are seeing a substantial increase in opportunities and shorter sales cycles. In Q4, we closed 43 agreements, including 19 pilots that were initiated in the quarter. The number of qualified enterprise opportunities targeted for closure within 12 months in our sales pipeline has increased by more than 100% in the past year. During fiscal year 23, We closed 126 agreements, up from 83 in the prior year. The average sales cycle for new and expansion deals was 3.7 months, down from five months in Q4 of the previous year. An examination of the composition of our pilot account profile suggests there is significant opportunity for growth as these accounts convert to consumption pricing. Of the 19 pilot accounts signed in Q4, seven were accounts greater than $100 billion in revenue. Seven were accounts between $10 billion and $100 billion in revenue. Four were accounts between $1 billion and $10 billion. And one was an account less than $100 billion in annual revenue. In fiscal year 23, we expanded our application footprint with a number of our customers, including Shell, Hope Industries, the United States Air Force Rapid Sustainment Office, PwC, Ball, ExxonMobil, Con Edison, the Defense Counterintelligence and Security Agency, Baker Hughes, the New York Power Authority, Duke Energy, ATB in Canada, Defense Innovation Unit, Roche, Cargill, and Engie. We also established many new relationships during the year, including the Department of Defense Common DOD AI Office, Daly City, California, Dow, ExxonMobil, Flex, Hexagon, Nucor, Owens, Illinois, Pantaleon, Riverside County, California, Stark County, Ohio, TELUS, Department of Defense SOCOM, Department of Defense TRANSCOM, and ESAL. Many of these also expanded their AI engagements with us in the course of the year. Let's address the C3 AI Partner Network. The C3 AI Partner Ecosystem is increasingly effective at opening new doors. With our partners, we're able to provide prospects the assurance of success and the highest quality service. In fiscal year 23, we closed 71 agreements with and through our partner network, including Google Cloud, AWS, Microsoft, Baker Hughes, and Booz Allen. CTA AI increased its qualified pipeline with AWS by over 24% in the fourth quarter, with particular focus on state and local government. With Google Cloud, our joint qualified 12-month opportunity pipeline grew from 25 opportunities at the end of fiscal year 22 to 140 opportunities at the end of fiscal year 23, a 460% increase. And importantly, we closed 10 new oil and gas accounts in the year with our strategic partner, Baker Hughes, with accounts including ExxonMobil, AdNoc, ENI, and others. In Q4, we released the C3 generative AI solution to the market. Our generative AI solution leverages the capabilities of the C3 AI platform and is distinguished from other GPT, LLM solutions in the market in several ways. Number one, it allows enterprises to access all their enterprise and open source data, ERP, CRMs, data, text, PDFs, Excel, PowerPoint, sensor data, you name it. Secondly, importantly, it provides traceable, deterministic, consistent answers. Thirdly, it enforces the corporate information access controls and security protocols that are currently in place. Fourthly, it has no risk of IP or data exfiltration caused by the large language model. And importantly, it is hallucination-free. So if the system doesn't know an answer, it doesn't fabricate it, which is clearly unacceptable for any commercial or serious government application. After releasing the product in March, we rapidly closed three generative AI applications in the quarter with large enterprises, including Georgia Pacific, Flint Hills Resources, and the U.S. Department of Defense Missile Defense Agency. We expect these applications to be live during this current quarter. We are currently working up quite substantial pipeline of additional C3 generative AI opportunities with large corporations. The C3 AI generative application is now available, today available, on both the AWS marketplace and the Google Cloud marketplace. It is difficult to estimate the size of the addressable market for these generative AI solutions, but it appears to be extraordinarily large. We saw a lot of momentum last year and in the fourth quarter with our U.S. federal business. The U.S. federal sector represented 29% of our bookings in fiscal year 23, and it continues to show significant strength. Our predictive maintenance solution, our predictive analytics and decision assistant, also known as Panda, has been in production used for several years at the United States Air Force Rapid Sustainment Office. And last quarter it was selected as the system of record for all predictive maintenance for virtually all United States Air Force assets. This important designation expands our opportunity really substantially in the U.S. Air Force and other services. Let's talk about guidance. C3AI has a consistent and solid track record of meeting or exceeding guidance, as we have done in every quarter since we've been public. And we are, at this time, we are not inclined to pout on the table regarding guidance. In general, we feel comfortable with the expectations that the Southside analysts have set for the coming year, and we are not inclined to change those expectations at this time. For Q1, Fiscal year 24, we see revenue in the range of $70 to $72.5 million. For the full year of fiscal year 2024, we expect revenue to be in the range between $295 million and $320 million. As it relates to non-GAAP loss from operations, we expect to fall between $25 million to $30 million in Q1 and $50 million to $70 million for the year. As we begin fiscal year 24, C3 AI has never been better positioned. The addressable market is large and expanding. The overall business environment for enterprise AI is strong, and C3 AI is front and center in the minds of CEOs and government leaders. Our balance sheet is strong, and with over $812 million in cash and cash equivalent, we are in a great position to expand market share. As the dynamics of the enterprise AI market are developing so rapidly, we thought it appropriate to host a mid-quarter investor day in New York City on June 22nd. We will provide, at that time, we will provide C3 AI investors a company update, additional information about our product roadmap, product demonstrations, direct access to the C3 AI executive team, updates on our partner ecosystem, C3 AI technology, C3 generative AI demonstrations, and additional company developing news. We hope you can attend either in person or online, and that investor day event will be available to view online live for all investors via webcast. I will now turn this call over to my colleague, Juho Parkinen, Chief Financial Officer, for additional details regarding our financial results. Juho.
