C3.ai Inc
NYSE:AI
| US |
|
Johnson & Johnson
NYSE:JNJ
|
Pharmaceuticals
|
| US |
|
Berkshire Hathaway Inc
NYSE:BRK.A
|
Financial Services
|
| US |
|
Bank of America Corp
NYSE:BAC
|
Banking
|
| US |
|
Mastercard Inc
NYSE:MA
|
Technology
|
| US |
|
UnitedHealth Group Inc
NYSE:UNH
|
Health Care
|
| US |
|
Exxon Mobil Corp
NYSE:XOM
|
Energy
|
| US |
|
Pfizer Inc
NYSE:PFE
|
Pharmaceuticals
|
| US |
|
Palantir Technologies Inc
NYSE:PLTR
|
Technology
|
| US |
|
Nike Inc
NYSE:NKE
|
Textiles, Apparel & Luxury Goods
|
| US |
|
Visa Inc
NYSE:V
|
Technology
|
| CN |
|
Alibaba Group Holding Ltd
NYSE:BABA
|
Retail
|
| US |
|
3M Co
NYSE:MMM
|
Industrial Conglomerates
|
| US |
|
JPMorgan Chase & Co
NYSE:JPM
|
Banking
|
| US |
|
Coca-Cola Co
NYSE:KO
|
Beverages
|
| US |
|
Walmart Inc
NYSE:WMT
|
Retail
|
| US |
|
Verizon Communications Inc
NYSE:VZ
|
Telecommunication
|
If you don’t study any companies, you have the same success buying stocks as you do in a poker game if you bet without looking at your cards.
Utilize notes to systematically review your investment decisions. By reflecting on past outcomes, you can discern effective strategies and identify those that underperformed. This continuous feedback loop enables you to adapt and refine your approach, optimizing for future success.
Each note serves as a learning point, offering insights into your decision-making processes. Over time, you'll accumulate a personalized database of knowledge, enhancing your ability to make informed decisions quickly and effectively.
With a comprehensive record of your investment history at your fingertips, you can compare current opportunities against past experiences. This not only bolsters your confidence but also ensures that each decision is grounded in a well-documented rationale.
Do you really want to delete this note?
This action cannot be undone.
| 52 Week Range |
20.5
42.94
|
| Price Target |
|
We'll email you a reminder when the closing price reaches USD.
Choose the stock you wish to monitor with a price alert.
|
|
Johnson & Johnson
NYSE:JNJ
|
US |
|
|
Berkshire Hathaway Inc
NYSE:BRK.A
|
US |
|
|
Bank of America Corp
NYSE:BAC
|
US |
|
|
Mastercard Inc
NYSE:MA
|
US |
|
|
UnitedHealth Group Inc
NYSE:UNH
|
US |
|
|
Exxon Mobil Corp
NYSE:XOM
|
US |
|
|
Pfizer Inc
NYSE:PFE
|
US |
|
|
Palantir Technologies Inc
NYSE:PLTR
|
US |
|
|
Nike Inc
NYSE:NKE
|
US |
|
|
Visa Inc
NYSE:V
|
US |
|
|
Alibaba Group Holding Ltd
NYSE:BABA
|
CN |
|
|
3M Co
NYSE:MMM
|
US |
|
|
JPMorgan Chase & Co
NYSE:JPM
|
US |
|
|
Coca-Cola Co
NYSE:KO
|
US |
|
|
Walmart Inc
NYSE:WMT
|
US |
|
|
Verizon Communications Inc
NYSE:VZ
|
US |
This alert will be permanently deleted.
You don't have any saved screeners yet
Good day and thank you for standing by and 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. [Operator Instructions] 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 year 2021, which ended April 30, 2021. This is Paul Phillips, VP of Investor Relations of 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 maybe 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 financial 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 responses 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 am 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, ConEd, 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 Joint Program Office. Importantly, Shell executed a very significant expansion that spans over slightly in excess of 5 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.
