C3.ai, Inc.

Good day and thank you for standing by and welcome to the C3AI four-quarter fiscal year 2021 earnings call. At this time, all participants are in a listen-only mode. After the speaker's remarks, there will be a question and answer session. To ask a question during the session, you will need to press star 1 on your telephone. Please be advised that today's conference is being recorded. If you require any further assistance, please press star 0. I would now like to hand the conference over to your speaker today. Paul Phillips, please go ahead.

Good afternoon and welcome to C3AI's earnings call for the fourth quarter and full year fiscal 2021, which ended April 30th, 2021. This is Paul Phillips, VP of investor relations of C3AI. With me on the call today are Tom Siebel, chairman and chief executive officer, and David Varner, chief financial officer. After the market closed today, we issued a press release with details regarding our fourth quarter and full-year fiscal results, as well as a supplement to our results, both of which can be accessed on 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 relating 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 of the material risks and other important factors that could affect our actual results, please refer to our filings at the SEC. 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 comments or response to your questions, we may discuss metrics that are incremental to our usual presentation to provide greater insight into the dynamics of our business or our annual results. Please be advised that we may or may not continue to provide this additional detail in the future. With that, let me turn the call over to Tom for his prepared remarks.

Tom? Well, thank you, Paul, and good afternoon, everyone. I am very pleased to give you an update on the state of the business. Bottom line, Q4 was a great quarter, and fiscal year 21 was a great year. I'm pleased to report that C3 AI is well positioned to substantially accelerate growth and continue to gain market share in the coming year. Let's talk about our fourth quarter results. We exceeded our guidance for both revenue and non-GAAP operating income. Our bookings grew, believe it or not, over 500% in Q4 compared to the quarter a year earlier. Our bookings grew 179% quarter to quarter. Revenue in the fourth quarter was $52.3 million, an increase of 26% year over year. Subscription revenue for the quarter was $43.1 million, up from $36.8 million a year ago, an increase of 17% year over year. Gross profit for the quarter was $40.6 million, a 78% gross margin, compared to $32.1 million gross profit a year ago, an increase in gross profit of 26% year-over-year. Our remaining performance obligations were $293.8 million compared to $239.7 million a year earlier, an increase of 23% year-over-year. including cancelable orders, our non-GAAP RPO was $345.1 million compared to $246.9 million a year ago, an increase of 40% year over year. Our total enterprise AI customer count at the end of the year was 89, representing an 82% growth rate year over year. Now, let's take a look at fiscal year 21 in entirety. Total revenue for the year was $183.2 million, up from $156.7 million a year ago, an increase of 17% year over year. Subscription revenue for the year was $157.4 million, up from $135.4 million a year earlier, an increase of 16% year over year. Subscription revenue, importantly, subscription revenue as a percentage of total revenue remained 86% constant year over year. Gross profit for the year was $138.7 million, a 76% gross margin, compared to $117.9 million gross profit a year ago, an increase of 18% year over year. Most importantly, Our average contract value for the year continued to decrease from $16.2 million in fiscal year 19 to $12.1 million in fiscal year 20 to $7.2 million in fiscal year 21, providing smoothing growth in bookings and greater revenue visibility going forward. We experienced continued customer momentum in the course of the year accelerating in the half of the year specifically in the fourth quarter we expanded our enterprise ai footprint in defense and intelligence financial services manufacturing oil and gas utilities and energy sustainability We had a number of new enterprise production application deployments at the United States Air Force, Bank of America, Standard Chartered Bank, Koch Industries, Meg Energy, Duke Energy, and Engie. C3 AI also initiated new enterprise AI projects with 3M, Con Ed, FIS, Infor, Koch Industries, New York Power Authority, and Shell. and signed new contracts with Commonwealth Bank, George Washington University School of Medicine and Health Sciences, NCS, One Medical, San Mateo County, Stanford Healthcare, Swift, and Yokogawa Electric Corporation in Japan. We enjoyed substantially expanded business agreements with existing customers, including the United States Air Force, the U.S. Military Rapid Sustain Office, and the F-35 Joint Program Office. Importantly, Shell executed a very significant expansion that spans slightly in excess of five years to significantly accelerate the deployment of C3 AI and ML applications across Shell global assets. This represents significant a major expansion of the partnership that C3 AI and Shell have forged over the past several years. Again, importantly, the total number of C3 AI customers at the end of the year was 89, up from 49 at the end of the previous year, an 82% increase year over year. We continue to expand our partner ecosystem to extend our global distribution and service capabilities. During the quarter, C3 expanded its relationship with strategic partner and financial technology leader FIS to launch joint solutions for the financial services industry, including FIS credit intelligence powered by C3 AI. And this builds upon the previously announced launch of FIS AML, or Anti-Money Laundering Compliance, powered by C3 AI. The company saw continued success in its partnership with Baker Hughes, exceeding its fiscal year 21 revenue target for the alliance. The company formed a wide-ranging strategic alliance with Infor, an ERP technology cloud leader, to jointly expand enterprise-class AI solutions across industries and extend Infor's native machine learning capabilities. Let's talk a little bit about product and technology. It is difficult to overstate the significance of the rate of innovation in product engineering at C3 AI. As of the end of Q4, we have released 20 enterprise AI applications into general availability across five vertical markets. This in addition to the C3 AI suite itself. In the course of the fourth quarter alone, we released 40 updates and upgrades to these applications. And to give you a feel for the complexity of some of these deployments, we update one of our larger deployments in excess of 320 million times per day. Operating at now massive scale, as of the end of the year, the C3 AI suite and applications were integrated with more than 800 unique enterprise and enterprise data sources and sensor constellations. We managed more than 4.8 million concurrent production AI models We process more than 1.5 billion AI predictions per day, and we evaluate over 30 billion machine learning features daily. Our service levels remain superlative, offering our customers 99.99% product availability with exceptional performance characteristics for the C3 AI suite over the course of the year. Ladies and gentlemen, this would constitute the gold standard in the software industry. The production release of Ex Machina, serving the needs of the citizen data scientist, opens a new, large, and rapidly growing marketing opportunity for C3, previously served by Alteryx. For those of you interested, I encourage you to go to our website and sign up for a free trial of Ex Machina. If you like it, buy it. I am most enthusiastic about the advancements we are making in C3 AICRM. AICRM represents the next generation of the now $80 billion addressable CRM market. I'm a market segment that I'm confident we will lead. Keep your eye on this space. You can expect a number of exciting announcements and product releases from C3 in the coming year. With Shell and Microsoft, C3 AI expanded the OpenAI Energy Initiative, an open marketplace for C3 AI applications. Announced in February, the OpenAI Initiative accelerates the deployment and availability of enterprise AI solutions to the energy industry. by providing a framework for energy operators, service providers, equipment providers, and independent software vendors to offer interoperable solutions powered by the C3 AI Suite and Microsoft Azure. Fiscal year 21 was a great year for C3 AI. The enterprise AI software market is rapidly growing. and we see accelerating interest in enterprise AI solutions across industries, geographies, and market segments. We are aggressively investing to extend our product and technology leadership, to expand our market partner ecosystem and associated distribution capacity. As we continue to execute on delivering high-value outcomes for our customers, we are increasingly well-positioned to establish a global leadership position in enterprise AI application software. Bottom line, performance was strong across the board, and we're planning for accelerating growth in the coming year. And with that, I'll turn it over to our CFO, David Barter, for more complete color on the quarter and the year. David.

