Good day. Thank you for standing by. Welcome to the C3.ai fourth 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 one on your telephone. Please be advised that today's conference is being recorded. If you require any further assistance, please press star zero. I would now like to hand the conference over to your speaker today, Paul Phillips. Please go ahead. Good afternoon and welcome to C3.ai'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 at C3.ai. With me on the call today are Tom Siebel, Chairman and Chief Executive Officer, and David Barter, 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 with 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, 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 2021 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 2021 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. 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 2019, to $12.1 million in fiscal year 2020, to $7.2 million in fiscal year 2021, 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 Edison, 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 Health Care, 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 Sustainment Office, and the F-35 Lightning II Joint Program Office. Importantly, Shell executed a very significant expansion that spans over slightly in excess of five years to significantly accelerate the deployment of C3.ai and ML applications across Shell global assets. This represents a major expansion of the partnership that C3.ai and Shell have forged over the past several years. 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.ai 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. 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 2021 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. 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 applications were integrated with more than 800 unique enterprise and extraprise data sources and sensor constellations. We manage 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 market and 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.ai CRM. AI CRM represents the next generation of the now $80 billion addressable CRM market, 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.ai In the coming year. With Shell and Microsoft, C3.ai expanded the Open AI Energy Initiative, an open marketplace for C3.ai applications. Announced in February, the Open AI Energy 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 2021 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. With that, I'll turn it over to our CFO, David Barter, for further, for more complete color on the quarter and the year. David? Thank you, Tom. We've exceeded our guidance for both revenue and profitability in the fourth quarter while also building significant backlogs that will help drive future growth in FY 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 services revenue grew to $9.2 million, reflecting strong 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. We continue to anticipate subscription revenue mix in the upper 80% range on a trended basis. 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 2020. 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 is 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 would 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. Baker Hughes partnership revenue increased 20% compared to $46.7 million of 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 C3.ai 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, and the non-related party component was $8.7 million. For full fiscal year 2021, related party revenue 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 78.3%, up from 77.5% a year ago. 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 million to $27 million. In the fourth quarter, head count increased by 56, an 11% sequential increase compared to the third quarter. For the full fiscal year, head count 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. 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 that 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. Finally, it is worth noting that we will invest thoughtfully to expand our leadership position in the market. Investment will 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 $243 million-$247 million, non-GAAP operating loss in the range of $119 million-$107 million. For the first quarter of fiscal year 2022, we expect revenue in the range of $50 million-$52 million and non-GAAP operating loss in the range of $35 million-$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 one on your telephone keypad. Again, that is star and then the number one on your telephone keypad. We'll pause for just a moment to compile the queuing roster. We have our first question coming from the line of Daniel Ives with Wedbush. Your line is open. Yeah, thanks. Can you talk 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? Yes. We had a huge concentration in utilities, as you'll recall. Then a couple 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. 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, Volcker Rule compliance, margin lending. Manufacturing remains a big business for us, particularly as it relates to cash optimization with supply chain, production optimization. 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 v ery, very large deals like we did three and four years ago. We have a mix of large deals, medium deals, and small deals that is resulting in a substantial reduction in our average contract value. As this plays out, just like the relational database business did, and the minicomputer market did, and CRM did, I think that enterprise AI will be adopted across all sectors, precision health, travel, transportation, aerospace, you name it. We expect to play in all those sectors. Great. 