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 market 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 and product engineering at C3.ai. As of the end of Q4, we have released 20 enterprise AI applications into general availability across 5 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 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 a 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 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, right.
I am most enthusiastic about the advancements we are making in C3.ai CRM. AI CRM represents the next generation over the now $80 billion addressable CRM market, a market segment that I am confident we will lead. Keep your eye on this space. You can expect that number of exciting announcements and product releases from C3 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 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 are planning for accelerating growth in the coming year.
And with that, I will turn it over to CFO, David Barter for a more complete color on the quarter and the year. David?
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 services revenue grew to $9.2 million reflecting strong customer implementation activity and engagement with Baker Hughes that will make our virtual data and reliability applications even more compelling for oil and gas customers. In Q4, 82% of our revenue was from subscriptions and 18% 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 8 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 continue 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 the cancellation rate. 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 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 the 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, 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 invest in 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 are 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. And 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 to $247 million, non-GAAP operating loss in the range of $119 million to $107 million. For the first quarter of fiscal year ‘22, we expect revenue in the range of $50 million to $52 million and non-GAAP operating loss in the range of $35 million 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. And I will turn the call over to the operator for questions. Operator?
Thank you. [Operator Instructions] We have our first question coming from the line of Daniel Ives with Wedbush. Your line is open.
Yes, thanks. Can you talk just about success that you are having vertically speaking when I think about utilities in 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 here as you will recall and then a couple of years ago we entered the oil and gas business and now that’s a pretty big chunk of our business. We are seeing initial success that’s quite significant in financial services with Bank of America and Standard Chartered Bank and now with 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 as particularly as it was fantastic optimization of the supply chain production optimization. So, I mean, we are clearly diversifying across a wide range of industries. And I think we will 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, 3 and 4 years ago, and 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, as this plays out, just like the relational database business did and the mini computer market did and CRM did, I think that enterprise, the 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 are having with customers, when you are talking to CIOs, CEOs, how it’s changed in terms of where C3 stands today versus even 6 months ago or a year ago? I mean, is it – has it really gone from to just more strategic and it’s almost more of a pull versus push, can you just compare and contrast, especially just given what you have seen the last 30, 40 years? Thanks.
Well, I think we really hit an inflection point after – I mean, the first two quarters of this calendar year where it should have calendar year ‘20, okay, we are tough, right. And we were doing these large enterprise transactions and then COVID hit, Paris closed, Rome closed, London closed, New York closed, Chicago closed. And so that did slow us down. Now, when we get into May, June, July of last year, we saw dramatic acceleration. And this mandate towards digital transformation seems to have made it at the top of everybody’s agenda. And 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 had been. I think that – I think we are doing a pretty good job of demonstrating thought leadership in AI, the work that we are doing with major research institutions like Illinois, Carnegie-Mellon, Princeton, MIT, Stanford, Berkeley, KTH, is kind of really helping us at the high end, but now we have production use cases in all over the place in utilities, all over the place in manufacturing and 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 we are – right now we are pretty optimistic about what the next coming 2 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.
Great. Thanks guys for taking my question. I wanted to ask one, just about the general environment for AI in 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 sales as 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, it’s a good question, Brad. And I think it is changing. If you see like the uptake on Ex Machina, they were selling to basically individual data scientists and citizen data scientists to all these organizations like $500 at a time or something. And the uptake there is pretty substantial. But I would say, it varies from organization to organization, someplace, it’s starting in divisions at other places, like Bank of America, starting at the very top or at or near the top. So, whether we start at the bottom or we start at the middle, we seem to make it to the top sooner or later, Bank of America or Standard Chartered Bank or Koch, it’s this is a rapidly growing hot market, with a lot of people really interested. And they have been – I think they are a little bit frustrated with what they have been attempting to accomplish in the last 3, 4, 5 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 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.