DAVID BARTER Thank you, Tom. We exceeded our guidance for both revenue and profitability in the fourth quarter, while also building significant backlog that will help drive future growth in fiscal year 2022 and beyond. Revenue in the fourth quarter was $52.3 million, up 26% from a year ago due to increasing demand for our enterprise AI applications, with particularly strong deal volume late in the quarter as reflected in our accounts receivable, deferred revenue, calculated billings, and remaining performance obligation. Our fourth quarter revenue growth is a meaningful improvement over the 19% growth in Q3 and the 11% growth in the first half of the fiscal year, which reflected the impact COVID had on our business. Subscription revenue increased to $43.1 million in the fourth quarter, while professional customer implementation activity and engagement with Baker Hughes that will make our virtual data lake and reliability applications even more compelling for oil and gas customers. In Q4, 82% of our revenue was from subscriptions and 18% was from professional services. On a full year basis, 86% of our revenue was from subscriptions and 14% was from professional services, consistent with our revenue mix in fiscal year 2020. However, there may be some variation in the revenue mix quarter to quarter. Our revenue growth was highlighted by contributions from eight different industry verticals, including some newer verticals such as high tech, life sciences, financial services, and telco. Over the course of fiscal year 2021, these newer verticals contributed 17% of revenue compared to 8% in fiscal year 2021. Geographically, our revenue diversification also increased as activity in EMEA and APAC continued to expand. On a full year basis, EMEA and APAC drove 34% of our revenue, compared to 22% in the prior year. Our sales execution in Q4 also drove a meaningful increase in our contracted backlog. Total remaining performance obligation, or RPO, at the end of the quarter was $293.8 million. an increase of 23% from a year ago, and a 19% sequential increase from the third quarter. Current RPO, which we expect to recognize in the next 12 months, was $145.2 million, an increase of 11% from the prior quarter. In addition, we had $51.3 million of additional contracted backlog from contracts with a cancellation right. When combined with our GAAP RPO, This produces a non-GAAP RPO of $345.1 million. Our non-GAAP RPO grew 40% from a year ago, and this represents a sequential increase of 17% from the third quarter. It's important to note that our non-GAAP RPO does not include any backlog associated with Baker Hughes that does not have an existing customer contract. This commitment at the end of the fourth quarter was $219.3 million. And it leads to an adjusted RPO of $564.4 million, an increase of 31% year-over-year. Before moving on, I'd like to provide a brief update on our performance in oil and gas. Our revenue related to the Baker Hughes market partner relationship was $55.9 million, and it exceeded its revenue commitment of $55.3 million. revenue generated in fiscal year 2020. In our financials, a portion of the Baker Hughes partner revenue is reported as related party revenue as it is contracted directly with Baker Hughes, and the balance of the revenue reflects situations where C3AI has a contractual relationship with the end customer, but Baker Hughes assisted with the sales process. In the fourth quarter, the related party revenue was 13.8 million dollars, and the non-related party component was 8.7 million dollars. was $35.4 million, and the non-related party revenue was $20.5 million. Turning to expenses and profitability, I will be referring to non-GAAP metrics, which excludes stock-based compensation expense and the employer portion of payroll tax expense related to stock transactions. A GAAP to non-GAAP reconciliation is provided with our earnings press release. Gross margin in the fourth quarter was $7 For full fiscal year 2021, our gross margin was 76.4%, up from 75.6%. The margin expansion over the year was driven by subscription gross margin, which increased to 80.6%, up from 77% in the prior year. Our operating loss was $15.4 million in the fourth quarter, and favorable to our guidance of a loss of $28 to $27 million. In the fourth quarter, headcount increased by 56. an 11% sequential increase compared to the third quarter. For the full fiscal year, headcount increased by 134, a year-over-year increase of 30%. We thoughtfully invested throughout the year, and we will continue to invest with focus on expanding our market leadership position as we scale our business. Shifting to our balance sheet and cash flows, we ended the year with $1.09 billion in cash and cash equivalents and investments, compared to $1.12 billion at the end of the third quarter. We had an operating cash outflow of $31.7 million in the fourth quarter, including capital expenditures of $462,000. Free cash flow was an outflow of $32.2 million in the fourth quarter. For full fiscal year 2021, operating cash flow was an outflow of $37.6 million, and free cash flow was an outflow of $39.2 million. Reflecting on the deal activity in the fourth quarter, accounts receivable increased to $65.5 million, up 112% over the fourth quarter in the prior year. Deferred revenue grew to $75.2 million, a healthy 25% increase from the end of fiscal year 2020, as well as a 21% sequential increase from the third quarter. Now, turning to our guidance for fiscal year 2022 and the first quarter. We're beginning the year with a healthy, contracted backlog. As I mentioned earlier, current RPO increased sequentially 11% last quarter, and our non-GAAP RPO increased 17% sequentially. This level of growth provides us with meaningful revenue coverage. In Q1, we expect subscription revenue will continue to expand, and our subscription revenue mix will climb back to prior year levels. We also expect approximately $2 million less of professional services revenue in Q1 when compared to the prior quarter. On a full-year basis, we expect our subscription revenue mix to increase slightly year-over-year, given our focus as a software company. Gross margin will continue to expand. It's important to keep in mind C3.ai has been designed to be a structurally profitable business. We expect gross margin to expand by another point in the coming year, driven by the growth of our subscriptions. And finally, it is worth be higher in Q1, and then it will be more balanced for the remaining quarters of the year. With that in mind, for full fiscal year 2022, we anticipate revenue to be in the range of $203 to $247 million, non-GAAP operating loss in the range of $119 to $107 million. For the first quarter of fiscal year 2022, we expect revenue in the range of $50 to $52 million, and non-GAAP operating loss in the range of $35 to $28 million. In summary, we exceeded our guidance for revenue and operating income in the fourth quarter. With our growth initiatives well underway and the increasing demand for our technology, we believe we are in a strong position to deliver an even better performance in fiscal year 2022. Thank you for joining today's call. Now I'll turn the call over to the operator for questions. Operator?