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.ai Stands today versus even six months ago or a year ago? Has it really gone from just more strategic, and it's almost more of a pull versus push? Can you just compare and contrast, especially just given what you've seen in the last 30, 40 years? Thanks. Well, I think we really hit an inflection point after. The first two quarters of this calendar year were issued in calendar year 2020, okay, were tough, right? We were doing these large enterprise transactions, and then COVID hit. Paris closed, Rome closed, London closed, New York closed, Chicago closed. That did slow us down. Now, when we get into May, June, July of last year, we saw dramatic acceleration. This mandate towards digital transformation seems to have made it to 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 high-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. W e're doing a pretty good job of demonstrating thought leadership in AI. The work that we're doing with major research institutions like Illinois, Carnegie Mellon, Princeton, MIT, Stanford, Berkeley, KTH, is really helping us at the high end. Now we have production use cases all over the place in utilities, all over the place in manufacturing and financial services, in aerospace. The pipeline has never been larger, okay, and the sales cycles are shorter than they've ever been. 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 Sills 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? Well, I mean, 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. The uptake there is pretty substantial. I'm saying 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 at or near the top. Whether we start at the bottom or we start at the middle, we seem to make it to the top sooner or later. Whether it's Bank of America or Standard Chartered Bank or Koch, this is a rapidly growing hot market with a lot of people really interested. 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. We present the prospect of being able to fix that, and business is good. That's great. Thank you, Tom. 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. T hat's a really good question. The answer is yes. I mean, as you get into selling to small and medium businesses, selling CRM, selling Ex Machina, I mean, they're just selling $500, $1,000 at a time, and it becomes an ARR game. ARR has been really less important as a metric for us historically because we were landing contracts that were so long in duration and so large. You can remember in fiscal year 2018 and 2019, you were here when we were doing $30 million, $40 million, $50 million deals all the time. That's clearly changing now. I think it's a healthy mix of large deals, medium deals, and de minimis transactions. I would say $500 a month, by our standards, is certainly de minimis. It certainly looks good in the long run in terms of evening out, 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 Turits with KeyBanc. 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. I think the existing contract that we had in place with Shell, Michael, and I could be wrong on this, I think it was the second or third contract, okay? 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. Then they expanded to kind of a small enterprise deal. They expanded to a larger enterprise deal, which was three or four years in duration. Shell 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, I am not really privy to all of Shell's strategy, but it looks to me like it might become an electricity business. Anyhow, they were deploying many successful applications. They decided to renew their application a year before it expired, they entered into a new five-year relationship with us to dramatically expand the number of assets to which they can apply the C3.ai Applications and the C3.ai Stack. We work with them independently of that to develop this Open AI Energy Initiative, which you can think of as a marketplace that's being sponsored by Shell, C3, and Microsoft. It's a marketplace in which all the energy providers can basically put their C3.ai Applications and they can trade them to one another. Shell is a strategic deal. It's five-plus years, and it is irrevocable, non-refundable commitment. It's a very substantial and important transaction that we think will serve as something of a bell cow in the oil and gas industry because Shell is perceived of as a technology leader in that space. We think that will help fuel our oil and gas business, which is already quite healthy. 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. David, 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 kind of TCV was like in the quarter if it's really moving down? Michael, we couldn't quite hear the second part of your question. Could you repeat it, please? Again, I'm sorry about that. Okay. All about the move down market, and maybe you could approach from a couple of angles is, first of all, how much traction with Ex Machina, how much is built into the guide for next year from Ex Machina? 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. As you can see in our guide, we're looking at a midpoint of 26% going up to 34%, and C3.ai Ex Machina certainly features in that. 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. Okay. That's in terms of Ex Machina. In terms of TCV in the quarter, we're at about $7.5 million of TCV in the quarter. Okay. All right, David and Tom, thanks very much. Thank you. We have our next question coming from the line of Pat rick Colville with Deutsche Bank. Your line is open. Hey, thank you so much. Thanks for the question. The presentation's fascinating, and it's really interesting to hear how you see the AI 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 basically flat sequentially, and implicit in the guide is kind of flat again in the first quarter. I just want to understand just the 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 dollars now. I t was kind of flat last year, Q4 to Q1, wasn't it, Patrick? If my memory serves me correct. 