I think it’s a really good question. And the answer is yes. I mean, as you get into selling to small and medium businesses, selling CRM, selling Ex Machina, I mean, there you are selling $500 or $1,000 at a time as it becomes a – as it becomes a NRR game. And NRR has been really less important as a metric for us historically, because we are landing contracts that were so long in duration and so large. I mean, you can remember and fiscal year ‘18, and 19, you were here when we are doing $30 million, $40 million, $50 million deals all the time. And that’s clearly changing now. So, 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. But it certainly looks good in the long run in terms of evening out, getting a lot business 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. So, I think that the existing contracts that we had in place with Shell, Micro and I could be wrong on this, I think it was the second or third contract, okay. And it was about 4 years in duration. Originally, we did a couple of trot production trials with them. I forget what year and those were successful. And then I expanded to kind of a small enterprise deal, then they expanded to a larger enterprise deal, which was 3 or 4 years in duration. Now, Shell is very much reinventing itself around all aspects of this 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 company, but all of Shell’s strategy, but 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 5-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 – it’s a strategic deal. It’s 5 plus years. And it is irrevocable, non-refundable commitment. And it’s a very substantial and important transaction that we think will serve at something of a bell cow in the oil and gas industry, because Shell is 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 are 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 TCV was like in the quarter if it’s really moving down?
Michael, I couldn’t quite hear the second part of your question, could you repeat it please?
So, again, I am sorry about that. So, all about the move down market and maybe you could approach it 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? 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 revenue, our subscription revenue accelerating over the course of the year. And as you can see in our guide, we are looking at a midpoint of 26, going up to 34 Ex Machina 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 on how to continue to accelerate our growth. So in terms of Ex Machina and then in terms of TCV in the quarter, we were at about $7.5 million of TCV in the quarter.
Okay. Alright, Tom. Thanks very much.
Thank you.
We have our next question coming from the line of Patrick Colville with Deutsche Bank. Your line is open.
Hey, thank you so much for taking my question. The presentation is fascinating and I was really interested to kind of hear how you see the market evolving. Just help me understand though, just this quarter and I guess implicit in your guide, it doesn’t seem like this translates 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 help me understand just the kind of puts and takes between this fantastic long-term potential that you have articulated that 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, Patrick, I think we are seriously correct. And I think that the growth projections that you and others had for us and why don’t you even correct me if I am wrong, for this year was about 9%. And I think we came in at about 17%. The – we are seeing, part of what’s going on in Q1 is – we – the growth the year is going to be a very healthy year, Q1 will be a very healthy quarter or you are raising guidance, okay, for Q1 over what the consensus was. Part of what’s going on in Q1 is an artifact of – you have to go back and look at bookings, which I am not going to disclose, okay, for like Q1 and Q2 of fiscal year ‘20 okay. And if you look at ‘19 and ‘20, we are kind of thrashing around quarter-to-quarter in bookings. And there is kind of an artifact there that has some downward pressure on Q1, everything as the revenue kind of waters from bookings, waterfalls out over say 36 months. And 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 that’s a little bit downward pressure on Q1. The Q1 is going to be, it will 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 of next year. I mean, it’s sticking the numbers here, again, the guide suggests quarter a material reacceleration. I mean, I remember the time of the IPO, when we are talking about a number of factors, including the exit of coronavirus. We are talking about collapsing 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 reacceleration of bookings in the second half of fiscal year ‘21, really, okay. And as we – I mean, when we came into fiscal year ‘21 blowing and gone, I think wasn’t the growth rate in fiscal year ‘20, like 91% growth or something?
71%.
71% okay, sorry.
It was big numbers.
It was big number. It was significantly non-zero. Okay, it was big, and then we got kicked in the teeth with COVID. Okay, and the – 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 COVID is clearly over. And digital transformation is 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 as a our more substantial, more reliable provider than we ever have been. So I think what we’re just seeing as the acceleration of business, it’s a good thing.
Great. Thank you so much. Really appreciate for 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. Hey, Tom, I was just wonder if you could speak to just the hiring environment, 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 finding the right types of people to build out the organization these days?
