Good afternoon, and thank you for attending today's C3.ai earnings call for the fourth quarter of the fiscal year 2022. My name is Jason, and I'll be the moderator for today's call. All lines will be muted during the presentation portion of the call with an opportunity for questions and answers at the end. If you'd like to ask a question, please press star followed by one on your telephone keypad. I would now like to pass the conference over to our host, Paul Phillips, Vice President of Investor Relations.
Good afternoon, and welcome to C3.ai's earnings call for the fourth quarter of fiscal year 2022, which ended April 30, 2022. This is Paul Phillips, VP of Investor Relations. With me on the call today are Tom Siebel, Chairman and CEO, and Juho Parkkinen, Chief Financial Officer. After the market closed today, we issued a press release with details regarding our fourth quarter and full year 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 in response to your questions, we may discuss metrics that are incremental to our usual presentation to provide greater insights into the dynamics of our business or our quarterly results.
Please be advised that we may or may not continue to provide this additional detail in the future. With that, let me turn the call over to Tom for his prepared remarks. Tom?
Thank you, Paul, and good afternoon, everyone. Thank you for joining us. I'm here with Juho Parkkinen, our Chief Financial Officer, and I am pleased to share with you our results for the fourth quarter and for the entire fiscal year of 2022. Bottom line, it was a great quarter. We finished the quarter with $72.3 million in revenue, up 38% year over year, exceeding our guidance and exceeding, I believe, all analyst expectations. I haven't really looked lately at the metrics of high growth software companies, but I expect that would be in the top decile of growth rates. Subscription revenue was $56.3 million, up 31% year over year. Our non-GAAP gross profit was $58.5 million, a 43% improvement over the previous year.
We ended Q4 of fiscal year 2022 with GAAP RPO of $477.4 million, a 62% increase year-over-year. Non-GAAP RPO is $516 million, a 50% increase year-over-year. We continue to sustain healthy non-GAAP gross margins of 81%. Our free cash flow for the quarter was a negative $14.8 million, a 46% improvement year-over-year. We finished the quarter with $992 million in cash and cash equivalents, so we have roughly $1 billion in the bank, and at this rate, it'll take quite a few quarters to deplete our cash reserves.
Looking at the results for the year, they were quite good, exceeding our guidance and exceeding analyst expectations, finishing the year at $252.7 million in revenue, a 30% growth rate over the previous year. Subscription revenue was $206.9 million, a 31% increase year-over-year, and our non-GAAP gross margin increased a little over five points to 81.7%. Now, I want to talk a little bit about the addressable market opportunity, which is really quite staggering. Enterprise AI software is predicted to be almost a $600 billion market by 2025. We spent the better part of a decade building what we call actually more than a decade now, building what we call the C3 .ai Suite.
That is a software platform that provides all of the services necessary and sufficient to design, develop, provision, operate even the most complex enterprise applications. On top of that, we have developed and delivered to the market now 42 enterprise AI applications that meet the needs of manufacturing, utilities, oil and gas, chemicals, aerospace, state and local government, other industries. Now, enterprise AI is a very complex market, and it has a lot of players who do a lot of things, and it is confusing to investors, it is confusing to customers, and it is confusing to the market at large. Because we have all of these kinds of bright, shiny objects out there that are provided by hyperscalers and are available as open source solutions.
They do things like provide machine learning libraries or virtualization or data persistence or machine learning pipelines or whatever it may be. Many of these are great products. Many of these are great companies. Again, this is really very confusing to investors, to customers, and to the market at large. C3.ai is frequently lumped into this category. I wanna take a minute and talk about how we fit into enterprise AI, because it's quite different from all this, and it's quite different from the way that these companies fit into the market. These organizations generally make piecemeal components that do interesting things like platform-independent data persistence, AutoML, or whatever. Now, the way that we think about enterprise AI applications is the way the market has thought about enterprise application software for the last few decades.
When we first began developing enterprise application software in the early eighties at companies like Oracle and SAP and later PeopleSoft and Siebel Systems and others, we basically built these applications on top of relational database systems. On top of relational databases, we built a set of development tools for building screens and reports and forms and whatnot, and we used those to build families of applications that solve business problems like CRM and ERP and manufacturing automation, supply chain management, what have you. A few decades later, this has grown to be roughly a $500 billion software market, and everybody understands it. These applications are used to solve very real-world business problems. They enable companies, for example, to report their inventory balances and their supply chain.