spk03: Thank you, Tom. I will now provide a recap of our financial results, add some color to the drivers of our financials, provide more detail on our first quarter and full year fiscal 2024 guidance, and I will conclude with some additional color related to the consumption-based revenue model we introduced three quarters ago. All figures will be discussed on a non-GAAP basis unless otherwise noted. Overall, the business activity is higher than we have ever seen. Our sales reps are more engaged, there are more opportunities they're working on, and there are more interest from our prospects. During Q4, our ability to close agreements was more consistent throughout the quarter compared to prior quarters this fiscal year. We ended the fourth quarter with a total revenue of $72.4 million, of which subscription revenue was 78.5%. As we discussed last quarter, we expected professional services would be within our historical range of 10% to 20%, with our actual professional services coming in at 21.5% of the mix. Gross profit for the fourth quarter was $53.9 million, and our gross margin was 74.4%. We generated $27.1 million in positive operating cash flow and $16.3 million in free cash flow for the quarter. As mentioned during the prior updates, we have a short-term pressure on our gross margins due to a higher mix of pilots, which carry a higher cost of revenue than production deployment. Operating loss of $23.5 million was improved due to more rigorous expense management. As a reminder, though, the fourth quarter is when we host our C3 AI Transform customer event. As such, our marketing expenses ramped up to support the successful execution of that event. Operating loss margin was 32.5% in Q4, where the sequential increase was driven by our annual customer conference. For the full year, fiscal 2023, our revenue was $266.8 million, an increase of 5.6% from fiscal 2022. Non-GAAP loss from operations was $68.1 million, and free cash flow was negative $187 million. Our gross margin for the year was 77%, Our subscription revenue was 86% of total revenue compared to 82% in fiscal 22. We ended fiscal 23 with $812.4 million in cash and investments. At the end of Q4, our accounts receivable, including unbilled receivables, was $134.6 million. Unbilled receivables at quarter end was $77.6 million, inclusive of $70.7 million created to Baker Hughes. During the quarter, we collected from Baker Hughes nearly $35 million. The general health of our accounts receivable is excellent. 76% of our receivables were current or less than 30 days past due. For the entirety of FY23, our bad debt expense was approximately $300,000. Now turning to RPO and bookings. As consumption-based go-to-market model continues to pick up, RPO is less important indicator of future performance. We reported GAAP RPO of $381.4 million, down 20% from last year, which is expected as a result of the transition to consumption-based pricing. Current GAAP RPO of $186.3 million is up 9.8% from last year and up 5.7% on a sequential basis. We continue to see positive trends in pilot bookings diversity as we have sold pilots to a broad range of nine different industries during the quarter. Regarding our outlook for fiscal 24, we're guiding Q1 revenue to range between 70 to 72.5 million. For the full year 2024, we expect revenue to range between 295 and 320 million. As it relates to the full year, we finished the third quarter of our transition under the consumption pricing model. As a returning model, we expect flatness and somewhat of a decline in revenue during the transition with an acceleration as consumption starts to have meaningful portion of our in-quarter revenue. As such, we expect the second half of FY24 to have higher growth rates on a sequential basis than the first half. We expect our non-GAAP loss from operations to range between 25 and 30 million for Q1, and for full fiscal 24, we expect non-GAAP loss from operations between 50 and 75 million. As a reminder, We expect to be non-GAAP profitable for Q4 24 and beyond, and as it relates to full fiscal 24, we are guiding to a range in operating loss due to the potential investments we may do for C3 generative AI applications. We expect our cash and investments to be at its lowest at around $700 million during fiscal 24. Turning to customer metrics. Historically, we have provided a quarterly customer count estimate as a proxy for the adoption of our products and solutions. However, due to the complexity of our contractual and pricing structures and the involvement of resellers, we believe comparing customer counts from quarter to quarter based on our current methodology does not fully convey the acceptance and adoption of our products and solutions. To help address this, we retained an external Big Four consulting firm to update our current customer methodology consistent with best practices to be consistent, systematic, and auditable. As a result of that review and adoption of those recommendations, we believe a metric that demonstrates contracted use cases that our customers are using our solutions to solve would provide a more meaningful understanding of the product adoption. This is defined as customer engagement. The customer engagement increased from 247 to 287, comparing Q3-23 to Q4-23. Our traditional customer count metric went from 236 to 244 for the same period. There will be additional detail included in the supplement, which is available on our website. We are on track with our plan for profitability for Q4-24 and expect to have cash positives quarter starting Q4-24 on a consistent go-forward basis. The entire executive team is managing the business to a detailed budget on our plan for profitability. We are expecting to invest aggressively to generative AI initiatives during the first half of the year, which is reflected in the operating income guidance. As it relates to the model assumptions that we provided three quarters ago for our consumption-based pricing, our preliminary analysis of the actual results suggests we are on that model. Overall, we're very excited about the business momentum as we start FY24. As a go-forward KPI for the investing community to assess our performance, we believe good KPIs to focus are the number of pilots started during the quarter the conversion of those pilots to production, and finally, the actual vCPU consumption fees generated. With that, I would like to open this up for questions. Operator?
spk20: Thank you. Ladies and gentlemen, if you'd like to ask a question, please press star 11 on your telephone. Again, to ask a question, please press star 11. One moment for our first question.
spk23: Thank you.
spk20: Our first question comes from the line of Canaccord. Your line is open.
spk08: Oh, hi. Thanks for taking the question. So, Tom, you said that sales cycles were down to 3.7 months from five months last year. Why do you think that is? Is this entirely due to the consumption model? How much of this is due to general excitement around the potential in the space? and even potentially increase Salesforce productivity.
spk15: Thanks, Kingsley. I think it's all of that. I mean, clearly, AI is on everybody's mind. The consumption-based pricing model that we have makes it much easier to adopt our technology. I mean, in the old days, you know, one and two years ago, to do business with us was, you know, $5, $10, $20, $50 million to open the door. And now the transaction is pretty much, you know, we'll bring the application live in six months for half a million bucks. If you like it, keep it. And pay $0.35 per CPU hour, since we're pretty easy to do business with. And so we're seeing the number of transactions increase dramatically, as we'd expect. The, you know, the ease of contracting with us, as you know, We have largely reconstituted the sales organization the last year and a half to a sales team that is candidly much more productive and effective than our other sales organizations. So I think all of those are contributing to increased pipeline, increased business, increased business activity, about which we're quite optimistic.
spk08: Thanks, Tom. That's really helpful. And then one for Juho. I want to think about the timing of the transition. So if it is the case that the vast majority of existing customers are not necessarily migrating to the consumption model, how should we think about the contribution of consumption over time and then particularly in the back half? Because I think that you said, you know, revenue could accelerate as consumption increases and mix.
spk03: Yeah, Kinski, thanks for that question. So that's exactly, as we sign and initiate more PYGOTs within the quarter, the PYGOTs are generally two quarters long, and then you start to see the consumption revenue kick in. As we finished the quarter with 19 PYGOTs last quarter, we had a good increase in PYGOTs at 17 PYGOTs as well. You can start seeing those layer on to the revenue by Q3 and Q4 of this fiscal year. Now, to your point about renewals, we do expect our existing customers with the large enterprise agreements to continue to remain on those types of agreement structures, but you will see the RPO trickle down as these contracts enter into renewal phase, and then we would expect to see a pickup as they renew.
spk07: Okay, very helpful. Thank you.
spk20: Thank you. One moment, please. Our next question comes from the line of Pat Walraven of JMP Securities. Your line is open.
spk16: Oh, great. Thank you. Tom, can you talk some more about the opportunity with national security and the Department of Defense? And then also you said something I thought was interesting about a version of generative AI that doesn't hallucinate. If you could maybe comment a little more on what hallucinating is and how you prevent it from doing that. I think that would be really interesting. Thank you.
spk15: DOD, well, Pat, you've asked kind of many times about the – we have two basically authorities to operate contract vehicles, one's for $100 million and one's for half a billion in DOD that are associated and it could be applicable to what we're doing at RSO. That was the Rapid Sustainment Office and the predictive maintenance application that we're doing for the United States Air Force for DOD. F-15, F-15, F-18, F-35, KC-135, et cetera. And we made a proposal to the Secretary of the Air Force to take that into full production for all the aircraft in the Air Force, which is 5,000. And I think the proposal would have increased aircraft availability for the Air Force by 25%, and I think decreased their cost of maintenance and readiness by about $6 billion. So he considered that, as did his chief of staff, General Brown. And they went off on their own for a few months while you were asking them the questions, and we didn't have the answers. And these guys go into their star chamber the way they do. What they came out with was a selection of C3 as the system of record. not only for aircraft in the United States Air Force, but for all AI-based, all predicted maintenance, okay, in the United States Air Force for all assets. So this is genuinely a big deal. Okay, now we have the opportunity to make this a line item in the budget. So this is, you know, it's hard to, you know, over-describe the impact of this or over-estimate the impact of this. And then not only do we have it in the Air Force, we can talk now to other services like the Army and in the Navy, in the Marines, in the National Guard, what have you. So this is a big one. The second one has to do with generative AI. So one of the problems with generative AI is you're limited to the number of data sources that you can use with these large language models. Typically, it's text, HTML, or sometimes code. And the large language model will interact directly with the data. Well, one of the problems is you get kind of random answers. You know, every time you ask the question, you get a different answer. If two people ask the same question, you get a different answer. And there's no traceability. It doesn't tell you where the answer came from. And finally, if it doesn't know the answer, it makes one up. This is what they call hallucination. So it doesn't know, so it just kind of wings it and makes up an answer. So we're using the entire C3 platform And the way that we do that is we incorporate, as you, I think, all know, we're very good at aggregating enterprise data, extra price data, code, images, text, sensor data, what have you, into a unified federated image. Now, when we do that, those data are read by a deep learning model, and they happen to be stored in a vector database. then we have a kind of a firewall between that and the large language model. Now, our customer can use any large language model they want, be it chat, GPT, be it Palm, be it BARD, be it Plan T5, whatever comes along next. But we've built a firewall between the large language model and the data. So every time you ask the question, it will give you the same answer. okay if two people ask the same question and they have the authority they will both get the same answer every time associate with the answer it provides you traceability so you can click on it you can see exactly where the data came come from okay and okay very importantly there's no risk of llm caused data exfiltration see samsung for details where they find out that all of their proprietary information is not published on the internet okay and Finally, there's no risk of LLM caused hallucination. If it doesn't know the answer, it tells you I don't know the answer rather than making one up. So, you know, for these you'd think would be kind of table stakes, and they are table stakes for any large commercial or government installation, and this is something that really distinguishes the C3 generative AI offering and one of the reasons that we're seeing, you know, very high levels of interest.