I reviewed those data to date, Jack. It’s 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. And this annualizes to roughly 50,000. And what we’re in the heart of Silicon Valley, this is supposed to be a very, very challenging hiring environment. Of the – of those 12,000 I think we had interviews and one former number there was almost 3,000, and we hired a net of like, 56. So, we have really the brightest and most trained, highly trained and experienced data scientists in the world, and an application engineers and sales people and sales leadership, okay, and marketing leadership, who want to join us. And so we’re very, very fortunate in that respect, we trying to need to figure what’s going on. And get the bottle this, as we go forward, but the rate of interest in people coming to work with at C3 has not slowed down. Okay, and I rate of interest in hiring people has definitely not slowed down. And if you go and I encourage, anybody who’s interested to either you get a pretty good feel for what the culture is like, and what the morale is, like, if you go look it up by Glassdoor.com. But it was, I think, 12,050 people, or 12,500 people who apply 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 wonder could you provide some more context around that. Was that something that just happened organically within your customer base? Or is that the result of maybe some of your partnerships really coalescing any further clarity would be appreciated?
Jack, I don’t think, I said anything like that.
I think Jackie may have heard it in one of my paragraphs.
But 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 in the just strengthening of our performance measures, like RPO. And so what you just saw…
Okay, thanks.
You just saw bookings begin to 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?
Well, oil and gas, I didn’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 navigating $7 a barrel or something, where is it today, you know better than I have a roughly $67 or something like that. So you get to know – it’s easy 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 the segments. We’re not now we’re not snapping in the air. I mean, you’re going to 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’ll put it, 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 oil and gas businesses and the banking business. And those industries today look very healthy.
Okay. As a follow-up, I guess, regarding the show, partnership extension, are you able to comment on the dollar amount? And I wasn’t clear to me whether that is reflected in the 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. And but in terms of the size of it I could tell you, if you take all of our deals, the size of the some of the deals and divide by the number of deals, it’s what I say sounds like $2 million, and that the size of shy, it’s a good one. It’s bigger than a bread box, it let’s say didn’t contribute to bringing our average total contract value down.
Yes. Okay. And 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 there? I think prior analyst was commenting that we see it in the kind of longer term portions. But can – do you look for instance, do you think that the CRPO number could be growing a little faster? A couple quarters down the road?
Yes. This 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 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? Is you going to reimagine it with AI?
Well, I’m not sure it’s exceedingly 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 thing precision health, think banking, think oil and gas, travel, transportation, what have you. That being said guys, CRM today’s an $80 billion addressable market, okay. The next generation of CRM is all about AI enabled CRM, okay, 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, okay, so Boeing has all these they used to sell $60 billion worth of commercial aircraft, I have no idea what they sell today. Okay, but they have a CRM system, probably sales force or Siebel or something, they’re all kind of the same. Okay, and they where they have all the sales forecasts that the guys put in and the sales the systems are just like the systems that you guys have it JPMorgan Chase and everyplace else, the sales guys just put whatever they needed to get it and put it in there to get the sales manager off the back. Okay. And so they put in all of these records already have 35,000 salespeople at Merck, each of which are putting 100 lines of garbage and so you get, 350,000 lines of kind of garbage in your forecasting system. And you think some of that is 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 this a hypothetical, because we’re not talking with them about this, but let’s think about Dave Calhoun is Boeing. And he’s got, he’s got the information that’s in their CRM system about contacts about opportunities about deals that are supposed to close at Lufthansa, at Bank of America at, at Southwest Airlines, and it’s just the information in the sales people put in now imagine combining of that data with almost 9x more that are 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, travel, passenger travel amount, is the country at war, is the country at peace. Okay, and NLP media, if Southwest Airlines is a 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 100 737 Max, this is going to close this quarter? That would be zero, okay.