A supply chain, say, for a Boeing, for a Boeing 777 might be 1 million components in a supply chain that stretches from South Carolina to Shenzhen and consists of resistors and transformers and flap actuators and propulsion devices and flight management systems. They wanna be able to report every 30 days or 90 days or 365 days exactly what was the inventory of each item. By the time you add the Boeing 777 to the 787 to the 767 to the 757 and the Boeing 737 or the Boeing 707, this is a pretty big parts inventory that you need to be able to report accurately. You might want to be reporting on what your customer churn was 60 days ago or 90 days ago.
Okay, if you're a bank, you might have to report on how much fraud took place, how much anti-money laundering took place 90 days ago or 180 days ago. If you don't do this correctly, as CEO, you get to rewrite your resume, you get to pay billions of dollars in fines, and you might go to jail. It's really quite important to get this right. You might wanna report on what your customer churn rates were at, for example, at Verizon. This enterprise software has become a big market and, you know, that you know of pretty well as ERP and CRM and supply chain management and what have you. I was there when we started it, and today it's roughly a half a trillion-dollar business. Now, these applications are inherently descriptive in nature.
They provide a company a perfect 20/20 hindsight into what happened three months ago, six months ago, a year ago. Now, at C3.ai, we spent a decade and almost $1 billion building a software technology stack that consists of a platform as a service, an application development platform, and low-code development tools, and now including 42 turnkey enterprise applications. These with C3.ai, we make these existing enterprise applications predictive in nature. Okay, now instead of using a database or a relational database for data storage, we're using the cloud. Okay, we're using existing ERP systems and CRM systems like SAP and Salesforce and Oracle and what have you.
We built an AI application layer that makes these applications predictive in nature, so they can tell us what's going to happen in the future so that we can change the future. Rather than simply telling us how many parts we had in each inventory bin historically, a predictive AI application will tell us exactly how many parts we need in each bin in each of the next 180 days to meet the demand function, okay? Rather than tell us how many customers left us 90 days ago or a 180 days ago, these applications will now tell us which customers by name are going to leave us in the next 180 days, so we can take action to retain them.
Rather than tell us, for example, the number of fraudulent events that we had some time ago, it will identify fraudulent events in real time, so we can prevent the fraud from happening. The beauty of enterprise AI, okay, is when we apply AI to the market of enterprise applications, they become predictive in nature. Okay? We can predict the future and change the future. Now, this promises to be order of a $600 billion market not too many years down the road. I believe that if we look two, three, four, five years out, this is a complete replacement market for everything that happened in enterprise application software in the last three decades. I do not believe that in two years or three years or four years, companies are gonna be satisfied knowing what their customer churn was 90 days ago.
They're gonna demand to know which customers are gonna leave if they don't take action. Rather than know what our non-deployment rate was for tractors, aircraft, automobiles, they're going to want to have predictive maintenance applications that tell them which machines are gonna fail in advance, so they can fix the devices before they fail and have lower failure rates. That's the big deal. That's what enterprise AI is all about. Now, when we look at the companies that many people in the market, investors and customers, okay, consider to be competitors of AI, okay, really, none of these are competitors. They're all in fact partners. Now, like C3.ai provides out of the box, okay, all of the services necessary to design, develop, provision, and operate an AI application.
Many of our customers, in fact, all of our customers, will have some experience working with AI tools, and they will want to use many of these third-party products like Databricks for data virtualization or Snowflake for platform-independent data persistence or Amazon SageMaker for citizen data scientists or Python-developed machine learning tools. C3.ai provides the orchestration layer that enables customers to easily knit these solutions together into a cohesive solution. All of these applications, both open source and proprietary, are entirely compatible with the C3.ai platform. We need to think of all of these things. Alteryx, TensorFlow, AWS, Google Cloud, Databricks, these look more to us like partners than they do like some competitors. Let's take a look. This would be example of the Shell.ai platform, where on top of Azure, they put C3.ai.
Because they have investments of value in things like Kubernetes for containerization and Databricks for virtualization and TensorFlow for machine learning libraries, MATLAB, TIBCO, Alteryx, what have you, we enable them to, you know, very easily incorporate these into the C3.ai platform architecture. This is Shell.ai, but virtually 100% of our customers, 100%, are using some combination of these other products with the C3.ai platform. It's really quite different than I think what it is perceived to be. Bottom line, all of these independent products that appear to some to be competitors are in fact partners. Okay, they're partners at Shell, at Koch Industries, at the United States Air Force, at virtually every C3.ai customer. Now, I want to address the issue of customer count.