spk16: Oh, great.
spk22: Thank you.
spk20: Thank you. One moment, please. Our next question comes from the line of Sanjit Singh of Morgan Stanley. Again, our next question comes from the line of Sanjit Singh of Morgan Stanley. Your line is open.
spk17: I appreciate you guys squeezing me in for the question. Tom, you know, earlier this week you guys announced how to press release about the C3 General AI Suite being available in the Amazon Marketplace. And it got me thinking about what the sales motion going forward is going to look like. As you sort of mentioned, General AI is permeating the boardroom, the C-suite, in a pretty substantial way. And when we look at sort of converting this interest into deals and ultimately revenue, how much of this is going to be like flywheel kind of, self-service, consumption-based marketplace-type deals versus you working with partners, taking a more consultative approach and helping, you know, these large enterprise customers sort of navigate the world of generative AI and actually deliver value?
spk15: Great question, Sanjit. So our first three engagements that are involved in now will be our organizations, the order of a hundred billion or greater in revenue. Okay. And have, um, um, you know, we'll bring the application alive in 12 weeks. We're not doing it within a game with w and we have like three people on the project. So it's pretty straightforward. Um, now the, you know, the issue of going from say six customers to 60 customers to a hundred customers. It's pretty straightforward. We know how to do that. The real key is, in terms of blowing the doors off this thing, can we go from 60 customers to 60 customers to 6,000? So for 6,000, now we have to leverage these channels like the AWS marketplace where the product's available today, the Google marketplace where they're available today. But in terms of usability, it needs to be like the Apple iPhone. You open the box, you take the cellophane off, you turn it on, and it works. And so now we're, you know, the next generation, the really serious development work that we're doing now on that product kind of relates to really product design and making it like an Apple product. You open it up, you turn it on, and it works. And so that's the challenge that's before us. I think we're up to it. And if we're able to hit that note, hold on to your socks.
spk17: I appreciate the color, Tom. And then maybe one follow-up. Maybe this is for Jill and Tom as well. And it sort of relates to the guidance for the full year. I'm trying to, you know, contextualize, like, what's really driving the guidance for next year because we're coming off a year, fiscal year 21, I think you guys grew north of 30%, 33%, 34%. This past year, you guys grew sort of mid-single digits. The initial guidance calls for growth sort of mid-teens at the midpoint, sort of 20% at the high end. And I want to understand, like, is the acceleration you're seeing a function that you're coming off, you know, a tougher year where you had, you know, spending environments were difficult, sales reorg, those types of things, versus, you know, generative AI really coming online in fiscal year 24. And so is there any way you can sort of, you know, attribute, you know, those two things between sort of coming off of, you know, a tougher year versus, the demand that you're seeing in pilots and out in the field.
spk14: Let me address the premise. Before we all wring our hands about your tougher year, tougher year, tougher year, I think we got that in four times in the call for all the audience.
spk15: Let's remember, when we announced the transition to consumption-based pricing, we made it very clear that this was going to have a short and mid-term Okay, negative effect on revenue growth. It's actually a math. Anybody who knows how to use a spreadsheet can figure this out. If we're closing half a million dollar deals instead of 10, 20, 30, 40, 50 million dollar deals, the short-term impact on revenue is to dampen revenue growth. So I'm not certain that's so tough. Okay, that is basically we're executing exactly to the plan that we set. So this thing is exactly on track. Now, when you run this two-year little extra spreadsheet model and you hit the carriage return, okay, and you run it out a few years, you know, a few quarters out there, you know, you can do the math and you know what happens. But I'm not, you know, so I think we're exactly on plan with what we did. We made the investment. I think it was a great decision. It was a good investment. And now in fiscal year 24 and 25, we're going to yield the returns from that investment.
spk19: Great. I appreciate the thoughts. Thank you. One moment, please.
spk20: Our next question comes from the line of John of Web Bush. Your line is open.
spk13: Hi. Thanks for taking my question. This is John for Dan Ives. So given the increased diversity seen, I guess, across industries served, how have you seen these use cases develop, and how do you see them playing out? Thank you.
spk15: Great question, John. Well, right now, you know, I mean, in terms of applying AI to enterprises, we're in, you know, first half of the first inning and, you know, the first guys at bat. OK, so this is an embryonic market. I mean, where we're seeing the biggest uptake immediately. First, it was in the smart grid. Okay. Why the smart grid? Because they had invested $2 trillion of the upgrade and get it good infrastructure globally to make all the devices in the smart grid, uh, remotely machine addressable is a huge IOT constellation. So that's where we saw it first. The next large, where we're seeing it in the past year, the largest market is in AI reliability, basically predictive maintenance. So then in the military, they call readiness. Okay. Or in the private sector, they call reliability. So AI-based predictive maintenance is the largest segment today. How will this evolve? I mean, it's clear we will be applying AI to all business processes. Production optimization, demand forecasting, supply chain risk, okay, stochastic optimization of the supply chain, you know, CRM. I think there is no aspect of business operations that will not be – okay, and medicine – okay, and research and the science and literature and entertainment that will not be accelerated by the use of AI. So we're along for the ride and going to see where this goes in the next few years and stay on the balls of our feet as it develops, but it is a rocket ship. Thank you, Tom.
spk20: Thank you. One moment, please. Our next question comes from the line of Mike Sikos of Needham Company, your line is open.
spk06: Hey, guys. Thanks for taking the questions here. Maybe the first would be going to you, Ho. So I know that you guys incited the 43 deals you closed this quarter. Nineteen of those are pilots. Can you further refine that for us? And maybe it's just the classifications or names we're using for this, but, like, how many of those pilots are purely consumption-based? versus maybe pilots that are still coming in under the old pricing model?
spk03: Hi, Mike. No, these are all – these would all follow the new consumption-based approach. These are not under the old model at all.
spk06: Okay. Okay. And so I guess the follow-up that I have on that is with the 19 deals that are consumption-based, and I know that you guys have – I'm sorry, 19 pilots that you guys closed that are initiated that are consumption-based this quarter – and the other pilots that we've cited in previous quarters, do we have a feel for how many of these pilots have now converted to production? And do we have a gauge for what the VCPU is for those consumption deals once they move into production?
spk03: That's a great question. So, Mike, on the first quarter we announced this would have been Q2, which obviously if you take six months from that, we get towards the end of Q4. So, we are very early in that. in the conversions. We are standing by with the model assumptions, i.e. whatever we provided three quarters ago where it is each pilot is expected at 70% likelihood to convert into a follow-on consumption deal. But I would say that the first quarter for consumptions, we really will start seeing more of that this quarter since it was late in Q2 as we entered into those original pilot arrangements.
spk05: Understood. Understood on that.
spk06: Thanks for that. And then just one quick follow-up, if I could, but I wanted to ask, just on the professional services revenue, I know it's a tick higher versus that typical 10% to 20% range we've been talking about, and I just wanted to see, is 10% to 20% still the appropriate range we should be thinking through, or is there maybe more hand-holding for these pilots as you guys engage in them, or is it maybe hand-holding of potentially federal sector customers? How do we think about the higher pro-serve revenue generation in Q4 versus what you guys are thinking about over the next year?