So you can see how we can take all of those data 10s of 1000s signals from the market. Analysts reports, news reports, stock prices, commodity prices, jet fuel prices, GDP growth rates, is the country at war, is the country at pace and build very precise machine learning models that tell Dave Calhoun, what deals are actually going to close? Okay, not only is that going to set Calhoun aside because they let’s talk about something like the Procter and Gamble, okay, so Procter and Gamble not only needs the revenue – forecast revenue, they need to forecast products, 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, right. So we can build a – we have now demonstrated that we can build these AI models, okay, that are literally in order of magnitude more precise. As it relates to revenue forecasting, customer forecasting, an excellent product, an excellent offer customer churn that what’s going on in CRM today. And you’re going to see us releasing these products this year for banking, okay, for aerospace, okay, for manufacturing, for health care, what have you. And most products will be well perceived that we have done extensive market research on the levels of customer satisfaction in the CRM industry today. And I’m telling you, the levels of customer, these people are hate their vendors, okay.
And so the levels of customer dissatisfaction are uniform, it’s an $80 billion market. And as you what’s the last 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 or some other very key people are joining us. And that is going to be exciting market, 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. I think we’re going to put existing CRM companies out of business, no way 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 this.
Yes, yes. Okay, it’s helpful. And then maybe you could speak to the mix of kind of direct versus partner led business and maybe how that differs today versus what it looked like a year ago?
How do you shift partner we will add? Okay, so…
Partner assisted I guess.
Yes. Well, partner assisted, I think is right. Okay. I’m not really certain we really have any. It’s a great question, David. And we’re going to work and we go to market at massive scale. I would 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. Partner assisted. I mean, it probably right. I mean, I think our pipeline today is larger than it has ever been. I think that this is off the record. I never say it again. Okay, it’s probably off by 10%. But I think our pipeline for this year, it’s like $1.6 billion or something. Okay, 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 dry. Actually, it’s about right. I would say, it would be my – I would speculate that I’m 50% of those transactions, we are engaged with a partner, either Microsoft or a Baker Hughes or something like that, to bring the deal home.
Yes, okay. That’s the 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? I am not so sure. We are going to have to close it ourselves. Okay, but the partner assistance, if your partner happens to be Satya or Judson Althoff at Microsoft, there’s going to, they’re pretty good sales guys. I’m telling you.
Thank you. We have our next question coming from the line of Sanjay Singh with Morgan Stanley. Your line is open.
Thank you for taking the questions. I wanted to follow-up on the previous question 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 out of this to better sort of spending environment or from a sort of go-to-market sales execution, sales hiring perspective, you are starting to see that sales productivity really start to come through the door to help accelerate that, that customer count velocity [ph]?
Well, Sanjay, I think, there are two things that we’re seeing that are very influencing that. Number one, you recall that pre IPO, we’re only elephants having. Okay, we’re only at a major accounts group. Okay. And since then, we’ve been building a, kind of ever judicial enterprise sales organization, a middle market sales organization, and a mass market sales organization. One of our – we did a pretty large transaction, this quarter, I believe, to place on the Microsoft, on the Azure Marketplace, they’ve done thing in Asia, they did, okay. Okay. And it is all you guys, I encourage you to go to C3.ai.com. – C3.ai now, okay, put in your name, address. And credit card number, and for 30 days use, use the X mark and up for free. I mean, hundreds and hundreds of people are doing that. Okay, so and so please do it and please also forget to dial in 30 days and cancel your subscription, okay. But I think there are two things. Sanjay, number one is, remember, you remember we said a couple of years ago we’re putting to do 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 in the internet sales, and then this is combined with the partner ecosystem, being at Microsoft, AWS, Baker Hughes, or what have you. So it’s a resulting in just a much larger diversity of different size 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 the early 2018. We’re executing it and it work.
It makes total sense, though, the follow-up question is, it’s a topic that we’ve talked about for a couple quarters now, Tom which is around like the competitive environment and sort of look at the broader landscape, including the C3 and then some of the other vendors that either own parts of the space or kind of few multiple on pro multiple parts of workflows and data science, machine learning, it seems like, everybody’s doing like a weed. And I know your view is that a lot of customers are stuck in proof of concept health. Going back to that question of customers sort of do the dance with that sort of fits together approach where they come to sort of a end to end platform like the C3, where are we in that journey do you think?