Now, our customer count has been growing quite substantially in recent years. In the last year alone, it grew from 151 customers to 223 customers. If you look at our diversification by industry, it's really becoming increasingly diverse. Like oil and gas, which is a pretty good market to be in today with oil at, you know, in excess of a rough order of $100 a barrel. Pretty good business. At the same time, we've seen a lot of diversification outside of oil and gas. This, if we look, this is diversification of the industry, including oil and gas. This is bookings, okay. This is bookings without oil and gas. You can see that while our year-over-year, our bookings in oil and gas grew 95%.
Outside of oil and gas, it grew by 116%. Let's talk about customer penetration. We are very certainly focused on landing new customers. That being said, when you think about many of our large global customers like Shell, Koch Industries, United States Air Force, Department of Defense, ENGIE, we are very much focused on penetrating these customers deeply. If we look at this customer base that we have today, it might be 5%-10% penetrated. Now, with many companies in the AI space or the SaaS software space, investors are really interested in how many new logos did the vendor add in the quarter at perhaps $10,000 or $20,000 each. That's not the business we're in, okay?
We are in the business of landing very large customers, okay, investing in those customers, and making them very large and very successful over a period of years. Let me give you a couple of examples, okay? Shell is, I think, the 5th largest company in the world, one of the largest hydrocarbon producers in the world, and Shell has standardized on C3.ai across all lines of business, upstream, downstream, midstream, integration of renewables. Today, they have over 10,000 pieces of equipment monitored by our platform. They have 23 assets in production. Now understand an asset at Shell isn't a pump or a valve. An asset at Shell is something like Pernis. Pernis being the largest refinery in Europe that I think processes order of 0.5 billion barrels of oil a day.
An asset for Shell would be like Nigeria LNG, okay? An asset of Shell might be larger than, you know, 50% of the companies in the world. Okay, they're on the road today. They have 65 assets in production this year. At our users group in March, okay, Shell stood up on stage, and they said they realized in front of all of our customers at our users group conference, and then they realized $1 billion in economic benefit from their C3 investments last year, and they expect to realize $2 billion in economic benefit from our investments this year. Okay, now I ask you, how many customers are you aware of from SAP, Salesforce, Siebel Systems, Oracle Corporation, whatever it might be, all five companies.
How many customers are you aware of who have stood up on stage and said that they are getting $1 billion , $2 billion , $3billion , $4 billion, or $5 billion a year in economic benefit from that solution? I would argue that none of you have ever heard that because it's never been said. Let's take a look at the United States Air Force Rapid Sustainment Office. Okay, this is predictive maintenance for aircraft, and the Air Force has roughly 5,000 aircraft. Here we're doing AI-based predictive maintenance for B-1 bomber, F-15, F-16, F-18, F-35 Joint Strike Fighter. Look at the speed. You know, this project plan shows the speed at which we bring these applications into production. What is this all about?
This is about integrating all of the data about missions, about weather, about fuel, telemetry from the devices on the aircraft, maintenance systems to build predictive models that'll predict what device is going to fail, you know, 50 or 100 flight hours before it fails, so that we can avoid the failure. You know, some of these aircraft cost $100 million a copy, and their current availability rate is, say, 50%. With C3.ai, we can increase the availability by 10%, 20%, 30%, and now we deal with the scale of the United States Air Force, this is worth $ billions in economic benefit annually. I believe we have 16 aircraft platforms live today, and we expect to have 22 platforms live by mid-year.
Deeply penetrating these accounts is what C3.ai is all about. We continue to be focused, okay, on adding new customers. At C3.ai, it's more important to look at the lifetime value of our customers than at how many new customers that we're signing. You know, yes, our customer base is growing. The new customers in the quarter would include PwC, EY, the County of San Mateo. Cargill is a recent customer. Again, what's really more important, okay, is the penetration of these customers. Koch Industries, which is more than a $100 billion business and became a customer a couple of years ago, made a decision in the quarter to standardize on C3.ai across all lines of business. This would include Flint Hills Resources, Georgia-Pacific, Molex. All Koch business units are standardizing on C3.ai.
Similarly, at Cargill, we're doing predictive supply chain optimization and supply network risk for one of the largest food producers in the world. The value of this is quite significant. We're helping feed the world at a time when much of the world is facing famine. This is what it means for bookings at C3.ai. This is an example of a large integrated energy company in Europe. Their initial contract with us was for about EUR 300,000. Over 8 years, it has continued to grow to EUR 120 million. This is an example of a large chemical company in the United States where their initial contract was for $9 million, and then it grew to $14 million, and then $59 million.
