C3.ai Inc (AI) 2022 Q4 法說會逐字稿

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 will be the moderator for today's call. (Operator Instructions) 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 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 pleased to -- 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 analysts' expectations. And I haven't really looked lately at the matrix 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 '22 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 at the bank -- in the bank. And at this rate, it will 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 5 points to $81.7 million.

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 in the most complex enterprise applications.

And on top of that, we have to develop and deliver to the market now 42 enterprise AI applications that meet the needs of manufacturing, utilities, oil and gas, chemicals, aerospace, state and local government and 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 -- some are available as open source solutions. And they do things like provide machine learning libraries or virtualization or data persistence or machine learning pipelines or whatever it may be. And many of these are great products. Many of these are great companies.

But again, this is really very confusing to investors, to customers and the market acquired. And C3 AI is frequently lumped into this category. So I want to 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 piece meal 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. Where we first began developing enterprise application software in the early '80s 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.

And on top of relational databases, we built a set of development tools, we're building teams and reports and forms and whatnot. And we use those to build families of applications that solve business problems like CRM and ERP and manufacturing automation, supply chain management and what have you. A few decades later, this has grown to be roughly a $500 billion software market, and everybody understands it. And 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 -- at 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 flat actuators and propulsion devices and flight management systems. And they want to be able to report every 30 days or 90 days or 365 days exactly what was the inventory of each item.

And 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, there's a pretty big parts inventory that you need to be able to report accurately. Or you might be able to -- you might want to report 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. And 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. So it's really quite important to get this right.

You might want to report on what your customer churn rates were, for example, at Verizon. And so this enterprise software is on a big market 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 $0.5 trillion business.

Now these applications are inherently descriptive in nature. They provide a company a perfect 20/20 hindsight into what happened 3 months ago, 6 months ago, a year ago. Now at C3 AI, we spent a decade at 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. And these with C3 AI, we make these existing enterprise applications predictive in nature.

Okay. So now instead of using a database or relationary 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. And 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.

So 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 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, a 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 2, 3, 4, 5 years out, this is a complete replacement market for everything that happened in enterprise application software in the last 3 decades. I do not believe that in 2 years or 3 years or 4 years, companies are going to be satisfied knowing what their customer churn was 90 days ago. They're going to demand to know which customers are going to leave if we don't take action.

Rather than know what our nondeployment rate was for tractors, aircraft, automobiles, they're going to want to have predictive maintenance applications that tell them which machines are going to 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, parts. Now like C3 AI provides out of the box 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 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 data scientists or Python to develop machine learning tools. And C3 AI provides the orchestration layer that enables customers to easily knit these solutions together in a cohesive solution.

And all of these applications, both open source and proprietary, are entirely compatible with the C3 AI platform. So we need to think of all of these things, Alteryx, TensorFlow, AWS, Google Cloud, Databricks, these look more to us like partners than the competitors. Let's take a look at -- this will be an example of the Shell AI platform, where on top of Azure, they put C3 AI. And because they have investments of value in things like Kubernetes or containerization and Databricks for virtualization and TensorFlow for machine learning libraries, MATLAB, TIBCO, Alteryx, what have you, we enable them to very easily incorporate these into the C3 AI platform market.

This is Shell AI, but virtually 100% of our customers, 100% are using some combination of these other products with the C3 AI platform. So it's really quite different than I think what is perceived to be.

Bottom line, all of these independent products appear to us -- that appear to some to be competitors are, in fact, partners. They're partners at Shell, at Koch Industries, at the United States Air Force, at virtually every C3 AI customer.

I want to address the issue of customer capture. Now our customer count has been growing quite substantially in recent years. And in the last year alone, it grew from 151 customers to 223 customers. But -- and if you look at our diversification by industry, it's really becoming increasingly diverse. Oil and gas, which is a pretty good market to be in today with oil 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. And this is a diversification of the industry, including oil and gas. This is bookings without oil and gas. And you can see that while our -- or year-over-year, our bookings in oil and gas grew 95%. Outside of oil and gas, it grew by 116%.