Thank you. At this time, I would like to remind everyone, in order to ask a question, press star and then the number 1 on your telephone keypad. Again, that is star and then the number 1 on your telephone keypad. We'll pause for just a moment to compile the Q&A roster. We have our first question coming from the line of Daniel Ives with Wedbush. Your line is open.

Yeah, thanks. Can you talk, Tom, just about success that you're having, vertically speaking, when I think about utilities and oil and gas versus financials? Are you starting to see just more and more penetration across verticals from a customer base?

Well, yes. I mean, we began, we had a huge concentration in utilities, as you will recall. Then a couple of years ago, we went into the oil and gas business, and now that's a pretty big chunk of our business. We're seeing initial success that's quite significant in financial services with Bank of America and Standard Chartered Bank. And now with the relationship with FIS and a number of discussions we have going on in the world, we expect to see substantial expansion of financial services as our products are used for anti-money laundering, customer churn, cash management, vocal rule compliance, margin lending. Manufacturing remains a big business for us, particularly as it relates to stochastic optimization of the supply chain, production optimization. I mean, we're clearly diversifying across a wide range of industries, and I think we'll see increasing diversification both in terms of additional industry segments and a wider range. Instead of only doing very, very large deals like we did three and four years ago, now we have a mix of large deals, medium deals, and small deals that is resulting in substantial reduction in our average contract value. So, you know, as this plays out, just like the relational database business did and the mini computer market did and CRM did, I think that, you know, enterprise AI will be adopted across all sectors, precision health, travel, transportation, aerospace, you name it. And we expect to play in all those sectors.

Great. And just a quick follow-up. Can you just talk about, from a conversation that you're having with customers when you're talking to CIOs, CEOs, how it's changed in terms of where C3 stands today versus even six months ago or a year ago? I mean, has it really gone from just more strategic and it's almost more of a pull versus a push? Can you just compare and contrast especially? just given what you've seen the last 30, 40 years? Thanks.

Well, you know, I think we really hit an inflection point after, you know, I mean, the first two quarters of this calendar year were, excuse me, calendar year 20, okay? We're tough, right? And, you know, we were doing these large enterprise transactions, and then COVID hit, Paris closed, Rome closed, London closed, New York closed, Chicago closed. And so, you know, that did slow us down. Now, when we get into, you know, May, June, July of last year, we saw dramatic acceleration. And, you know, this mandate towards digital transformation seems to have made it at the top of everybody's agenda. Digital transformation is very much about the application of enterprise AI to make stuff more efficiently, plan stuff more efficiently, deliver higher quality products into the hands of more satisfied customers at lower cost. We are clearly more credible today in the market than we ever have been. I think that You know, I think we're doing a pretty good job of demonstrating thought leadership in AI. The work that we're doing with major research institutions like, you know, Illinois, Carnegie Mellon, Princeton, MIT, Stanford, Berkeley, KTH is kind of really helping us at the high end. But, you know, now we have, you know, production use cases in, you know, all over the place in utilities, all over the place in manufacturing, in financial services, in aerospace. And so the pipeline has never been larger, okay, and the sales cycles are shorter than they have ever been. So right now we're pretty optimistic about what the next coming two years look like.