This company stood up on stage at our users group and said they expect to realize $1 billion in economic benefit from C3.ai this year. $1 billion. This is a major U.S. government agency and how, you know, and how we have penetrated that. This is a large, industrial manufacturing company, what have you. While we might start small, and we might start with a trial, a free trial, a $50,000 trial, a $500 product, a half a million dollar trial, or initial project for a couple of million dollars, our goal is to realize, you know, sometimes $1 billion, $2 billion, $3 billion, $4 billion in annual economic benefit for the customer.
As you can see, this is quite a different story, you know, from what you're used to seeing in, you know, in enterprise application software, where people are selling hundreds of things for $20,000 apiece. Our primary focus is penetrating existing customers. This is an example of a utility in Europe that today is generating $ billions in annual benefit from smart grid analytics. Now, the growth strategy, you know, I've covered this. You're all familiar with how we're growing the business. We continue to grow geographically in North America, in Europe, in Asia Pacific. At the same time, we're building vertical market sales organizations in financial services, manufacturing, what have you.
We're aligning with go-to-market partners in each vertical, Baker Hughes in oil and gas, FIS in financial services, Raytheon in aerospace and defense. We have very meaningful horizontal market partnerships with hyperscalers, very significant relationship with Microsoft, significant and growing relationship with Google, HPE, NVIDIA, and others. This is how we're expanding all facets of theCUBE to establish a leadership position. We've made a big investment in this over the years. I've talked about it. I've talked to you about this. You know, how has this investment paid off, you know, with these partners, hyperscalers, vertical market partners, utility partners, oil and gas partners? You know, it's paid off pretty well.
If we look at our bookings for last year, 64% of our bookings, okay, was generated in partnership with these market partners. This is becoming really quite significant. We have a substantial and growing partner ecosystem. We have, you know, a recognized market leadership. We have a proven track record of success. We have a veteran management team. We have a very high-performance culture. We have excellence in execution. Big picture, C3.ai today is a quarter of a billion dollar software business growing at roughly a 40% compound annual growth rate. We have roughly $1 billion of cash in the bank, and our strategy is quite simply to establish and maintain a market leadership position globally in enterprise AI. Okay, let's talk about guidance, okay? Okay. As I mentioned, the addressable market opportunity is large and expanding.
Our pipeline continues to expand. Our customer footprint is growing. Our balance sheet is rock solid. I have never been more optimistic about C3.ai than I am today. We have exceeded revenue guidance for each of the six consecutive quarters that we've been a public company, and we are tracking exactly to the long-term plan that we laid out during the IPO roadshow. Listen, go play back the tape. It's still on the web. We are tracking exactly to what we said then. Our revenue growth rate was 38% in the year ending April, up 17% from 17% in the prior year. Now in the past few years, as you know, we've been making substantial investments in branding and advertising. These investments have contributed substantially to our brand equity and market recognition.
I'm confident these were prudent and productive investments. We largely created and now lead the market category of enterprise AI. That being said, it's not lost on us that there's been a fundamental shift in capital market expectations regarding cash flow. Look, until recently, the market rewarded rapid growth at any cost. This has clearly changed. The market is currently demanding sustainable growth combined with free cash flow. We are confident that we can achieve that goal. Our economic model is quite healthy. This is a structurally profitable business with a strong cash balance and a non-GAAP gross margin of 80%. Our investments in branding and advertising over the last few years have been very effective in establishing C3.ai as a market leader in enterprise AI.
Those investments will now permit us to dramatically reduce our branding investments as a percent of revenue going forward. We'll benefit from cost economies of scale in product marketing and development, and we will realize additional savings from expanding the bulk of our engineering and services capacity in our new Guadalajara, Mexico, facility. To drive growth, we will continue to expand our investments in sales, partner capacity, and service capacity commensurate with revenue growth. Our target is to generate sustainable positive free cash flow within eight to 12 quarters. Under stable market conditions, I would guide to a 30% or greater growth rate for fiscal year 2023. With the current economic and political uncertainty, however, and pervasive market pessimism, we are inclined to set the expectations bar low.
While we are much more optimistic about the business, we're not sure that guiding high is of any benefit to our shareholders. Also, candidly, we did see some business that we expected to close in Q4, okay, move out of the quarter. There is still lump, you know, too much lumpiness in our pipeline. Taking all of this into consideration, we believe it is prudent to guide to provide fiscal year 2023 Q1 revenue guidance of $65 million-$67 million. Fiscal year 2023 growth targets of 23%-25%. By the way, there's a typo on this slide that the vendor was not able to pick up. It's so. It says 22, and in fact, it should say 23, so I apologize for that error.