So 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, Energy, we are very much focused on penetrating these customers deeply. And if we look at this customer base that we have today, it might be 5% to 10% penetrated.

Now with many companies in the AI space or the SaaS software space, investors are really interested 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 fifth largest company in the world, one of the largest hydrocarbon producers in the world. 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 I understand the 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 LN Gas, okay. So an asset of Shell might be larger than 50% of the companies in the world.

And there on the road today, we have 65 assets in production this year. At our Users Group in March, Shell sit up on stage and they said they said they realized, in front of all of our customers at our User Group conference, and they realize $1 billion of economic benefit from their C3 investments last year. And they expect to realize $2 billion of economic benefit from our investors this year.

Now I ask you, how many customers are you aware of from SAP, Salesforce, Siebel Systems, Oracle Corporation, whatever it might be. All 5 companies. How many customers are you aware of who have stood up on stage and said that they are getting $1 billion, $2 billion, $3 billion, $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. This is predictive maintenance for aircraft, and the Air Force has roughly 5,000 aircraft. Here, we're doing AI-based predictive maintenance for B1 bomber, F-15, F-16, F-18, F-35 Joint Strike Fighter. And look at the speed, this project line shows the speed at which we bring these applications into production. So what is this all about? This is about integrating all of the data about missions, about weather, about fuel or kilometry from the devices on the aircraft maintenance systems to build predictive models that will predict what device is going to fail, 50 or 100 flight hours before it fails so that we can avoid the failure. And 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 of dollars in economic benefit annually. I believe we have 16 aircraft platforms live today, and we expect to have 22 platforms live by midyear. So deeply penetrating these accounts is what C3 is all about.

We continue to be focused, okay, on adding new customers. But at C3 AI, it's more important to look at the lifetime value of our customers than at how many new customers were sized. And yes, our customer base is growing, with new customers in the quarter, we include PwC, EY, the Conti Amadeus. 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 they became a customer a couple of years ago, made a decision in the quarter to standardize on C3 across all lines of business. This would include Flint Hills Resources, Georgia-Pacific, Molex, all Koch business units are standardizing on C3.

Similarly at Cargill, where we do predictive supply chain optimization and supply network risk from one of the largest food producers in the world. And the value of this is quite significant. We're helping feed the world at a time when much of the world is facing famine.

So this is what it means to -- for bookings at C3. So this is an example of a large integrated energy company in Europe. Their initial contract was for about EUR 300,000 in 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 at stage at our Users Group and said that they expect to realize $1 billion of economic benefit from C3 this year, $1 billion. This is a major U.S. government agency and how we have penetrated that. This is a large industrial manufacturing company, what have you.

So while we might start small, we might start with a trial -- a free trial, a $50,000 trial, a $500 product, $0.5 million trial or initial project for a couple of million dollars, our goal is to realize sometimes $1 billion, $2 billion, $3 billion, $4 billion in annual economic benefit for the customer. So as you can see, this is quite a different story from what you're used to seeing in enterprise application software where people are selling hundreds of things for $20,000 apiece. So our primary focus is penetrating existing customers. This is an example of the utility in Europe that today is generating billions of dollars of smart an annual benefit from smart grid analytics.

Now the growth strategy. 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. And then we have very meaningful horizontal market partnerships with hyperscalers, very significant relationship with Microsoft, significant and growing relationship with Google, HPE, NVIDIA, and others.

And so this is what -- this is how we're expanding all assets of the cube to establish a leadership position. And we've made a big investment in this over the years. I've talked about it. I've talked to you about this. And so how does this investment pay off with these partners, hyperscalers, vertical market partners, utility partners, oil and gas partners, 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. So this is becoming really quite significant.