spk03: I think on a go-forward basis, we expect to be in the 10% to 20% range. There's always going to be these types of projects that our customers want, but it's difficult to forecast a specific percent in a go-forward revenue, but we believe 10% to 20% is appropriate on a go-forward basis.
spk06: Thank you for that. I'll turn it back to my colleagues. Appreciate the time.
spk20: Thank you. Again, ladies and gentlemen, if you'd like to ask a question, please press star 1-1 on your telephone. Again, to ask a question, please press star 1-1. Our next question comes from the line of Brad Sills of Bank of America. Your line is open.
spk11: Hey, great. Thank you. This is Adam Brashear. I'm for Brad Sills. So you're pretty well positioned in the current market, just given, you know, AI use cases are coming into focus. I'm kind of curious if this has changed your cadence for R&D investments at all.
spk15: Well, this is Tom. I mean, clearly the investments we've made in the last 14 years are paying off. Okay. You know, in that we have over 40 applications and people want applications. And I think we're the only company in the world that has 40 applications. I think the only recent change that we've made is we're a little bit shocked by the response that we had to C3 generative AI. I mean, we're a little bit overwhelmed by that. That's a big opportunity. And so now we just came off of Planet Mean, and we decided to really invest in that product category in a big way because it's you know, it's just difficult to estimate the size of that market, but it's extraordinarily large.
spk11: Yep, fair enough. And then for, you know, kind of degenerative AI use cases and solutions thus far, you know, I guess the first, you know, this is your first take on it, but do you see any, you know, outsized uptake, you know, or expect any outsized uptake within certain verticals over others in your view? Thank you.
spk15: You know, it's a good question. It kind of seems like everybody is interested in this. They want, you know, at the level of the CEO or the person who operates manufacturing and the person who operates sales, they want basically a Google-like interface where they're getting a web browser-like interface where they can ask any question about their business. Okay, where are the problems in our supply chain? If I'm the chair of the Joint Chiefs, what are my readiness levels? We have 35 squadrons in Central Europe. I mean... that's what we call Google for DOD, but their open AI initiatives can provide the Secretary of Defense or the Chair of the Joint Chiefs of Staff answers to that question in seconds. Right now, it actually takes weeks for him or for most people to get those answers. So I don't know any industry that will not be taking use of this technology. It's really quite amazing.
spk11: All right. I appreciate the perspective, Tom. Thank you.
spk20: Thank you. One moment, please. Our next question comes from the line of Mike Sikos of Needham Company. Your line is open.
spk06: Hey, guys. Thanks for getting me back in. I did just have one quick follow-up. Maybe building on the question that Sanjay had asked earlier, but taking a different look. Rather than looking at the revenue, let's talk profitability for a second. But Obviously, you guys are issuing guidance now, which is below street and below what you guys had initially flagged if we go back a quarter ago, maybe for you, Ho. Can you help us think about the additional levers you have to pull on to ensure that C3 is achieving its target of exiting fiscal 24 with non-GAAP profitability?
spk15: Before we answer it, Mike, I do want to poke at the premise a little bit. I think our guidance is pretty much in line. with what the street expectations are once you take out, like, one outlier or two outliers. So I think our current guidance is in line with what the street currently has. I'm pretty confident of that.
spk03: Now, the other question related to how are you sure you're going to get to profitability? Right. So, Mike, one of the things that I had on the prepared remarks was our planned investments into generative AI, which combined that and vendor expenses, I think we can – control spending towards the end of the year if, for whatever reason, the expected revenue would not occur from those. But we're pretty bullish about the generative AI opportunity.
spk06: Got it. Thank you very much.
spk15: That being said, we don't need the generative AI opportunity to be – generative AI could be zero, okay, and we're still going to run a cash-positive profitable business in Q4. Well, we have a very, very detailed plan that's been distributed to all the members of the management team. They all have big budgets. They know that it can operate. You can expect it to be a cash-positive, profitable business and non-gap profitable business in Q4, hard stop. That's right.
spk20: Thank you.
spk21: One moment, please. One more question.
spk20: Thank you. Our next question comes from the line of Noah Harmon of J&P Securities. Your line is open.
spk02: It was great to see, you know, the average sales cycles for agreements tick down, I think, by about 1.3 months year over year. You know, what's really driving that? And, you know, where do you think, you know, a sustainable, you know, sales cycle, you know,
spk22: basically concludes that, maybe thinking about the rest of this year. Thanks.
spk15: Well, I think the consumption-based pricing model is driving it, where it's pretty easy to adopt when you can have a large-scale enterprise AI application live in production in six months for half a million bucks. I mean, that's nothing, guys, in terms of what it costs to bring in an Accenture or an IBM or somebody to try to bring one of these things live. That's going to be scores of millions of dollars in years. So it's a pretty easy sale. It's a shorter sales cycle. And, um, you know, so, you know, I'm not sure where, where it ends up, but, you know, as, as we move more and more of our products onto the AWS marketplace, the Google marketplace and other, other, you know, leverage channels like this, you know, we'd expect to see it, you know, get shorter.
spk22: Great, thank you. Thank you.
spk20: Thank you. I just want to turn the call back over to Mr. Siebel for any closing remarks.
spk15: Ladies and gentlemen, we, you know, thank you so much for your attention today. Thank you for tuning in. I encourage you to mark your calendars for June 22nd. I think you'll find that... that we'll talk about some interesting developments at our investor conference at that time, and we hope you'll have time to join us for that exchange. So thank you very much for your time today, and we wish you all a good night.
spk20: Thank you. Ladies and gentlemen, this does conclude today's conference. Thank you all for participating. You may now disconnect. Have a great day. you Thank you. Thank you. Thank you.
spk01: Thank you. music music
spk18: Good afternoon, and welcome to C3.ai's earnings call for the fourth quarter fiscal year 2023, which ended on April 30th, 2023. My name is Amit Berri, and I lead investor relations at C3.ai. With me on the call today is Tom Siebel, Chairman and Chief Executive Officer, and Juho Parkinen, Chief Financial Officer. After market close today, we issued a press release with details regarding our fourth quarter results, as well as a supplemental of 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 be caused that could cause the 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 and response to your questions, we may discuss metrics that are incremental to our usual business 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.