When market conditions stabilize, we expect to target 30%-35% steady-state top-line growth while continuing to grow free cash flow to 20%, non-GAAP targets. Free cash flow, that's just a 20% target. That's for net non-GAAP, okay? Now, I'm gonna turn the call over to our experienced and accomplished Chief Financial Officer, Juho Parkkinen, to provide additional color on our business results and plans, and then we'll throw this open to questions. Juho, over to you.
Thank you, Tom. First off, I want to quickly recap on the summary financial results. As Tom mentioned, we ended the quarter with revenue of $73.3 million or 38% growth. Subscription revenue increased by a healthy 31% year-over-year growth. I would also like to highlight the remaining performance obligations of $477.4 million, a 62% year-over-year increase. Further, during the quarter, we repurchased approximately 720,000 shares for $15 million under our share repurchase program announced in Q3. With respect to the full year, we are roughly a quarter of a billion-dollar business, as Tom mentioned, with a 38% year-over-year increase, and we've been able to maintain really quite excellent gross margin rates of 39% for the year, which is a three-point increase from the prior year.
Here are the trends from the past year indicating, again, a nice healthy growth on a year-over-year basis. Moving on to the deal balance, we were quite happy to see a 35% sequential increase in deals to close 27 deals during the quarter. We saw a nice increase with respect to our band of less than $1 million deals where we do a lot of transactions in trials with customers. In the higher bands, we saw application and platform deals, whether it was with new customers directly into enterprise deals or renewals or expansions with existing customers. Overall, our path towards a lower average TCV continues to improve, where at Q3 we were at $5.6 million and now in Q4 our average TCV was $2.9 million.
With respect to the revenue mix, subscription revenue was 78% of Q4 revenue and professional services was at 22%. When we think about the sizes of the deals we make with some of the most known entities on the planet, it's non-rational for us not to invest in these customers with professional services. We generally see expansions in subscription as a result of successful pro serve engagement. We were able to improve our gross margins and our non-GAAP operating margin during the period as well. Path to profitability. We spent some time this quarter thinking about the long-term prospects and the long-term path to a sustained operating profit on a non-GAAP basis. We've broken out for everybody's benefit, sales and marketing into separate marketing and sales lines.
In addition, you see the traditional research and development and G&A as well as cost of revenue. The key takeaway is that we currently operate at a negative 29% non-GAAP operating margin. We are confident that we have a robust executable plan to get to an operating profit position sometime in FY 2024 to FY 2025 range. We believe that we are structurally profitable and are able to maintain our gross margin on a prospective basis. As we have indicated during the IPO, we have invested heavily in brand recognition, which we believe has been very successful. We believe that we have reached a point where from here we can sustain our brand with lower investment. With respect to our sales team, we will continue to invest in additional capacity on a global level.
With respect to research and development, we're very pleased with our start with our Guadalajara Application Development Center professionals and expect strong growth in that team. The natural benefits from economies of scale, combined with the lower human capital costs, will drive R&D spend lower as a proportion of total revenue. Finally, for G&A related costs, we expect economies of scale to reduce the proportional spend in this category. Overall, we're excited about our Q4 results and are looking forward for the upcoming fiscal year. With that, it's time to hear the questions. Operator?
If you would like to ask a question, please press star followed by one on your telephone keypad. If for any reason you'd like to remove that question, please remember to press star followed by two. Again, to ask a question, press star one. As a reminder, if you're using a speakerphone, please remember to pick up your handset before asking a question. We'll pause here briefly as questions are registered. Our first question is from Arvind Ramnani with Piper Sandler. Please proceed.
Hi, you know, thanks for taking my question. You know, just really wanted to ask about, you know, guidance. You know, on the last earnings call, you know, although you didn't provide formal guidance, you had talked about being comfortable with consensus, which was about 33% growth. You know, when I look at this year's number, kind of growth is closer to like, you know, mid-20%. You know, if you can just kind of talk about a change in environment that's caused kind of the revision of guidance or is it, do I look at your guidance as sort of more sort of conservative and this is a starting point for the year?
Well, hi, Arvind, it's Tom. Thanks for the question. You know, I haven't seen a lot of enthusiasm and cheer, okay, in any market activity in the last few months since our last call. I would say that, you know, what we're seeing from the market, you know, is really quite dire. You know, I think that given everything that is going on in the market, okay, you know, it seemed prudent to us to, you know, set market expectations at, you know, conservatively, and that's what we did.