We have a substantial and growing partner ecosystem. We have 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 $0.25 billion software business, growing at roughly 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. As I mentioned, the addressable market opportunity is land and expand. Our pipeline continues to expand. Our customer footprint is growing. Our balance sheet is rock solid. Okay. I have never been more optimistic about C3 AI than I am today.

We have exceeded revenue guidance for each of the 6 consecutive quarters that we have been a public company. And we are tracking exactly to the long-term plan that we laid out during the IPO road show, listen, play back the tape, it's still on the web, okay, and we're tracking exactly to what we said then. Our revenue growth rate was 38% in the year ending April, okay, up 17% -- up from 17% in the prior year.

Now in the past few years, as you know, okay, 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 not only at 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.

Until recently, the market rewarded rapid growth at any cost. This has clearly changed the market currently demanding sustainable growth combined with free cash flow, 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. And 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 8 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 passivism, 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 at any benefit to our shareholders.

Also, candidly, we did see some business that we expected to close in Q4 got moved out of the quarter. And we feel there is still too much lumpiness in our pipeline. Taking all of this into consideration, we believe it is prudent to guide -- to provide fiscal year '23 Q1 revenue guidance of $65 million to $67 million, and fiscal year '23 growth targets of 23% to 25%. By the way, there's a typo on the slide, that the vendor was not able to pick up. It's so -- it says '22 and in fact, this is a '23. So I apologize for that error.

When market conditions stabilize, we expect to target 35 -- 30% to 35% steady-state top line growth, while continuing to grow free cash flow to 20% non-GAAP targets. Now well, free cash flow, it's just a 20% target, so -- predict non-GAAP, okay.

Now I'm going to 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 $72.3 million or 38% growth year-over-year. 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 $0.25 billion 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 79% for the year, which is a 3-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.

And moving on to the deal bands. 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 to customers. And then in the higher band, 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 not rational for us not to invest in these customers with professional services. We generally see expansions in subscription as a result of successful proserve 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 '24 to FY '25 range.

We believe that we are structurally profitable and are able to maintain our growth -- are able to maintain our gross margin on a prospective basis. As we had indicated during the IPO, we have invested heavily in brand recognition, which we believe has been very successful. We believe that we have reached the point where, from here, we can sustain our brand with lower investments.

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 are 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 their proportional spend in this category. Overall, we're excited about our Q4 results and are looking forward for the upcoming fiscal year.

And with that, it's time to hear the questions. Operator?

(Operator Instructions) Our first question is from Arvind Ramnani with Piper Sandler.

Just really want to ask about guidance. On the last earnings call, although you didn't provide formal guidance, you had talked about being comfortable with consensus, which was about 33% growth. And then when I look at this year's number, kind of growth is closer to like mid-20%. If you can just kind of talk about the 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, Arvind, it's Tom. Thanks for the question. I haven't seen a lot of enthusiasm and sheer, okay, in any market activity in the last 2 months since our last call. I would say that what we're seeing from the market is really quite dire. If you look at -- candidly, so I think that given everything that is going on in the market, okay, it seemed prudent to us to set market expectations conservatively. And that's what we did.

Perfect. That's great. And just in terms of kind of bookings growth 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 any particular industries or clients that you're seeing strong growth from in terms of bookings.

Yes. Well, if we look at -- let's see where is 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. But it's becoming efficiently diversified.

And 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%. And outside of oil and gas, I think it was 115%. So diversification strategy is playing out well.

Our next question comes from Patrick Walravens with JMP Securities.

Great. Tom, can we start by hearing a little bit more about the deals that slipped in Q4?

Let's see. I have to look at the pipeline. I don't really have that one on my desk, Pat. I mean I would say that we did see a number of deals move out of Q4 into Q1 and Q2. They had -- they didn't disappear and they weren't lost. They just kind of moved and they love to -- there's still lumpiness in the business. We did close how many deals in the course of the quarter?

27.