spk15: Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. We finished the fourth quarter strong. and the coming year looks stronger. I believe that it is generally agreed that the overall market for enterprise AI now appears substantially larger and is growing at a much greater rate than most analysts and experts predicted. We have been working since 2009 to develop product leadership and establish thought leadership in enterprise AI. assisting private and popular sector enterprises to apply AI to improve operational processes. C3.AI has been at the vanguard of enterprise AI of the enterprise AI market for over a decade, as the market has developed from its roots in IoT to supervised learning, unsupervised learning, NLP, deep learning, reinforcement learning, and now generative AI. In the past 14 years, we have developed and enhanced the C3 AI platform and now offer over 40 enterprise AI applications developed with that platform that allow our customers to rapidly take advantage of AI to improve their business processes. We have been communicating for over a decade that we believe that the market for enterprise AI solutions would be quite large. And now, as we enter the summer of 2023, has become a dominant theme in technology discussions, government, or AI has become a dominant theme in technology discussions, government discussions, media reports, defense and intelligence imperatives, and government and business imperatives. I do not believe that it's an overstatement to say that there is no technology leader, no business leader, and no government leader who is not thinking about AI daily. AI chip makers like NVIDIA are accelerating production to try to keep up with the very real demand that's out there. And all of this is being accelerated by the advent of generative AI. The interest in AI and in applying AI to business and government processes has never been greater. Business inquiries are increasing. The opportunity pipeline is growing. Demand is increasing. And C3.AI is well positioned to serve that increasing demand with our tried, tested, and proven AI platform, our applications, our global footprint, and our large global ecosystem. The world is, in many ways, now coming to us. The interest in applying AI to business processes is substantially greater than we have ever seen. In the fourth quarter, we increased our customer base, expanded our work with existing clients, and saw especially strong growth in our federal business. In the fourth quarter, our total revenue was $72.4 million. Our free cash flow was $16.3 million. And we ended the quarter with over $812 million in cash and cash equivalents. Importantly, we have a well-defined plan to be sustainably cash positive and non-GAF profitable by the end of this fiscal year. For fiscal year 2024, I'm sorry, for the fiscal year 2023, total revenue was $266.8 million, an increase of 5.6% over fiscal year 2022. Subscription revenue was $230.4 million, representing an 11.4% increase over the prior year. Let's talk a little bit about the AI applications market. Now, as the enterprise AI market has developed, it appears that the bulk of the demand is increasingly for turnkey enterprise AI applications rather than for development tools. This thesis is supported by an evaluation of our bookings for the past fiscal year that indicates that 83% of our bookings were driven by application sales. 17% of our bookings were driven by the sales of the C3A platform. Importantly, we are seeing increasing diversity in the industries we serve. For fiscal year 23, an analysis of our bookings includes oil and gas was 34%. Federal defense and aerospace was 29%. High tech was 13%. Energy and utilities, 11%. Manufacturing, 4%, food processing, 2%, chemicals, 2%, life sciences, 1.5%, and other industries made up the remaining 3%. An important leading indicator of our increasing industry diversity is evidenced by the trial and pilot agreements closed in Q4. Federal defense and aerospace made up almost 37%. Manufacturing comprised approximately 16%, and high-tech made up more than 10%. Oil and gas also made up more than 10%. When we look at ag, state and local, chemicals, energy, and financial services, each made up approximately 5% of our bookings. As a result of the increased demand for enterprise AI, Helped by our transition to consumption-based pricing, we are seeing a substantial increase in opportunities and shorter sales cycles. In Q4, we closed 43 agreements, including 19 pilots that were initiated in the quarter. The number of qualified enterprise opportunities targeted for closure within 12 months in our sales pipeline has increased by more than 100% in the past year. During fiscal year 23, We closed 126 agreements, up from 83 in the prior year. The average sales cycle for new and expansion deals was 3.7 months, down from five months in Q4 of the previous year. An examination of the composition of our pilot account profile suggests there is significant opportunity for growth as these accounts convert to consumption pricing. Of the 19 pilot accounts signed in Q4, seven were accounts greater than $100 billion in revenue. Seven were accounts between $10 billion and $100 billion in revenue. Four were accounts between $1 billion and $10 billion. And one was an account less than $100 billion in annual revenue. In fiscal year 23, we expanded our application footprint with a number of our customers, including Shell, Hope Industries, the United States Air Force Rapid Sustainment Office, PwC, Ball, ExxonMobil, Con Edison, the Defense Counterintelligence and Security Agency, Baker Hughes, the New York Power Authority, Duke Energy, ATB in Canada, Defense Innovation Unit, Roche, Cargill, and Engie. We also established many new relationships during the year, including the Department of Defense Common DOD AI Office, Daly City, California, Dow, ExxonMobil, Flex, Hexagon, Nucor, Owens, Illinois, Pantaleon, Riverside County, California, Stark County, Ohio, TELUS, Department of Defense SOCOM, Department of Defense TRANSCOM, and ESAL. Many of these also expanded their AI engagements with us in the course of the year. Let's address the C3 AI partner network. The C3 AI partner ecosystem is increasingly effective at opening new doors. With our partners, we're able to provide prospects the assurance of success and the highest quality service. In fiscal year 23, we closed 71 agreements with and through our partner network, including Google Cloud, AWS, Microsoft, Baker Hughes, and Booz Allen. CTA AI increased its qualified pipeline with AWS by over 24% in the fourth quarter, with particular focus on state and local government. With Google Cloud, our joint qualified 12-month opportunity pipeline grew from 25 opportunities at the end of fiscal year 22 to 140 opportunities at the end of fiscal year 23, a 460% increase. And importantly, we closed 10 new oil and gas accounts in the year with our strategic partner, Baker Hughes, with accounts including ExxonMobil, AdNoc, ENI, and others. In Q4, we released the C3 generative AI solution to the market. Our generative AI solution leverages the capabilities of the C3 AI platform and is distinguished from other GPT, LLM solutions in the market in several ways. Number one, it allows enterprises to access all their enterprise and open source data, ERP, CRMs, data, text, PDFs, Excel, PowerPoint, sensor data, you name it. Secondly, importantly, it provides traceable, deterministic, consistent answers. Thirdly, it enforces the corporate information access controls and security protocols that are currently in place. Fourthly, it has no risk of IP or data exfiltration caused by the large language model. And importantly, it is hallucination free. So if the system doesn't know an answer, it doesn't fabricate it, which is clearly unacceptable for any commercial or serious government application. After releasing the product in March, we rapidly closed three generative AI applications in the quarter with large enterprises, including Georgia Pacific, Flint Hills Resources, and the U.S. Department of Defense Missile Defense Agency. We expect these applications to be live during this current quarter. We are currently working on quite substantial pipeline of additional C3 generative AI opportunities with large corporations. The C3 AI generative application is now available, today available, on both the AWS marketplace and the Google Cloud marketplace. It is difficult to estimate the size of the addressable market for these generative AI solutions, but it appears to be extraordinarily large. We saw a lot of momentum last year and in the fourth quarter with our U.S. federal business. The U.S. federal sector represented 29% of our bookings in fiscal year 23, and it continues to show significant strength. Our predictive maintenance solution, our predictive analytics and decision assistant, also known as Panda, has been in production used for several years at the United States Air Force Rapid Sustainment Office. And last quarter it was selected as the system of record for all predictive maintenance for virtually all United States Air Force assets. This important designation expands our opportunity really substantially in the U.S. Air Force and other services. Let's talk about guidance. C3AI has a consistent and solid track record of meeting or exceeding guidance, as we have done in every quarter since we've been public. And we are, at this time, we are not inclined to pout on the table regarding guidance. In general, we feel comfortable with the expectations that the Southside analysts have set for the coming year, and we are not inclined to change those expectations at this time. For Q1, Fiscal year 24, we see revenue in the range of $70 to $72.5 million. For the full year of fiscal year 2024, we expect revenue to be in the range between $295 million and $320 million. As it relates to non-GAAP loss from operations, we expect to fall between $25 million to $30 million in Q1 and $50 million to $70 million for the year. As we begin fiscal year 24, C3 AI has never been better positioned. The addressable market is large and expanding. The overall business environment for enterprise AI is strong, and C3 AI is front and center in the minds of CEOs and government leaders. Our balance sheet is strong, and with over $812 million in cash and cash equivalent, we are in a great position to expand market share. As the dynamics of the enterprise AI market are developing so rapidly, we thought it appropriate to host a mid-quarter investor day in New York City on June 22nd. We will provide, at that time, we will provide C3 AI investors a company update, additional information about our product roadmap, product demonstrations, direct access to the C3 AI executive team, updates on our partner ecosystem, C3 AI technology, C3 generative AI demonstrations, and additional company developing news. We hope you can attend either in person or online, and that investor day event will be available to view online live for all investors via webcast. I will now turn this call over to my colleague, Juho Parkinen, Chief Financial Officer, for additional details regarding our financial results. Juho.