Perfect. Yeah, that's great. You know, just in terms of kind of bookings growth, you know, still seems sort of healthy. If you can kind of double-click and give us kind of a little bit granularity where you're seeing kind of bookings growth from like the particular industries or clients that you're seeing strong growth from in terms of bookings.
Yeah. Well, if we look at, let's see, where's Q4? Let's see. 42% of our bookings were in Manufacturing, 18% in Financial Services, 15% in Defense and Aerospace, 13% in Oil and Gas, 4% in Accounting Services, and then it goes into agriculture, food processing, retail, hospitals. You know, it's becoming increasingly diversified.
All right. Perfect. That's pretty helpful. I don't know. I'll hop back in queue for further questions.
As I mentioned, for the year, I think booking growth in oil and gas, which is a big business for us and a good business, was 95%. Outside of oil and gas, I think it was 115%.
The diversification strategy is playing out well.
Yep. I would agree with that.
Thank you for your question. Our next question comes from Patrick Walravens with JMP Securities.
Oh, great. Thank you. Hey, Tom, can we start by hearing a little bit more about the deals that slipped in Q4?
Let's see. I'd have to look at the pipeline. I don't really have that one on my desk, Pat. I would say that we did see a number of deals move out of Q4 into Q1 and Q2. They didn't disappear, and they weren't lost. They just kinda moved, and they're lumped to it. There's still lumpiness in the business. We did close how many deals in the course of the quarter?
27.
27. The number of deals is quite-
High
Quite high. We had, you know, honestly, we had a number of deals that, you know, we expected to close at the quarter but didn't. The bookings number was not as high as we'd like to be. That being said, the revenue growth exceeded our expectations and everybody's expectations for the quarter end of the year.
Yeah. Can I ask how May has been so far?
How is what?
How's the last month been since the beginning of this quarter?
You know, I'm not prepared to comment on the business as of the end of the quarter, Pat. You know, we've given our guidance for what we think is gonna happen in Q1. So far, I don't think I'm really quite confident that we've not fallen short of our guidance. I think we've hit it.
Okay.
However many quarters we've been a public company, we've exceeded guidance. Six? Yeah.
Yeah. Okay. It seems like Baker Hughes, I mean, last quarter you called out Baker Hughes 'cause it contributed, I forget what the percentage was, but a really big percentage of the booking. With Baker Hughes, it seems like it was softer this quarter. Is that a fair assessment?
Well, oil and gas was 13% of our business in bookings, so I mean, it was pretty strong. Oil and gas last year grew by 95%, which is pretty strong in bookings. I would not describe it as soft. Did some oil and gas deals move out of the quarter? Yes.
Yeah. Okay.
It's quite healthy.
Okay, great. Juho, one for you, which is so, can you repeat the how much of the. You have a $100 million buyback plan, right? I think you told us how much you had bought back, and I missed it.
Yeah. It was $15 million to 720 shares.
720,000 shares. Okay, great. Thank you. Oh, sorry. Last one. One more for you, Juho. What will free cash flow for this coming year if the operating loss is -$76 to -$86, how should we think about free cash flow?
Well, yeah, that's a great question. I think on a cash flow basis, we still have a lot of lumpiness in that. I think on a more longer term perspective, as we are gonna reach the operating profit goals that are outlined, you're gonna start seeing a more sustained operating or free cash flow positive. As we march towards that goal, there's gonna be lumpiness. There's gonna be periods where we're gonna be closer to positivity and then periods where we're gonna be a little bit more free cash flow spent.
Okay. Just so we don't have unpleasant surprises in Q1. Just for Q1, you guided an operating loss of -$23 to -$28. Should we expect cash flow to be in that range? Worse? Better? How should we think about it?
I think that's a good question, Pat. I think more broadly speaking again, there's gonna be, we're gonna have some activities. I think one of the things that you're aware of is that we're having to build out on the new lease. As part of that, we'll be incurring some cash outflow items, which don't show up as operating expenses until years after, since they're capitalized as part of the new office.
The tenant improvements.
Yeah
In the office building that we're moving into. Yeah.
Okay. All right. Thank you.
Thank you for your question. Our next question comes from Brad Sills with Bank of America. Please proceed.
Hey, this is Adam on for Brad. Thanks for taking our question. So for you, Juho, just a quick one. How should we be thinking about the Q1 guide in terms of the mix between subscription and professional services revenue? It's kind of been, you know, moving into a higher mix of pro services, so just wanted to get your take on how we should be thinking about that going forward.