27. So the number of deals is quite high, but we had -- honestly, we had a number of deals that we expect to close in the quarter but didn't. So 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 and for the year.

Yes. And can I ask how -- so how is May then, so far?

How is what?

How was the last month then, the beginning of this quarter?

I'm prepared to comment on the business as of the as of the end of the quarter of, Pat. And we've given our guidance for what we think is going to happen in Q1. And so far, I don't think we've -- I'm really quite confident that we've not fallen short of our guidance. I think we hit it -- every quarter we've been a public company, we've exceeded the guidance. Yes.

Yes. Okay. And so it seems like Bakers Hughes -- I mean last quarter, you called out Baker Hughes because it contributed, I forget what the percentage was, but a really big percentage of the bookings. So was Baker Hughes 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, and oil and gas last year grew by 95%, which is pretty strong in bookings. So I would not describe it as soft. Did some oil and gas deals move out of the quarter? Yes.

Yes. Okay. And then...

Business is quite healthy.

Okay. Great. And then Juho, one for you, which is so can you repeat the -- how much of the -- you have a $100 million buyback plan, right? And I think you told us how much you had bought back and I missed it.

Yes, it was $15 million or 720,000 shares.

720,000 shares. Okay. Great. Sorry, last one, one more for you, Juho. What will free cash flow for this coming year if the operating loss is minus 76% to minus 86%, how should we think about free cash flow?

Well, yes, 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 going to reach the operating profit goals that I outlined, you're going to start seeing a more sustained operating or free cash flow positive. But as we march towards that goal, there's going to be lumpiness. There's going to be periods where we're going to be closer to positivity and then periods where we're going to be a little bit more free cash flow spend.

Okay. Just so we don't have unpleasant surprises in Q1. So just for Q1, you guided to an operating loss of negative 23 to 28. Should we expect cash flow to be in that range? Worse? Better? How should we think about it?

Well, I think -- yes, that's a good question, Pat. I think more broadly speaking, again, there's going to be -- we're going to have some activities. I think one of the things that you're aware of is that we're having the build-out on the new lease. And 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.

We had a tenant improvements in the office building that we're moving into.

Yes.

Our next question comes from Brad Sills with Bank of America.

This is Adam on for Brad. So for 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 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% to 15% range. Obviously, this quarter, we ended at 22%. Last quarter, I think it was 18%. I think you should expect somewhere to be in the mid-teens, but there's still going to be some activities in the quarter that may change that. But I think that's a fair assumption at this point.

Okay. Super helpful. And then a quick one for Tom. You guys kind of called out in the press release the expansion of One Medical. Can you just talk about what the lining point looked like and then how that ultimately evolves into becoming an Ex Machina customer?

Ex Machina. I believe that One Medical began as an Ex Machina customer and has expanded as an Ex Machina customer. So 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.

The -- regarding the professional services question, I want to say, I mean, think about kind of what's going on and what we do where we're investing -- 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 then 60 -- there's $100 million in business there. So for right now, as we establish market presence and we had established successful customers, it's kind of nonrational 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, when we can take a company from EUR 300,000 to EUR 120 million and do that kind of over and over again, to not invest in professional services in the few years to get them live, I would suggest, I mean, it's not rational for us not to do that. And in the short term, it's pushed up our professional services revenue a little higher than we would like to see. But we're achieving the objective of market penetration.

Our next question comes from Michael Turits with KeyBanc.

This is Eric Heath on for Michael. On the couple of deals you called out is pushing out of the quarter. I was curious if there was any commonalities across those deals either by geography or vertical.

I would say, Eric, across verticals and across geographies and somebody needs to get budget approval or to need to get something signed by some senior executive and it didn't get signed in time or there is some committee that needed to go to where the committee didn't get scheduled. And some of these are in Europe, it's kind of Europe, the deals on Euro time. And so it's -- many of these are large organizations, where they're very bureaucratic in their processes and maybe need to get Board approval or CEO approval or CFO approval or whatever happened and just -- they're operating on their time line and not ours. That's all.