spk03: Thank you, Tom. I will now provide a recap of our financial results, add some color to the drivers of our financials, provide more detail on our first quarter and full year fiscal 2024 guidance, and I will conclude with some additional color related to the consumption-based revenue model we introduced three quarters ago. All figures will be discussed on a non-GAAP basis unless otherwise noted. Overall, the business activity is higher than we have ever seen. Our sales reps are more engaged, there are more opportunities they're working on, and there are more interest from our prospects. During Q4, our ability to close agreements was more consistent throughout the quarter compared to prior quarters this fiscal year. We ended the fourth quarter with a total revenue of $72.4 million, of which subscription revenue was 78.5%. As we discussed last quarter, we expected professional services would be within our historical range of 10% to 20%, with our actual professional services coming in at 21.5% of the mix. Gross profit for the fourth quarter was $53.9 million, and our gross margin was 74.4%. We generated $27.1 million in positive operating cash flow and $16.3 million in free cash flow for the quarter. As mentioned during the prior updates, we have a short-term pressure on our gross margins due to a higher mix of pilots, which carry a higher cost of revenue than production deployment. Operating loss of $23.5 million was improved due to more rigorous expense management. As a reminder, though, the fourth quarter is when we host our C3 AI Transform customer event. As such, our marketing expenses ramped up to support the successful execution of that event. Operating loss margin was 32.5% in Q4, where the sequential increase was driven by our annual customer conference. For the full year, fiscal 2023, our revenue was $266.8 million, an increase of 5.6% from fiscal 2022. Non-GAAP loss from operations was $68.1 million, and free cash flow was negative $187 million. Our gross margin for the year was 77%, Our subscription revenue was 86% of total revenue compared to 82% in fiscal 22. We ended fiscal 23 with $812.4 million in cash and investments. At the end of Q4, our accounts receivable, including unbilled receivables, was $134.6 million. Unbilled receivables at quarter end was $77.6 million, inclusive of $70.7 million created to Baker Hughes. During the quarter, we collected from Baker Hughes nearly $35 million. The general health of our accounts receivable is excellent. 76% of our receivables were current or less than 30 days past due. For the entirety of FY23, our bad debt expense was approximately $300,000. Now turning to RPO and bookings. As consumption-based go-to-market model continues to pick up, RPO is less important indicator of future performance. We reported gap RPO of $381.4 million, down 20% from last year, which is expected as a result of the transition to consumption-based pricing. Current gap RPO of $186.3 million is up 9.8% from last year and up 5.7% on a sequential basis. We continue to see positive trends in pilot bookings diversity as we have sold pilots to a broad range of nine different industries during the quarter. Regarding our outlook for fiscal 24, we're guiding Q1 revenue to range between 70 to 72.5 million. For the full year 2024, we expect revenue to range between 295 and 320 million. As it relates to the full year, we finished the third quarter of our transition under the consumption pricing model. As a returning model, we expect flatness and somewhat of a decline in revenue during the transition with an acceleration as consumption starts to have meaningful portion of our in-quarter revenue. As such, we expect the second half of FY24 to have higher growth rates on a sequential basis than the first half. We expect our non-GAAP loss from operations to range between 25 and 30 million for Q1, and for full fiscal 24, we expect non-GAAP loss from operations between 50 and 75 million. As a reminder, We expect to be non-GAAP profitable for Q4 24 and beyond. And as it relates to full fiscal 24, we are guiding to a range in operating loss due to the potential investments we may do for C3 generative AI applications. We expect our cash and investments to be at its lowest at around $700 million during fiscal 24. Turning to customer metrics. Historically, we have provided a quarterly customer count estimate as a proxy for the adoption of our products and solutions. However, due to the complexity of our contractual and pricing structures and the involvement of resellers, we believe comparing customer counts from quarter to quarter based on our current methodology does not fully convey the acceptance and adoption of our products and solutions. To help address this, we retained an external Big Four consulting firm to update our current customer methodology consistent with best practices to be consistent, systematic, and auditable. As a result of that review and adoption of those recommendations, we believe a metric that demonstrates contracted use cases that our customers are using our solutions to solve would provide a more meaningful understanding of the product adoption. This is defined as customer engagement. The customer engagement increased from 247 to 287, comparing Q3-23 to Q4-23. Our traditional customer count metric went from 236 to 244 for the same period. There will be additional detail included in the supplement, which is available on our website. We are on track with our plan for profitability for Q4-24 and expect to have cash positives quarter starting Q4-24 on a consistent go-forward basis. The entire executive team is managing the business to a detailed budget on our plan for profitability. We are expecting to invest aggressively to generative AI initiatives during the first half of the year, which is reflected in the operating income guidance. As it relates to the model assumptions that we provided three quarters ago for our consumption-based pricing, our preliminary analysis of the actual results suggests we are on that model. Overall, we're very excited about the business momentum as we start FY24. As a go-forward KPI for the investing community to assess our performance, we believe good KPIs to focus are the number of pilots started during the quarter, the conversion of those pilots to production, and finally, the actual vCPU consumption fees generated. With that, I would like to open this up for questions. Operator?
spk20: Thank you. Ladies and gentlemen, if you'd like to ask a question, please press star 11 on your telephone. Again, to ask a question, please press star 11. One moment for our first question.
spk23: Thank you.
spk20: Our first question comes from the line of Kingsley Crane of Canaccord. Your line is open.
spk08: Oh, hi. Thanks for taking the question. So, Tom, you said that sales cycles were down to 3.7 months from five months last year. Why do you think that is? Is this entirely due to the consumption model? How much of this is due to general excitement around the potential in the space? and even potentially increase Salesforce productivity.
spk15: Thanks, Kingsley. I think it's all of that. I mean, clearly, AI is on everybody's mind. The consumption-based pricing model that we have makes it much easier to adopt our technology. I mean, in the old days, you know, one and two years ago, to do business with us was, you know, $5, $10, $20, $50 million to open the door. And now the transaction is pretty much, you know, we'll bring the application live in six months for half a million bucks. If you like it, keep it. And pay $0.35 per CPU hour, since we're pretty easy to do business with. And so we're seeing the number of transactions increase dramatically, as we'd expect. The, you know, the ease of contracting with us, as you know, We have largely reconstituted the sales organization the last year and a half to a sales team that is candidly much more productive and effective than our other sales organizations. So I think all of those are contributing to increased pipeline, increased business, increased business activity, about which we're quite optimistic.
spk08: Thanks, Tom. That's really helpful. And then one for Juho. I want to think about the timing of the transition. So if it is the case that the vast majority of existing customers are not necessarily migrating to the consumption model, how should we think about the contribution of consumption over time and then particularly in the back half? Because I think that you said, you know, revenue could accelerate as consumption increases and mixes.
spk03: Yeah, Kinski, thanks for that question. So that's exactly, as we sign and initiate more PYGOTs within the quarter, the PYGOTs are generally two quarters long, and then you start to see the consumption revenue kick in. As we finished the quarter with 19 PYGOTs last quarter, we had a good increase in PYGOTs at 17 PYGOTs as well. You can start seeing those layer on to the revenue by Q3 and Q4 of this fiscal year. Now, to your point about renewals, we do expect our existing customers with the large enterprise agreements to continue to remain on those types of agreement structures, but you will see the RPO trickle down as these contracts enter into renewal phase, and then we would expect to see a pickup as they renew.
spk07: Okay, very helpful. Thank you.
spk20: Thank you. One moment, please. Our next question comes from the line of Pat Walraven of JMP Securities. Your line is open.
spk16: Oh, great. Thank you. Tom, can you talk some more about the opportunity with national security and the Department of Defense? And then also you said something I thought was interesting about a version of generative AI that doesn't hallucinate. If you could maybe comment a little more on what hallucinating is and how you prevent it from doing that. I think that would be really interesting. Thank you.