I think that's a great question. We've said earlier that we think a long-term target for this mix is probably in the 10%-15% range. Obviously, this quarter, we ended at 22%. Last quarter, I think it was 18%. I think you should expect to be somewhere in the mid-teens, but there's still gonna be some activities in the quarter that may change that. I think that's a fair assumption at this point.
Okay. Super helpful. Quick one for Tom. You guys kinda called out in the press release the expansion of One Medical. Can you just talk about what the starting point looked like and then how that ultimately evolved into becoming an Ex Machina customer? Thank you.
Ex Machina, I believe that One Medical began as an Ex Machina customer and has expanded as an Ex Machina customer. If I'm not mistaken, that's the extent of the product. We have many customers that are only using Ex Machina, and that's one of them. Regarding the professional services question, I wanna say, I mean, think about kind of what's going on and what we do, where we're investing. You know, maybe we have a $1 million deal or a $10 million deal or a $20 million deal with a company that makes it very clear that if we succeed, there's a $100 million in business there.
You know, for right now, as we establish market presence and we establish successful customers, it's kind of irrational for us not to invest professional services in those accounts. Now, professional services for us is a very high margin business. But that being said, you know, when we can take a company from EUR 300,000 to EUR 120 million and do that kinda over and over again, to not invest in professional services in the first three years, few years to get them live, I would suggest to me it's irrational for us not to do that. In the short term, it's pushed up our professional services revenue a little higher than we would like to see, but you know, we're achieving the objective of market penetration.
All right. Sounds good. Thank you very much.
Thank you for your question. Our next question comes from Michael Turits with KeyBanc. Please proceed.
Hey, this is Eric Heath on for Michael. Tom, on the couple deals you called out as pushing out of the quarter, I was curious if there was any commonalities across those deals, either by geography or vertical.
I would say they're cross verticals, and it's cross geographies, and somebody needed to get budget approval, or they needed to get something signed by some, you know, senior executive, and it didn't get signed in time, or there was some committee that it needed to go to, or the committee didn't get scheduled. You know, some of these are in Europe. It's kind of Europe, the deal time, you know, Euro time. Many of these are large organizations where they're very bureaucratic in their processes and, you know, they need to get board approval or CEO approval or CFO approval or whatever it happened, and it just. You know, they're operating on their timeline and not ours. That's all. I would say it's pretty much across industries and across geographies.
You know, we didn't see any specific industry fall apart. I would say, you know, given the kind of the market dynamics of what's going on with, you know, supply chain disruption, I mean, probably, you know, one of our biggest products is supply network risk and stochastic optimization of supply chain. This is becoming, you know, really, you know, mission-critical. Okay. You know, associated with all of our applications were, as you can see from our presentations, you know, our discussions with the customers is, you know, how much money are they saving in a year. As people start to tighten their belts in a, what might be an economy that's turning down, we, you know, provide tools that enable them to tighten their belts very cost effectively.
That's helpful. It looks like you had some nice drawdowns of the $500 million authorization within the DoD this quarter. Just curious what else you might be seeing in the pipeline, specifically with the DoD, and maybe just any broader commentary about opportunities you see in the federal space.
DoD business looks good. Okay. You know, we've had continued penetration in the Air Force with RSO. That is now accelerating at a. You know, I think that offers a big opportunity to accelerate. We have, you know, two or three other agencies, you know, in the defense intelligence community that have made, okay, and are processing large C3.ai procurements. You know, we have, I think, $600 million in dry powder there almost to draw down, okay, and in contract vehicles that are in place, and we're working on additional contract vehicles at the same time. We're very optimistic about the U.S. defense intelligence and civilian businesses.
Got it. Thank you. That's all from me.
Thank you for your question. Our next question comes from Bob Huang with Morgan Stanley. Please proceed.
Hi, this is Bob filling in for Sanjit today. Thanks for taking the question. First, maybe if we can talk about just the billings for the next quarter and maybe for the full year a little bit. Obviously, fourth quarter billings is seasonally high, but it was probably a little bit lighter than what we thought it would have been. Maybe if you can just give us sort of a trajectory or a better understanding of how we should think about billings going forward for the next 12 months or so.
Go ahead, Juho.
Yeah. Thanks, Bob, for the question. I think some of the things that ties to what I was mentioning earlier to Pat on the cash flow item. We transact in. We have large deals with large multinationals, and these individual payment terms with specific customers impact the calculated billings metric that you're looking at. At this point in our company, we're gonna have a lot of lumpiness that you see this. You could have an individual quarter where the calculated billings looks really good, and then the next quarter it could be a little bit less. I don't think it's a metric that you need to focus on particularly intensely.