Well, I think everybody’s going to try to build with themselves. And that’s what IT people do. And they try to build relation database systems themselves. They tried to build the ERP systems themselves. They tried to build their own CRM systems themselves. How that worked for Morgan Stanley? Okay. I mean, they tried, okay. They tried to build all of those things themselves. Okay, I was there, okay, how would it work for JPMorgan Chase? I mean, they tried to build all of those systems themselves and today JPMorgan Chase is trying to build their own AI platform, after that comes out of crash just 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 will spend, I don’t know how many hundreds of millions to billions of dollars a year trying to build their own AI platform and then Jamie will be gone and they will begin in some new CEO in, fire everybody and I will buy it from a commercial vendor. That’s the way this works. So, virtually every one of our customers, Shell, ENGIE, Koch Industries, United States Air Force, Army Futures Command, have tried to build this themselves, a bigger use, that would be GE and it could work out so well. And so this is just the phase we have seen this over and over and over in the industry and it’s just a phase that everybody has got to go through. They have to try it themselves and crash and burn a couple times for them. They buy it from a reliable vendor.
I appreciate the background. 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, 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?
Yes, Arvind, 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 you have 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 are doing object identification for the Space Command, clearance adjudication for the Defense Intelligence Agency, sarcastic 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 codes that are running across all of 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 are able to – everything we do is reusable. And so I mean, that’s what people, we have broken the code, we all know 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. So, it’s a 90% of the cost, but 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, but we can all agree I hope that the user interface is trivial. And then the part that differs from the most from installation are the machine learning models. Then the machine learning models we quite hopefully going to agree these are non-trivial, but they constitute maybe 3% of the code.
Terrific. And I know you have 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 are really adding $62 million in revenue in fiscal ‘22. And then, when I look at like fiscal ‘20, which was a good year before the pandemic hit, you added $65 million. So, it seems like the guidance has 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 add more than like $62 million. So, I just wanted to get a sense of how conservative your guide maybe?
Well, Arvind, 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. So we are focusing on being credible. And we are – what we want to do is meet and exceed, beat and exceed, beat and exceed. So, we are – I think that I don’t know how many enterprise application software companies are growing, what’s the expected growth rate in the middle of 33% or something?
34%.
34%. I mean, I don’t know how many enterprise software companies are growing at 34% compound annual growth rates, but I can assure that would be in the top deck, I suspect to not really check this stuff out, but I suspect it’s in the top decile. And right now we improve – we intend to move in the top decile this year. And hopefully, it would come back the next year and move up a little higher.
Terrific. Thank you.
We have our next question coming from the line of Pat Walravens with JMP Group. Your line is open.
Great. Thank you and congratulations on the quarter. So, Tom, you have got oil and gas, financial services, CRM, Ex Machina, can you just tell us for this year, for this coming here, what are your top three sort of strategic imperatives?
It’s really a good question. I think there is strategic imperatives Pat and you will 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 have seen some of this with Ed Cardon, you’ve seen some of this from General Cardon, who is 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 bringing senior leadership into the company in the last 9 months. And we are – and you are going to see a number of announcements there that I think you will agree are significant. And I think that is the – I mean, we have the technology. The market is much bigger than we can address in rapidly growing. The technology foundation we have is very rich and it works. We have us – we are leaving in our wake a string of highly satisfied customers. I think we are doing a pretty good job at building brand equity. The competitive dynamics of this market are not very significant. I mean, basically, we are selling vehicles and everybody else is selling ball bearings and wheels and carburetors, okay. And we are selling vehicles, okay. And so there is 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 in federal systems, in Asia-Pacific, in Japan, in Europe, in manufacturing, healthcare, telecommunications, aerospace, etcetera. I think its human capital. 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, we thank you for taking time out of your busy day, okay to check in on us. We appreciate your interest. And you know that we are – it is now June of 2021, I am 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 2, 3, 4 years, I can tell you, we approach it with great enthusiasm. And we will see how this turns out when it’s over, but I think there is 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.