Great.

Thanks.

We have our next question coming from the line of Brad Silves with Bank of America. Your line is open.

Oh, great. Thanks, guys, for taking my question. I wanted to ask one just about the general environment for AI and the sales audience. Are you seeing a change where now your deals are sponsored more by a data scientist owner, if you will, or is it still very much a CIO sale? Is it a line of business? As AI becomes more at the forefront of critical capabilities for these companies, is the sales audience changing and are you seeing that more pervasively through these organizations?

It's a good question, Brad, and I think it is changing. If you see the uptake on Ex Machina, they were selling to basically individual data scientists and citizen data scientists at all these organizations like $500 at a time or something. And, you know, the uptake there is pretty substantial. But I would say it varies from organization to organization. Some places it's starting in divisions. At other places, like Bank of America, it's starting at the very top or, you know, ahead or near the top. So it, you know... Whether we start at the bottom or we start at the middle, we seem to make it to the top sooner or later. And whether it's Bank of America, Standard Chartered Bank, or Coke, you know, this is a rapidly growing hot market with a lot of people really interested in And they've been – I think they're a little bit frustrated with what they've been attempting to accomplish in the last three, four, five years but haven't been able to accomplish. So we present the prospect of being able to fix that, and business is good.

That's great. Thank you, Tom. And then one more, if I may, please. As you've pivoted towards these smaller deals, smaller land deals, What does that mean for the expansion opportunity? How is that different from some of these larger deals where you land bigger? Should we see a greater velocity of expand deals in some of these early wins that perhaps are smaller in footprint? Thank you so much.

Oh, I think it's a really good question. And the answer is yes. I mean, as you get into, you know, selling to small and medium businesses, selling CRM, selling ex machina, I mean, there you're selling, you know, $500, $1,000 at a time. And, you know, it becomes a NRR game. And, you know, NRR has been really less important as a metric for us historically because we were landing contracts that were, you know, so long in duration and so large. I mean, you can remember in, you know, fiscal year 18 and 19, you were here when we were doing, you know, $30, $40, $50 million deals all the time. And, you know, that's clearly changing now. So I think it's a healthy mix of large deals, medium deals, and, you know, and, you know, The minimus transactions, I would say, you know, $500 a month, you know, by our standards is certainly the minimus. But, you know, it certainly looks good in the long run in terms of evening out, you know, getting the lumpiness out of bookings so we don't have to deal with that anymore.

That's great. Thanks, Tom.

Thank you. We have our next question coming from the line of Michael Turrett with KeyBank. Your line is open.

Hey, Tom, can you just give us a little bit more on the Shell deal? Is it an expansion? How does it impact if it does revenue going forward?

Well, it is revenue, and it's more revenue, and it's more revenue. So I think the existing contract that we had in place was Shell, Michael, and I could be wrong on this. I think it was the second or third contract, okay? And it was about four years in duration. Originally, we did a couple of production trials with them. I forget what year, and those were successful. And then they expanded to kind of a small enterprise deal. Then they expanded to a larger enterprise deal, which was three or four years in duration. Now, Shelley is very much reinventing itself. around all aspects of its business with this initiative they call Shell AI, which is a combination of basically C3 AI sitting on top of Azure and then a number of very, very bright people who are applying AI to basically all aspects of Shell's business, upstream, downstream, midstream, and really importantly, renewables. I think by 2050, you know, I'm not really privy to all of Shell's company, all of Shell's strategy, but it looks to me like it might become an electricity business. Anyhow, they were deploying many, many successful applications. They decided to renew their application a year before it expired, and so they entered into a new five-year relationship with us to kind of dramatically expand the number of assets to which they can apply the C3 applications and the C3 stack. We work with them independently of that to develop this open AI initiative, which you can think of as a marketplace that's being sponsored by Shell, C3, and Microsoft. And it's a marketplace in which all the energy providers can basically put their C3 applications and they can trade them to one another. So Shell is a, you know, it's a strategic deal. It's five-plus years, and it is, you know, irrevocable, nonrefundable commitment. And, you know, it's a very substantial and important transaction that we think will serve, you know, at something of a bell cow in the oil and gas industry because, you know, Shell is, you know, perceived of as a technology leader in that space. And so we think that will help fuel our oil and gas business, which is already quite healthy. And I know a lot of people think oil and gas is kind of yucky, but these guys are all reinventing themselves as renewable energy companies, and we're very pleased to be able to play a role in that.

Thanks, Tom. And David, if you could, could you talk to us a little bit about the move down market from a couple of aspects, one in terms of ex machina, in terms of the progress there and how much might be built into the guide, and then maybe what your CV was like in the quarter if it's really moving down?

Michael, we couldn't quite hear the second part of your question.

So, again, I'm sorry about that. So all about the move down market, and maybe you could approach it from a couple of angles. First of all, how much traction with Ex Machina, how much is built into the guide for next year from Ex Machina? And on TCV, what was it not just in the year but in the quarter, and how effectively are you moving that down?

Great questions. Michael, in terms of planning, the way we planned our business, We think about our subscription revenue accelerating over the course of the year, and as you see in our guide, we're looking at a midpoint of 26 going up to 34, and ex-market certainly features in that. So we have thought about it in terms of our go-to-market teams, and we planned in a detailed level as we thought about the outlook for the year and how to continue to accelerate our growth. So that's in terms of ex-market. And then in terms of TCB in the quarter, we're at about 7.5 million of TCB in the quarter.

Okay. All right, David and Tom, thanks very much. Thank you.