spk15: DOD, well, Pat, you've asked kind of many times about the – we have two basically authorities to operate contract vehicles, one's for $100 million and one's for half a billion in DOD that are associated and it could be applicable to what we're doing at RSO. That was the Rapid Sustainment Office and the predictive maintenance application that we're doing for the United States Air Force for DOD. F-15, F-15, F-18, F-35, KC-135, et cetera. And we made a proposal to the Secretary of the Air Force to take that into full production for all the aircraft in the Air Force, which is 5,000. And I think the proposal would have increased aircraft availability for the Air Force by 25%, and I think decreased their cost of maintenance and readiness by about $6 billion. So he considered that, as did his chief of staff, General Brown. And they went off on their own for a few months while you were asking them the questions, and we didn't have the answers. And these guys go into their star chamber the way they do. What they came out with was a selection of C3 as the system of record. not only for aircraft in the United States Air Force, but for all AI-based, all predicted maintenance, okay, in the United States Air Force for all assets. So this is genuinely a big deal. Okay, now we have the opportunity to make this a line item in the budget. So this is, you know, it's hard to, you know, over-describe the impact of this or over-estimate the impact of this. And then not only do we have it in the Air Force, we can talk now to other services like the Army and and the Navy and the Marines and the National Guard and what have you. So this is a big one. The second one has to do with generative AI. So one of the problems with generative AI is you're limited to the number of data sources that you can use with these large language models. Typically it's text, HTML, or sometimes code. And the large language model will interact directly with the data. Well, one of the problems is you get kind of random answers. You know, every time you ask the question, you get a different answer. If two people ask the same question, you get a different answer. And there's no traceability. It doesn't tell you where the answer came from. And finally, if it doesn't know the answer, it makes one up. This is what they call hallucination. So it doesn't know, so it just kind of wings it and makes up an answer. So we're using the entire C3 platform And the way that we do that is we incorporate, as you, I think, all know, we're very good at aggregating enterprise data, extra price data, code, images, text, sensor data, what have you, into a unified federated image. Now, when we do that, those data are read by a deep learning model, and they happen to be stored in a vector database. then we have a kind of a firewall between that and the large language model. Now, our customer can use any large language model they want, be it chat, GPT, be it Palm, be it BARD, be it Plan T5, whatever comes along next. But we've built a firewall between the large language model and the data. So every time you ask the question, it will give you the same answer. okay if two people ask the same question and they have the authority they will both get the same answer every time associate with the answer it provides you traceability so you can click on it you can see exactly where the data came come from okay and again very importantly there's no risk of llm caused data exfiltration see samsung for details where they find out that all of their proprietary information is not published on the internet okay and Finally, there's no risk of LLM caused hallucination. If it doesn't know the answer, it tells you I don't know the answer rather than making one up. So, you know, for these you'd think would be kind of table stakes, and they are table stakes for any large commercial or government installation, and this is something that really distinguishes the C3 generative AI offering and one of the reasons that we're seeing, you know, very high levels of interest.
spk16: Oh, great. Thank you.
spk20: Thank you. One moment, please. Our next question comes from the line of Sanjit Singh of Morgan Stanley. Again, our next question comes from the line of Sanjit Singh of Morgan Stanley. Your line is open.
spk17: I appreciate you guys squeezing me in for the question. Tom, you know, earlier this week you guys announced how to press release about the C3 General AI Suite being available in the Amazon Marketplace. And it got me thinking about what the sales motion going forward is going to look like. As you sort of mentioned, General AI is permeating the boardroom, the C-suite, in a pretty substantial way. And when we look at sort of converting this interest into deals and ultimately revenue, how much of this is going to be like flywheel kind of, self-service, consumption-based marketplace-type deals versus you working with partners, taking a more consultative approach and helping, you know, these large enterprise customers sort of navigate the world of generative AI and actually deliver value?
spk15: Great question, Sanjit. So our first three engagements that are involved in now will be our organizations, the order of a hundred billion or greater in revenue. Okay. And have, you know, we'll bring the application alive in 12 weeks. We're not doing it within a game with, and we have like three people on the project. So it's pretty straightforward. Now the, The issue of going from, say, six customers to 60 customers to 100 customers is pretty straightforward. We know how to do that. The real key is, in terms of blowing the doors off this thing, can we go from six customers to 60 customers to 6,000? For 6,000, now we have to leverage these channels like the AWS marketplace where the product's available today, the Google marketplace where they're available today. But in terms of usability, it needs to be like the Apple iPhone. You open the box, you take the cellophane off, you turn it on, and it works. And so now we're the next generation, the really serious development work that we're doing now on that product kind of relates to really product design and making it like an Apple product. You open it up, you turn it on, and it works. And so that's the challenge that's before us. I think we're up to it. And if we're able to hit that note, hold on to your socks.
spk17: I appreciate the color, Tom. And then maybe one follow-up. Maybe this is for Jill and Tom as well. And it sort of relates to the guidance for the full year. I'm trying to, you know, contextualize, like, what's really driving the guidance for next year because we're coming off a year, fiscal year 21, I think you guys grew north of 30%, 33%, 34%. This past year, you guys grew sort of mid-single digits. The initial guidance calls for growth sort of mid-teens at the midpoint, sort of 20% at the high end. And I want to understand, like, is the acceleration you're seeing a function that you're coming off, you know, a tougher year where you had, you know, spending environments were difficult, sales reorg, those types of things, versus, you know, generative AI really coming online in fiscal year 24. And so is there any way you can sort of, you know, attribute, you know, those two things between sort of coming off of, you know, a tougher year versus, the demand that you're seeing in pilots and out in the field.
spk14: Let me address the premise. Before we all wring our hands about your tougher year, tougher year, tougher year, I think we got that in four times in the call for all the audience.
spk15: Let's remember, when we announced the transition to consumption-based pricing, we made it very clear that this was going to have a short and mid-term Okay, negative effect on revenue growth. It's actually a mess. Anybody who knows how to use a spreadsheet can figure this out. If we're closing half a million dollar deals instead of 10, 20, 30, 40, 50 million dollar deals, the short-term impact on revenue is to dampen revenue growth. So I'm not certain that's so tough. Okay, that is basically we're actually getting exactly to the plan that we set. So this thing is exactly on track. Now, when you run this two-year little extra spreadsheet model and you hit the carriage return, okay, and you run it out a few years, you know, a few quarters out there, you know, you can do the math and you know what happens. But I'm not, you know, so I think we're exactly on plan with what we did. We made the investment. I think it was a great decision. It was a good investment. And now in fiscal year 24 and 25, we're going to yield the returns from that investment.
spk19: Great. I appreciate the thoughts. Thank you. One moment, please.
spk20: Our next question comes from the line of John of Web Bush. Your line is open.
spk13: Hi. Thanks for taking my question. This is John for Dan Ives. So given the increased diversity seen, I guess, across industries served, how have you seen these use cases develop, and how do you see them playing out? Thank you.
spk15: Great question, John. Well, right now, you know, I mean, in terms of applying AI to enterprises, we're in, you know, first half of the first inning and, you know, the first guys at bat. OK, so this is an embryonic market. I mean, where we're seeing the biggest uptake immediately. First, it was in the smart grid. Okay. Why the smart grid? Because they had invested $2 trillion of the upgrade and get it good infrastructure globally to make all the devices in the smart grid, uh, remotely machine addressable is a huge IOT constellation. So that's where we saw it first. The next large, where we're seeing it in the past year, the largest market is in AI reliability, basically predicted maintenance. So then in the military, they called readiness. Okay. Or in the private sector, they call reliability. So AI-based predictive maintenance is the largest segment today. How will this evolve? I mean, it's clear we will be applying AI to all business processes. Production optimization, demand forecasting, supply chain risk, okay, stochastic optimization of the supply chain, you know, CRM. I think there is no aspect of business operations that will not be – okay, and medicine – okay, and research and the science and literature and entertainment that will not be accelerated by the use of AI. So we're just going to have to, we're along for the ride and going to see where this goes in the next few years and stay on the balls of our feet as it develops, but it is a rocket ship. Thank you, Tom.