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%. We're seeing part of what's going on in Q1 is the year is going to be a very healthy year. Q1 will be a very healthy quarter. We are raising guidance, okay, for Q1 over what the consensus was. Part of what's going on in Q1, however, is an artifact of you have to go back and look at bookings, which I'm not going to disclose, okay, for like Q1 and Q2 of fiscal year 2020. Okay? If you look at 2019 and 2020, we're kind of thrashing around quarter to quarter to quarter to quarter in bookings, and there's kind of an artifact there that has some downward pressure on Q1. We're thinking as the revenue from bookings waterfalls out over, say, 36 months. 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 a little bit downward pressure on Q1. Q1 it'll be a fine quarter, and the year is going to be a great year. Great. That's very helpful. A s we think beyond fiscal first quarter into fiscal second, third, and fourth of next year, I mean, just sticking the numbers here, again, the guide suggests quite a material re-acceleration. 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 collapsing of the Baker Hughes contract reset. Are they still the key reasons for this re-acceleration in subscription revenue in the second half of fiscal 2022, 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 2021, really, okay? We came into fiscal year 2021 blowing and going, I think. Wasn't the growth rate in fiscal year 2020 like 91% growth or something? 71%. 71%. Okay. Sorry. It was a big number. It was a big number. It was significantly non-zero. Okay. It was big. Then we got kicked in the teeth with COVID, okay? I think what you're seeing is just what we saw in the second half of the year is just a re-acceleration of business. COVID is clearly over. Digital transformation, 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? We're perceived of as a kind of more substantial, more reliable provider than we ever have been. 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. It's historically been difficult for applicants to secure opportunities at C3. Could you speak to, are you able to scale the organization the way you want to in terms of 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 C3.ai. Count them, 12,000. Okay? This annualizes to roughly 50,000. We're in the heart of Silicon Valley, which is supposed to be a very challenging hiring environment. Of those 12,000, I think we had interviews in one form or another with almost 3,000, and we hired a net of like 56. We have really the brightest and most highly trained and experienced data scientists in the world, and application engineers and salespeople and sales leadership, okay, and marketing leadership who want to join us. We're very, very fortunate in that respect. We kind of need to figure what's going on and bottle this as we go forward. The rate of interest in people coming to work with C3.ai has not slowed down, okay, and our rate of interest in hiring people has definitely not slowed down. If you go, and I encourage anybody who's interested to. 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. 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. 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 said anything like that. I think Jack may have heard it in one of my paragraphs. I missed that. I was out of the room. 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, thanks. You saw bookings percolate through the financial results. Thanks. We have our next question coming from the line of Mark Murphy with JPMorgan. 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 much firmer footing versus a year ago where you would see that driving strong pipeline growth for later in this year? Appreciate it. Well, oil and gas, 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. What is it today? You'd know better than I, but roughly $67 or something like that. 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. The banks all seem to be printing money around the world. 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. 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. Yes, we will be further penetrating the oil and gas businesses and the banking business and those industries today look very healthy. Okay. As a follow-up, regarding the Shell partnership extension, are you able to comment on the dollar amount? It wasn't clear to me whether that is reflected in the RPO balance that we're seeing for Q4, or would that manifest in the Q1 metrics? That's in RPO. We closed it in Q4, and it's in RPO. In terms of the size of it, I could tell you if you take all of our deals, the size of the sum of the deals and divide by the number of deals, it's, what did I say, $7.2 million. The size of Shell, it's a good one. It's bigger than a breadbox. Let's say it didn't contribute to bringing our average total contract value down. It was a good one. Yeah. Okay. Then just one final one, David. On the CRPO, I think it grew well sequentially. I think it grew 9% or 10% year-over-year. Is there any perspective on maybe how to drive that current piece of RPO a bit faster? I think a prior analyst was commenting that we see it in the longer-term portions. 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 Hynes with Canaccord. Your line is open. Hey, thanks very much. Tom, you highlighted CRM as kind of the opportunity that excites you the most. I'm just curious, where do you see the most low-hanging fruit in CRM, and what's the home run vision for that market as you kind of reimagine it with AI? Well, I'm not sure it's the thing that excites 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, guys, CRM today is an $80 billion addressable market, okay? The next generation of CRM is all about AI-enabled CRM, okay? 