We have our next question coming from the line of Patrick Caldwell with Deutsche Bank. Your line is open.

Hey, thank you so much for taking my question. I mean, the presentation is fascinating and it's really interesting to kind of hear, you know, how you see the market evolving. Just help me understand, though, just this quarter, and I guess implicit in your guide, doesn't seem like this is translating into dollars just yet. Subscription revenue is kind of basically flat sequentially, and implicit in the guide is kind of flat again in the first quarter. So just how to understand just the kind of puts and takes between this fantastic long-term potential that you articulated and we can see versus the kind of near-term and this translating into kind of dollars now.

I think it was kind of flat last year, Q4 to Q1, wasn't it, Patrick? If my memory serves me correct. And, you know, I think that the growth projections that you and others had for us, and one of you can correct me if I'm wrong, for this year was about 9%, and I think we came in about 17%. You know, we're seeing, you know, part of what's going on in Q1 is, is the growth of the year is going to be a very healthy year. Q1 will be a very healthy quarter. We are raising guidance for Q1 over what the consensus was. Part of what's going on in Q1, however, is an artifact. You have to go back and look at bookings, which I'm not going to disclose. okay for like q1 and q2 of um uh uh fiscal year 20 okay and you know but if you look at 19 and 20 you know we're kind of thrashing around quarter and quarter quarter to quarter in bookings and there's kind of an artifact there that has some downward pressure on you know on q1 you know everything as this as the revenue kind of water from bookings water falls out over say 36 months And, you know, there was a quarter back there that wasn't very big, and the term of the revenue was not very long in the quarter. And there was, you know, a little bit of downward pressure on Q1. But Q1 is going to be a fine quarter, and the year is going to be a great year.

Great. That's very helpful. And I guess as we kind of think beyond fiscal first quarter into kind of fiscal second, third, and fourth, up next year. I mean, just sticking to the numbers here, again, the guide suggests quite a material reacceleration. I mean, I remember at the time of the IPO, we were talking about a number of factors, including the exit from coronavirus. We're talking about the kind of lapsing of the Baker Hughes contract reset. Are they still the kind of key reasons for this reacceleration in subscription revenue in the second half? of fiscal 22, or are there other factors that we should be aware of? Thank you.

Well, I think what we saw was a re-acceleration of bookings in the second half of fiscal year 21, really. Okay. And, you know, as we, I mean, we came into fiscal year 21 blowing and going, I think. Wasn't the growth rate in fiscal year 20 like 91% growth or something? 71%. Okay. Sorry. It was a big number. It was significantly not zero. Okay. It was big. And then we got, you know, kicked in the teeth with COVID. Okay. And I think what you're seeing is just what we saw in the second half of the year is just a reacceleration of business. And, you know, COVID is clearly over. Digital transformation is – you know, the interest in that is more acute than it ever has been. Okay. The interest in enterprise AI is more significant than it ever has been. Okay. And we're perceived of as a, you know, kind of more substantial, more reliable provider than we ever have been. So I think what we're just seeing is acceleration of business. It's a good thing. Great.

Thank you so much. Really appreciate you taking the time.

We have our next question coming from the line of Jack Andrews with Needham. Your line is open.

Good afternoon. Thanks for taking my question. Tom, I was wondering if you could speak to just the hiring environment. You know, it's historically been difficult for applicants to secure opportunities at C3. And so could you speak to are you able to scale the organization the way you want to in terms of, you know, finding the right types of people to build out the organization these days?

I reviewed those data today, Jack. It's a great question. Last quarter, I think we had 12,000 applicants, okay, job applicants from all over the world to C3A. Count them, 12,000, okay? And this annualizes to roughly 50,000. And we're in the heart of Silicon Valley. This is supposed to be a very, very challenging hiring environment. You know, of those 12,000, I think we had interviews of one form or another with, you know, almost 3,000, and we hired a net of like 56. So we have really the brightest and most highly trained and experienced data scientists in the world and application engineers and salespeople and sales leadership and marketing leadership who want to join us. And so we're very, very excited. We kind of need to figure what's going on and bottle this as we go forward. But the rate of interest in people coming to work with FC3 has not slowed down. And our rate of interest in hiring people has definitely not slowed down. And if you go, and I encourage anybody who's interested to, you know, you get a pretty good feel for what the culture is like and what the morale is like if you go look us up on Glassdoor.com. But, yeah, it was, I think, 12,500 people who applied for jobs here in the last quarter. It's really rewarding.

That's great. Thanks for the color around that. And just as a follow-up question, I think in your prepared remarks, you referenced strong deal volume late in the quarter. I was wondering if you could provide some more context around that. Was that something that just happened organically within your customer base, or was that the result of maybe some of your partnerships really coalescing? Any further clarity would be appreciated.

I don't think I could say anything like that. I think, Jack, you may have heard it in one of my paragraphs. I missed that. I was out of the room. And so I think all we were highlighting is the correlation, Jack, between our bookings and how that manifested in terms of accounts receivable, deferred revenue, and the strengthening of our performance measures like RPO. Got it. Okay. You just saw bookings, you know, percolate through the financial results.

Thanks.

We have our next question coming from the line of Mark Murphy with JP Morgan. Your line is open.

Yes, thank you. Tom, how is the signaling from some of your end markets that benefit from higher commodity prices like oil and gas or higher inflation and interest rates such as financial services? I'm just wondering, because that's a pretty good portion of your customer base, is it safe to assume that's on, you know, much firmer footing versus a year ago where you would see that driving strong pipeline growth for later in this year?