Okay. Thank you. That's very helpful. My next question. Just you obviously have had some or quite a bit of success on the energy sector, oil and gas and such. In terms of various verticals that you are in, as well as geography, like for example, Europe versus U.S., oil and gas versus machinery, what verticals are you confident or feel good about going forward, and what are maybe some of the verticals or areas that you might wanna keep a closer eye on going forward?
Energy looks strong. Utilities look strong. Oil and gas look strong. Chemicals look strong. Manufacturing looks strong. We really haven't penetrated telco yet. I think there's big opportunities there. Financial services there, I think there are big opportunities there. We're starting now to penetrate consulting companies, EY, PwC, and others. I think there's gonna be big opportunity there, where we're providing them tools to accelerate their what they do. Yeah, I think it's. The question is, I mean, ultimately, this is just like CRM or like ERP, all industries adopt. It's just that, you know, which industries adopt at which rates.
You know, interestingly enough, we're seeing a lot of interest in agribusiness, which is, you know, there's huge supply chain problem globally as it relates to agribusiness as the world faces kind of potential famine associated with wheat and rice production. We're doing there with some work with Cargill and others that's really interesting and really important. You know, in general, we don't really see, you know, right now a lot of softness out there. We do read the newspapers and read what you guys write and, you know, we haven't seen a lot in the newspapers. We don't see it, our business looks quite good. You know, I think as long as we didn't read the newspapers or turn on the TV, everything would be fine.
Thanks. That's very helpful.
Thank you for your question. Our next question comes from Pinjalim Bora with JP Morgan. Please proceed.
Looks like we lost JP Morgan.
Oh, sorry, I think I was talking to myself on mute. Apologies. I wanted to ask you about the deals that got pushed out. From your conversations with those customers, is it entirely driven by macro-related considerations? Or do you think, is there an element of the sales organization changes that you had done or the amount of sales capacity that you have currently given the tight labor market?
Our sales capacity has grown pretty considerably really. It's not a sales capacity issue. It's just, I mean, I'm looking at these, you know, transactions that we expected to close. You know, here's one in the United States government. Here's an insurance company. This is an oil and gas company. Here's a beltway bandit, a large energy company in Europe, pharmaceutical company in Europe, bank in Canada, food services company in the United States, a retailer in Europe, civilian agency, oil and gas company. I'm going right down the list. Oil and gas company in Africa, U.S. federal agency, U.S. federal agency, U.S. federal agency, large big box retailer, division of the Air Force. Here's a company I don't know what they do.
The Department of Defense, large food provider, a local county. Here's, you know, there's the County of San Mateo with roughly 1 million people in it. Large, you know, a large credit card provider, U.S. intelligence agency. Insurance. I just read right down the list, okay, of deals that we were looking at that we were expecting. I would say particularly the ones that we were absolutely expecting in the quarter would be intel agency, insurance company, a large European oil company, beltway integrator, European energy company, European pharmaceutical company, large exchange, stock exchange, bank in Canada, food services company, and manufacturing company in Wisconsin. It varies. It's across industries, across geographies, and it's just. It's not that their business has gone south or that they're going under.
It's just that, you know, they weren't processed in time.
Understood. I guess one thing that people trying to understand.
That was not from memory. I was reading right from the list.
Yep, understood. Well, the follow-up to my follow-up would be that AI obviously or C3 AI obviously saves a lot of money when deployed. You have really big economic benefits, right, when deployed. However, it seems like it is a factor of the large initial outlay, which is kind of creating these problems, right? Otherwise, people should probably adopt AI during a slow economic environment, wouldn't you say?
Well, I'm not sure. I mean, the initial outlay sometimes is $50,000, sometimes it's $10,000. You know, the initial outlay at a $300 million-$1 billion-dollar oil company was $300,000, which might seem like a lot, but it's not a lot for a $300 billion-dollar company. I'm not sure the initial outlay is. I accept that. You know, as you saw from the slides that I showed you know, frequently the initial outlay is $50,000 or $300,000, and then it grows every time.
So the average-
It's not $20,000.
The average entry point is [crosstalk]
It's large compared to a lot of the other things that you look at in the AI space where I think their average sales price is, like, $20,000. We're not in that game.
Right. Understood. Thank you.
There are no further questions waiting at this time, so I'll pass the call back over. Go ahead.
Right. Thanks everybody for your time. We'll wrap up the call now and appreciate everyone's interest. Have a good rest of your day.
Thanks, everybody.
That concludes the C3.ai earnings call of the fourth quarter fiscal year 2022. Thank you for your participation. You may now disconnect your lines.