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. Boeing, they used to sell $60 billion worth of commercial aircraft. I have no idea what they sell today. They have a CRM system, probably Salesforce or Siebel or something. They're all kind of the same, where they have all these sales forecasts that the guys put in, and these systems are just like the systems that you guys have at JPMorgan Chase and every place else. They put in all these records, or you have 35,000 salespeople at Merck, each of which are putting 100 lines of garbage. You get 350,000 lines of garbage in your forecasting system, and you take the sum of that, and it's supposed to be your sales forecast. It really doesn't work that way. However, the data really aren't useless. If we think about, this is a hypothetical because we're not talking with them about this, but let's think about Dave Calhoun at Boeing. He's got the information that's in his CRM system about contacts, about opportunities, about deals that are supposed to close at Lufthansa and Bank of America, at Southwest Airlines. It's just the information that the salespeople put in. Now, imagine combining that data with almost 9x 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. 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? 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 100 737 MAXes is going to close this quarter? Oh, that would be zero. 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? Build very precise machine learning models that tell Dave Calhoun what deals are actually going to close. Let's set Calhoun aside because let's talk about something like a Procter & Gamble. Procter & Gamble, not only needs to forecast revenue, they need to forecast profits 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 an order of magnitude more precise as it relates to revenue forecasting, customer forecasting, next best product, next best offer, customer churn, than what's going on in CRM today. You're going to see us releasing these products this year for banking, for aerospace, for manufacturing, for healthcare, what have you, and most products will be well received. We have done extensive market research on the levels of customer satisfaction in the CRM industry today, and I'm telling you, these people hate their vendors. The levels of customer dissatisfaction are uniform. It's an $80 billion market. As it relates to 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 very key people in CRM here. You'll be seeing some announcements soon of some other very key people who are joining us, and that is going to be an exciting market. As you people know, it's a market that I'm not entirely unfamiliar with. 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 where people are interested in using AI for these things? Don't bet against us. Yeah. Okay. That's helpful. Maybe you could speak to the mix of direct versus partner-led business and maybe how that differs today versus what it looked like a year ago. How do you say partner-led? Okay. Partner-assisted, I guess. Well, partner-assisted, I think is right. It's a great question, David, if we go to market, at massive scale, I'd say with Microsoft, with Baker Hughes, and now we're just kicking into gear with FIS and Infor, and I think we're ready to go to market with Singtel in Asia. Partner-assisted. I think our pipeline today is larger than it has ever been. This is off the record. I'll never say it again. It's probably off by 10%, I think our pipeline for this year is $1.6 billion or something. Give me some slack on that one, guys. I don't have any numbers in front of me, I think pretty directionally, it's about right. I would speculate that on 50% of those transactions, we are engaged with a partner, either Microsoft or Baker Hughes or somebody 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. Right. Can we really rely on the partner to close the deal for us? I'm not so sure. We might have to close it ourselves. Okay, the partner assist, if your partner happens to be Satya or Judson Althoff at Microsoft, 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 question. I wanted to follow up on the previous question, really relating to the customer count, which picked up pretty nicely. I think you're up to 89 customers from around 54 at the time of IPO. 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 on the call with that customer count buildup? Well, Sanjit, I think there's two things that we're seeing that are really influencing that. Number one, you'll recall that pre-IPO, we were only elephant hunting. Okay? We only had a major accounts group. Okay? Since then, we've been building a kind of a traditional enterprise sales organization, a middle market sales organization, and a mass market sales organization. We did a pretty large transaction this quarter, I believe, took place on the Azure marketplace. Did it not? Thing in Asia? We did. Okay. All you guys, I encourage you, go to c3.ai now. Okay? Put in your name, address, okay, and credit card number, and for 30 days use the C3.ai Ex Machina for free. H undreds and hundreds of people are doing that. Okay, please do it, and please also forget to dial in in 30 days and cancel your subscription. Okay? T here's two things, Sanjit. Number one is, you remember we said a couple of 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. This is combined with the partner ecosystem be it Microsoft, AWS, Baker Hughes, or what have you. It's resulting in just a much larger diversity of different sized deals. The strategy that we said we were going to execute starting in well before the IPO, I mean, I communicated this as early as 2018. We're executing it, and it's working. It makes total sense. The follow-up question is a topic that we've talked about for a couple of quarters now, which is around the competitive environment. When you look at the broader landscape, including C3.ai and then some of the other vendors that either own parts of the space or try to do multiple parts of the workloads and data science, machine learning, it seems like everybody's building like a weed. 