Well, Oil and gas, you know, I don't know what gas prices were a year ago, but I remember about a year and a half ago, you couldn't give oil away, right? It was like negative $37 a barrel or something. You know better than I, but roughly $67 or something like that. So you can assume... It's easier to do business with oil at $67 a barrel than it is at negative $37. I can assure you of that. And the banks all seem to be printing money around the world. So those segments do look healthier than they have in some time for us. And we expect to see outsized growth in those segments. We're not stopping there. I mean, you can expect us to be investing this year in a big way in defense and intelligence, and that's been manifested in some of the hiring that you've seen. Telco, where we've put together a large organization around Telco. You'd expect to see a large investment in precision health. So, yes, we will be further penetrating the oil and gas businesses and the

um banking business and um and those those those issues today look very healthy okay um as a follow-up I guess regarding the Shell uh partnership extension are you um able to comment on the dollar amount and I I wasn't clear to me whether that is reflected in the uh RPO balance that we're seeing for Q4 or is that something, would that manifest in the Q1 metrics?

That's in RPO. We closed it in Q4 and it's in RPO. But in terms of the size of it? I can tell you if you take all of our deals, the size of some of the deals, and divide by the number of deals, it's, what did I say, 7.2 million? But the size of Schaller, it's a good one. It's bigger than a bread box. Let's say it didn't contribute to bringing our average total contract value down. It was a good one.

yeah okay um and then just one one final one uh david uh the on the the crpo i think it grew well sequentially i think it grew nine or ten percent um year over year is there any perspective on um maybe how to drive that current piece of rpo a bit faster there um i think a prior analyst was commenting that we we we see it in the kind of longer term uh portions But can, for instance, do you think that CRPO number could be growing a little faster a couple quarters down the road?

Yes, is the short answer.

Thank you.

We have our next question coming from the line of David Hines with Canaccord. Your line is open.

Hey, thanks very much. Tommy highlighted CRM is kind of the opportunity that excites you the most. I'm just curious, like, where do you see the most low hanging fruit in CRM? And what's the home run vision for that market? If you kind of reimagine it with AI?

Well, I'm not sure it's the thing that excited me the most, but I'm really excited about it, okay? It's not going to be our biggest market. Our biggest market is going to be enterprise AI writ large. Think precision health. Think banking. Think oil and gas, travel, transportation, what have you. That being said, you know, guys, you know, CRM today is an $80 billion addressable market, okay? The next generation of CRM is all about AI-enabled CRM. An AI-enabled CRM is basically when you take the data that are in the CRM system and combine it with all sorts of exogenous data. Let's take a hypothetical of a manufacturing company, maybe Boeing. So Boeing has all these, and they used to sell $60 billion worth of commercial aircraft. I have no idea what they sell today. Okay. But, you know, they have a CRM system, probably Salesforce or Siebel or something. They're all kind of the same. Okay. And they, you know, where they have all these sales forecasts that the guys put in, and these systems are just like the systems that, you know, you guys have at J.P. Morgan, Chase, and everybody else. You know, the sales guys just put whatever they need to get it, but put it in there to get the sales manager off the back. Okay, and so they put in all these records, already have 35,000 salespeople at Merck, each of which are putting, you know, 100 lines of garbage. And so you get, you know, 350,000 lines of kind of garbage in your forecasting system, and you take some of that, and it's supposed to be your sales forecast. Well, it really doesn't work that way. Now, however, the data really aren't useless. And if we think about, you know, this is a hypothetical because we're not talking with them about this, but let's think about Dave Calhoun at Boeing. And he's got, you know, he's got the information that's in his CRM system about contacts, about opportunities, about deals that are supposed to close at Lufthansa, at Bank of America, at Southwest Airlines. And it's just the information that the salespeople put in. Now, imagine combining that data with almost nine times more of that or order of magnitude more exogenous data about the market. Think commodity prices, jet fuel prices, the equity prices of Boeing's customers, Southwest Airlines, Lufthansa, American Airlines. NLP on social media. Okay. NLP on analyst reports, equity prices of all these companies, GDP growth rates, passenger travel miles. Is the country at war? Is the country at peace? Okay. NLP on media. If Southwest Airlines is announcing a 15% layoff for whatever reason, like airlines do from time to time, and their stock just goes down 30%, what's the probability that this order for like, you know, 100, 737 maxes is going to close this quarter? Oh, that would be zero. Okay, so you can see how we can take all of those data, tens of thousands of signals from the market, analyst reports, news reports, stock prices, commodity prices, jet fuel prices, GDP growth rates, is the country at war, is the country at peace, and build very precise machine learning models that tell Dan, tell Hoon, what deals are actually going to close, okay? And not only is this, let's set Calhoun aside, because let's talk about, you know, something like a, what would be Procter & Gamble, okay? So Procter & Gamble not only needs to forecast revenue, they need to forecast products, okay? because they need to make the right amount of stuff at the right time to meet the demand function in order to realize their revenue. We have now demonstrated that we can build these AI models that are literally, in order of magnitude, more precise as it relates to revenue forecasting, customer forecasting, next best product, next best offer, customer return, than what's going on in CRM today. And you're going to see us releasing these products this year for banking, for aerospace, Okay, for manufacturing, for healthcare, what have you. And most products will be well-perceived. Now, we have done, you know, extensive market research on the levels of customer satisfaction in the CRM industry today. And I'm telling you, the levels of customers, these people hate their vendors. Okay? And so the levels of customer satisfaction are uniform. It's an $80 billion market. And as it went from that segment that's related to AI, the intersection of AI and CRM, I believe we're going to establish a leadership position in that market. We've hired some, you know, very key people in CRM here. You'll be seeing some announcements soon of some other, you know, very key people who are joining us. And that is going to be an exciting market. And as you people know, it's a market that I'm not entirely unfamiliar with. And so we're going to have some fun there. Do I think we're going to put existing CRM companies out of business? No way, no how. They're great companies. They're going to continue to survive. Will we establish a significant toehold in that segment that is where people are interested in using AI for these things? Don't bet against us.