spk20: Thank you. One moment, please. Our next question comes from the line of Mike Sikos of Needham Company, your line is open.
spk06: Hey, guys. Thanks for taking the questions here. Maybe the first would be going to you, Ho. So I know that you guys incited the 43 deals you closed this quarter. Nineteen of those are pilots. Can you further refine that for us? And maybe it's just the classifications or names we're using for this, but, like, how many of those pilots are purely consumption-based? versus maybe pilots that are still coming in under the old pricing model?
spk03: Hi, Mike. These would all follow the new consumption-based approach. These are not under the old model at all.
spk06: Okay. And so I guess the follow-up that I have on that is with the 19 deals that are consumption-based, and I know that you guys have called – I'm sorry, 19 pilots that you guys closed that are initiated that are consumption-based this quarter – and the other pilots that we've cited in previous quarters, do we have a feel for how many of these pilots have now converted to production? And do we have a gauge for what the BCPU is for those consumption deals once they move into production?
spk03: That's a great question. So, Mike, on the first quarter we announced this would have been Q2, which obviously if you take six months from that, we get towards the end of Q4. So, we are very early in that. uh in in in in the conversions we are standing by with the model assumptions i.e whatever we provided three quarters ago where it is each pilot is expected at 70 likelihood to convert into a follow-on consumption deal but i would say that the first quarter um for consumptions we really will start seeing more of that this quarter since it was late in q2 as we entered into those original pilot arrangements.
spk05: Understood. Understood on that.
spk06: Thanks for that. And then just one quick follow-up, if I could, but I wanted to ask, just on the professional services revenue, I know it's a tick higher versus that typical 10% to 20% range we've been talking about, and I just wanted to see, is 10% to 20% still the appropriate range we should be thinking through, or is there maybe more hand-holding for these pilots as you guys engage in them, or is it maybe hand-holding of potentially federal sector customers? How do we think about the higher pro-serve revenue generation in Q4 versus what you guys are thinking about over the next year?
spk03: I think on a go-forward basis, we expect to be in the 10% to 20% range. There's always going to be these types of projects that our customers want, but it's difficult to forecast a specific percent in a go-forward revenue, but we believe 10% to 20% is appropriate on a go-forward basis.
spk06: Thank you for that. I'll turn it back to my colleagues. Appreciate the time.
spk20: Thank you. Again, ladies and gentlemen, if you'd like to ask a question, please press star 11 on your telephone. Again, to ask a question, please press star 11. Our next question comes from the line of Brad Sills of Bank of America. Your line is open.
spk11: Hey, great. Thank you. This is Adam Brashear on for Brad Sills. So you're pretty well positioned in the current market, just given, you know, AI use cases are coming into focus. I'm kind of curious if this has changed your cadence for R&D investments at all.
spk15: Well, this is Tom. I mean, clearly the investments we've made in the last 14 years are paying off, okay, in that we have over 40 applications, and people want applications, and I think we're the only company in the world that has 40 applications. I think the only recent change that we've made is we're a little bit shocked by the response that we had to C3 generative AI. I mean, we're a little bit overwhelmed by that. That's a big opportunity. And so now we just came off of Planet Mean, and we decided to really invest in that product category in a big way because it's you know, it's just difficult to estimate the size of that market, but it's extraordinarily large.
spk11: Yep, fair enough. And then for, you know, kind of degenerative AI use cases and solutions thus far, you know, I guess the first, you know, this is your first take on it, but do you see any, you know, outsized uptake, you know, or expect any outsized uptake within certain verticals over others in your view? Thank you.
spk15: You know, it's a good question. It kind of seems like everybody is interested in this. They want, you know, at the level of the CEO or the person who operates manufacturing and the person who operates sales, they want basically a Google-like interface where they're getting a web browser-like interface where they can ask any question about their business. Okay, where are the problems in our supply chain? If I'm the chair of the Joint Chiefs, what are my readiness levels? We have 35 squadrons in Central Europe. I mean... that's what we call Google for DOD, but their open AI initiatives can provide the Secretary of Defense or the Chair of the Joint Chiefs of Staff answers to that question in seconds. Right now, it actually takes weeks for him or for most people to get those answers. So I don't know any industry that will not be taking use of this technology. It's really quite amazing.
spk11: All right. I appreciate the perspective, Tom. Thank you.
spk20: Thank you. One moment, please. Our next question comes from the line of Mike Sikos of Needham Company. Your line is open.
spk06: Hey, guys. Thanks for getting me back in. I did just have one quick follow-up. Maybe building on the question that Sanjay had asked earlier, but taking a different look. Rather than looking at the revenue, let's talk profitability for a second. But Obviously, you guys are issuing guidance now, which is below street and below what you guys had initially flagged if we go back a quarter ago, maybe for you, Ho. Can you help us think about the additional levers you have to pull on to ensure that C3 is achieving its target of exiting fiscal 24 with non-GAAP profitability?
spk15: Before we answer it, Mike, I do want to poke at the premise a little bit. I think our guidance is pretty much in line. with what the street expectations are once you take out like one outlier or two outliers. So I think our current guidance is in line with what the street currently has. I'm pretty confident of that.
spk03: Now, the other question related to how are you sure you're going to get to profitability? Right. So, Mike, one of the things that I had on the prepared remarks was our planned investments into generative AI, which combined that and vendor expenses, I think we can control spending towards the end of the year if, for whatever reason, the expected revenue would not occur from those. But we're pretty bullish about the generative AI opportunity.
spk06: Got it. Thank you very much.
spk15: That being said, we don't need the generative AI opportunity to be – generative AI could be zero, okay, and we're still going to run a cash-positive profitable business in Q4. Well, we have a very, very detailed plan that's been distributed to all the members of the management team. They all have big budgets. They know that it can operate. You can expect it to be a cash-positive, profitable business and non-gap profitable business in Q4, hard stop. That's right.
spk20: Thank you.
spk21: One moment, please. One more question.
spk20: Thank you. Our next question comes from the line of Noah Harmon of J&P Securities. Your line is open.
spk02: It was great to see, you know, the average sales cycles for agreements tick down, I think, by about 1.3 months year over year. You know, what's really driving that? And, you know, where do you think, you know, a sustainable, you know, sales cycle, you know, basically concludes that, maybe thinking about the rest of this year.
spk22: Thanks.
spk15: Well, I think the consumption-based pricing model is driving it, where it's pretty easy to adopt when you can have a large-scale enterprise AI application live in production in six months for half a million bucks. I mean, that's nothing, guys, in terms of what it costs to bring in an Accenture or an IBM or somebody to try to bring one of these things live. That's going to be scores of millions of dollars in years. So it's a pretty easy sale. It's a shorter sales cycle. And, um, you know, so, you know, I'm not sure where, where it ends up, but, you know, as, as we move more and more of our products onto the AWS marketplace, the Google marketplace and other, other, you know, leverage channels like this, you know, we'd expect to see it, you know, get shorter.
spk22: Great. Thank you. Thank you.
spk20: Thank you. I just want to turn the call back over to Mr. Siebel for any closing remarks.
spk15: Ladies and gentlemen, we thank you so much for your attention today. Thank you for tuning in. I encourage you to mark your calendars for June 22nd. I think you'll find that that we'll talk about some interesting developments at our investor conference at that time, and we hope you'll have time to join us for that exchange. So thank you very much for your time today, and we wish you all a good night.
spk20: Thank you. Ladies and gentlemen, this does conclude today's conference. Thank you all for participating. You may now disconnect. Have a great day.
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