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 a 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? I think everybody's going to try to build it themselves, that's what IT people do. They tried to build relational 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 would think. Okay. How'd it work for JPMorgan Chase? I mean, they tried to build all those systems themselves, 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. They'll spend, I don't know how many hundreds of millions or billions of dollars, 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. He'll buy it from a commercial vendor. That's the way this works. Virtually every one of our customers, Shell, ENGIE, Koch Industries, U.S. Air Force, Army Futures Command, tried to build this themselves. Baker Hughes, that would be GE. It didn't work out so well. This is just a phase. 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 of times, and then they buy it from a reliable vendor. All right. I appreciate the thoughts, Tom. Thank you. Thank you. We have our next question coming from the line of Arvind Ramnani with Piper Sandler. Your line is open. Hi, Tom. Most of my questions have been asked. 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, Arvind, it's a really good question. You and I have talked about this before, but I really do appreciate you asking it. We deliver, about 21 different AI products today across five different industries. We have a family of products for manufacturing, for oil and gas, for financial services, for aerospace. 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 98% of the codes that are running across all those applications, whether it's cash management at Bank of America, or predictive maintenance for offshore oil rigs at Shell, it's the same code base. That's counterintuitive, and this is the beauty of this model-driven architecture, and we have really broken the code on that. Okay? Everything we do is reusable. 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. It's 90% of the code set. 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 predictive maintenance for low-pressure compressors on offshore oil rigs. We can all agree, I hope, that the user interface is trivial. The part that differs the most from installation to installation are the machine learning models. The machine learning models, we hopefully can agree, these are non-trivial, but they constitute maybe 3% of the code. Perfect. I know you 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 2022. When I look at your fiscal 2020, which was a good year before the pandemic hit, you added $65 million. 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 the delays that you experienced last year that should kind of boost revenue more than $62 million. I just wanted to get a sense of how conservative your guidance may be. Well, Arvind Ramnani, you know me a little bit, and I hope that at the end of the day, that people will believe that I was credible, and I am credible. We're focusing on being credible. What we want to do is meet and exceed, beat and exceed. I don't know how many enterprise application software companies are growing. What's the expected growth rate in the middle of the year, 33% or something like that? 34%. 34%. 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 decile. I do not really track this stuff, but I suspect it's in the top decile. Right now, we intend to move in the top decile 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 Walravens with JMP Group. Your line is open. Oh, great. Thank you, and congratulations on the quarter. Tom, you've got oil and gas, financial services, CRM, Ex Machina pairing. Can you just tell us for this coming year, what are your top three strategic imperatives? It's a really good question. The strategic imperatives, Pat, 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. You've seen some of this with Ed Cardon. You've seen some of this from General Cardon, who's the chairman of C3.ai Federal, the new general manager of C3.ai Federal. 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. We have been really focused on bringing senior leadership into the company in the last nine months. You're going to see a number of announcements there that I think you'll agree are significant. W e 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. B asically, we are selling vehicles, and everybody else is selling ball bearings and wheels and carburetors. Okay. We're selling vehicles. Okay. There's not much going on in terms of the competitive dynamics. We just need to make sure that we have the seasoned leadership in place to scale this business in C3.ai Federal, in Asia Pacific, in Japan, in Europe, in manufacturing, healthcare, telecommunications, aerospace, et cetera. I t's human capital. That is the game. If you go look on Glassdoor, any of you who 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, we thank you for taking time out of your busy day to check in on us. We appreciate your interest. We know that it is now June of 2021. 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 there has been more market opportunity, or when this company has been better positioned to seize the market opportunity. As we approach the next two, three, four years, I can tell you we approach it with great enthusiasm. We'll see how this turns out when it's over. I think there's some probability that we might build a pretty substantial company here. Thank you for your interest, thank you for your support. Thank you for your questions. We wish you all a great day. This concludes today's conference call. Thank you for participating. You may now disconnect.