Yeah, yeah.

Okay. And then maybe you could speak to the mix of kind of direct versus partner led business and maybe how that differs today versus, you know, what it looked like a year ago.

Oh, partner led. Okay, so... Partner-assisted, I guess. Yeah, well, partner-assisted, I think, is right, okay? I'm not really certain we really have any, you know, it's a great question, David, and we're going to work, we go to market at a massive scale, I'd say, with Microsoft, okay, with Baker Hughes, and now we're just kind of kicking into gear, okay, with FIS, okay, and Infor, and I think we're ready to go to market with Singtel in Asia, okay? partner assisted i mean it's i mean probably i mean i think our pipeline today is larger than it has ever been i think that this is off the record i'll never say it again okay it's probably off by 10 but i think our pipeline for this year is like 1.6 billion dollars or something okay and and so give me some slack on that one guys i don't have any numbers in front of me but i think it's Pretty directionally, it's about right. I would speculate that on 50% of those transactions, we are engaged with a partner, either Microsoft or a bigger user or something like that, to bring the deal home.

Yeah, okay. That's a helpful data point. Thank you.

This partner ecosystem is an important part of the equation. Can we really rely on the partner to close the deal for us? You know, I'm not so sure. I think we might have to close it ourselves. Okay, but the partner assists. You know, if your partner happens to be Satya, you know, or Judson Alsop at Microsoft, you know, they're pretty good sales guys, I'm telling you.

Thank you. We have our next question coming from the line of Sanjit Singh with Morgan Stanley. Your line is open.

Thank you for taking the questions. I wanted to follow up on the previous question, really relating to the customer count, which picked up pretty nicely. I think they're up to like 89 customers from around 64 at the time of IPO. And just wanted to get a sense of what's driving that. Is this a better sort of spending environment or from a sort of go-to-market sales execution, sales hiring perspective. You're starting to see that sales productivity really start to come through the door to help accelerate that customer account velocity.

Well, Sanjay, I think there's two things that we're seeing that are influencing that. Number one, you'll recall that, you know, pre-IPO, we were only elephant hunting, okay? We only had a major accounts group. Okay. And since then, we've been building, you know, kind of a traditional enterprise sales organization, a middle market sales organization, and a mass market sales organization. One of our, you know, we did a pretty large transaction this quarter, I believe, to place on the Microsoft, on the Azure marketplace. Did it not? Did it in Asia? It did. Okay? Okay? And all you guys, I encourage you to go to c3.ai.com, c3.ai now. Okay? Put in your name, address, okay, and credit card number, and for 30 days use, you know, use the Ex Machina for free. I mean, hundreds and hundreds of people are doing that. Okay? So please do it, and don't Please also forget to dial in in 30 days and cancel your subscription, okay? But I think there's two things, Sandy. Number one is, remember we said a couple years ago we're going to expand the major accounts group. We're going to expand the enterprise group. We're going to put a middle market group in place. We'll put a mass market group in place. We're doing all that, including telesales, marketplaces, the internet sales. And then this is combined with the partner ecosystem. be it Microsoft, AWS, Baker Hughes, or what have you. So it's resulting in just a much larger diversity of different sized deals. So the strategy that we said we were going to execute starting in well before the IPO, I mean, I communicated this as early as early 2018, we're executing it and it's working.

makes total sense though the follow-up question is the topic that we've talked about um for a couple of quarters now tom which is around like the competitive environment look at The broader landscape, including C3 and then some of the other vendors that either own parts of the space or kind of do multiple parts of the workloads and data science machinery, seems like everybody's throwing like a weed. And I know your view is that a lot of customers are stuck in proof of concept hell. Going back to that question of do customers sort of do the dance with this sort of stitch-together approach, or they come to sort of an end-to-end platform like a C3, where are we in that journey, do you think?

Well, I think everybody's going to try to build it themselves, and that's what IT people do. And, you know, they tried to build relation database systems themselves. They tried to build ERP systems themselves. They tried to build their own CRM systems themselves. How'd that work for Morgan Stanley? Okay. I mean, they tried. Okay. They tried to build all those things themselves, okay? I was there, okay? How did it work for JPMorgan Chase? I mean, they tried to build all the systems themselves, and today JPMorgan Chase is trying to build their own AI platform, okay? After that comes down crash, they tried to build their own ERP system. They tried to build their own CRM system. All that came crashing down around them, so they'll spend, you know, I don't know how many hundreds of millions to billions of dollars you're trying to build their own AI platform, and then Jamie will be gone, and they'll bring in some new CEO, and he'll fire everybody, and he'll buy it from a commercial vendor. That's the way this works. So virtually every one of our customers, Shell, Engie, Coke Industries, United States Air Force, Army Futures Command, has tried to build this themselves, Baker Hughes. That would be GE. And, you know, it didn't work out so well. And so this is just a phase. You know, we've seen this over and over and over in the industry, and it's just a phase that everybody's got to go through. They have to try it themselves and crash and burn a couple times, and then they buy it from a reliable vendor.

I appreciate the thoughts, Tom. Thank you.

Thank you. We have our next question coming from the line of Arvind Ramnagy with Piper Sandler. Your line is open.

Hi, Tom. Most of my questions have been asked, but I did have a couple of questions. I had a question about your overall product. Can you talk about applicability of using the same code base across different industries or different applications?

Yeah, well, Garvin, I mean, it's a really good question. And you and I have talked about this before, but I really do appreciate you asking it. So we deliver, I think, about 21 different AI products today across five different industries. And we have a family of products for manufacturing, for gas, for financial services, for aerospace. And what's counterintuitive is that whether we're doing object identification for the Space Command, clearance adjudication for the Defense Intelligence Agency, stochastic optimization of the supply chain at Koch Industries, or AI-based predictive maintenance for Shell for offshore oil rigs, all of which we do, Now, these are separate products with separate documentation, separate user interfaces, separate APIs to aggregate data, but 90% of the code that are running across all those applications, whether it's Cash Management Bank of America or Predictive Maintenance for Offshore Oil Rigs at Shell, it's the same code base. And so that's counterintuitive. And this is the beauty of this model-driven architecture. And we have really broken the code on that. Okay, so we're able, everything we do is reusable. And so that's what people, you know, we have broken the code. We own all the intellectual property. The patents have been awarded to us. It is our invention, okay, this idea of using a model-driven architecture for enterprise AI and IoT applications. Okay. What changes from customer to customer are the data sources, the APIs that we use for the data source, trivial problem. okay the user interface expression it differs from say anti-money laundering to um uh predictive maintenance for low pressure compressors on offshore all race but we can all agree i hope that the user interface is trivial and then the part that differs from the most from installation to installation are the machine learning models. And the machine learning models, I hope we can agree, these are non-trivial, but they constitute maybe 3% of the code.

Perfect. And I know you've answered a couple of questions on guidance, but I just maybe wanted to frame it a little bit differently. At the midpoint of the guide, you're really adding $62 million in revenue in fiscal 22. And then when I look at your fiscal 20, which was a good year before the pandemic hit, you added $65 million. So it seems like the guidance has a fair bit of conservatism because you have $62 million adding, but you also have some delays and some pent-up demand from, you know, the delays that you experienced last year that should kind of boost revenue add more than like 60 to a million. So I just wanted to get a sense of how conservative your guide may be.

Well, Arvind, you know, you know me a little bit. And, you know, I hope that at the end of the day that people will believe that I was credible and I am credible. So we're focusing on being credible. And, you know, what we want to do is meet and exceed, beat and exceed, beat and exceed. So, you know, we're, you know, I think that, you know, I think that I don't know how many enterprise applications, software companies are growing. What's the expected growth rate in the middle of that, 33% or something like that? 34. 34%. I mean, I don't know how many enterprise software companies are growing at 34% compound annual growth rates, but I'm sure that would be in the top deck. I don't want to track this stuff, but I suspect it's in the top deck aisle. And right now we intend to move in the top deck aisle this year, and hopefully we can come back to you next year and move up a little higher. Perfect. Thank you.

We have our next question coming from the line of Pat Walrivance with J&P Group. Your line is open.

Pat Walrivance Oh, great. Thank you. And congratulations on the quarter.

So, Tom, you've got oil and gas, financial services, CRM, Ex Machina.

Can you just tell us for this year, you know, for this coming year, what are your top three sort of strategic imperatives? It's a really good question. The strategic imperatives, Pat, and you'll see a number of announcements coming in this area, and there have been some announcements, is making sure that we have the leadership in place to scale this business globally. And you've seen some of this with Ed Cardone. You've seen some of this from... General Cardone, who's the chairman of C3 Federal, the new general manager of C3 Federal. And you can expect that we will be adding a number of, you saw this with Jim Snabe, the co-CEO of SAP joining our board. And we have been really, really focused on on bringing senior leadership into the company in the last nine months. And you're going to see a number of announcements there that I think you'll agree are significant. And I think that is the – I mean, we have the technology. The market is much bigger than we can address and rapidly growing. The technology foundation we have is very rich, and it works. We're leaving in our wake a string of highly satisfied customers. I think we're doing a pretty good job at building brand equity. The competitive dynamics of this market are not very significant. I mean, basically, you know, we are selling vehicles and everybody else is selling, you know, ball bearings and wheels and carburetors, okay? And we're selling vehicles, okay? And so there's not much going on in terms of the competitive dynamics. And so we just need to make sure that we have the seasoned leadership in place to scale this business, you know, in federal systems, in Asia Pacific, in Japan, in Europe, in manufacturing, healthcare, telecommunications, aerospace, et cetera. I think it's human capital. That's that is the game. And if you go look on Glassdoor, and if you are interested, I think that this focus on human capital has been consistent for many years and it will continue. Great. Thank you.

Thank you. There are no further questions at this time. I will now turn the call over back to Tom Siebel for closing remarks.

okay ladies and gentlemen uh we thank you for uh taking time out of your busy day okay to uh to check in on us uh we you know appreciate your interest uh and um you know know that we are you know it is now you know june of 2021 you know i'm very pleased to report that there has been no day in the history of this company when this company has been better positioned, when the market has been, whether there has been more market opportunity or whether this company has been better positioned to seize the market opportunity. So as we approach the next two, three, four years, I can tell you we approach it with great enthusiasm and we'll, you know, we'll, You know, we'll see how this turns out when it's over, but I think there's some probability that we might build a pretty substantial company here. So thank you for your interest, thank you for your support, and thank you for your questions. And we wish you all a great day.

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