But I would say it's pretty much across industries and across geographies. It was not -- we didn't see any specific industry fall apart. And I would say given kind of the market dynamics of what's going on with supply chain disruption, I mean, probably one of our biggest products is supply network risk and stochastic optimization of the supply chain. This is becoming really mission-critical and associated with all of our applications where, as you can see from our presentations, our discussions with the customers is how much money are they saving in a year.

So as people start to tighten their belts in what might be an economy that's turning down, we provide tools that enable them to tighten their belts very cost effectively.

That's helpful. And then just I think you had some nice drawdown of the $500 million authorization in the DoD this quarter. So 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. And we're -- we had continued penetration in the Air Force with RSO. That is now accelerating at a -- I think that offers a big opportunity to accelerate. We have 2 or 3 other agencies in the defense and intelligence communities that have made, okay, and are processing large C3 AI procurements. So 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. So we're very optimistic about the U.S. Defense, Intelligence and Civilian businesses.

Our next question comes from Bob Huang with Morgan Stanley.

This is Bob sitting in for Sanjit today. So 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 are seasonally high, but it was probably a little 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.

Yes. Thanks, Bob, for the question. So I think some of the things that ties to what I was mentioning earlier to Pat on the cash flow items, so 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. So at this point in our company, we're going to 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. So I don't think it's a metric that you need to focus on, particularly intensely.

Okay. That's very helpful. My next question, just -- you obviously had some -- 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 want to keep a closer eye on going forward?

Energy looks strong. Utilities look strong. Oil and gas looks strong. Chemicals look strong. Manufacturing looks strong. We really haven't penetrated telco yet. I think there are big opportunities there. Financial services, I think there are big opportunities there. We're starting now to penetrate consulting companies, EY, PwC and others. I think there's going to be a big opportunity there. We're providing them tools to accelerate their -- what they do.

So yes, I think it's -- the question is, I mean, ultimately, this is just like CRM or like ERP. All industries adopt, it's just which industries adopt at which rates. And interestingly enough, we're seeing a lot of interest in agribusiness, which is a huge supply chain problem globally as it relates to agribusiness, as the world faces kind of potential famine associated with wheat and rice production. So what we're doing there, with some work with Cargill and others that's really interesting and really important.

In general, we don't really see right now a lot of softness out there, but we do read the newspapers, shouldn't we, what you guys write? And we haven't seen a lot of the newspapers. And while we don't see it, our business looks quite good. I think as long as we didn't read the newspapers, or turn off the TV, everything would be fine.

Our next question comes from Pinjalim Bora with JPMorgan.

Sorry, I was -- 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 have done or the amount of sales capacity that you have currently given the tight labor market?

Sales capacity has grown pretty considerably. Really, we've been -- so it's not a sales capacity issue. It's just, I mean, I'm looking at these transactions that we expected to close, 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, a pharmaceutical company in Europe, a 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 division of defense, large food provider, local, a county with roughly 1 million people in it, a large credit card provider, U.S. Intelligence Agency. So insurance -- I just read right down the list, okay? Of deals that we're 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.

So it varies. It's across industries, across geographies, and it's just -- it's not that their business has gone south that they're going under, it's just that they did -- they are processed in time.

Understood. I guess one thing that people trying to understand...

That was not in memory. I was reading right from the list.

Yes. Understood. Well, the follow-up to the -- my follow-up would be that AI obviously -- or C3 obviously saves a lot of money when deployed. You have really big economic benefits, right, when deployed. However, it seems like it's a factor of the large initial outlay, which is kind of creating these problems, right? Otherwise, people should probably adopt AI during a slower economic environment, wouldn't you say?

Well, I'm not sure. I mean the initial outlay sometimes is $50,000, sometimes is $10,000. The initial outlay at a $300 billion oil company was $300,000, which were -- might seem like a lot but it's not a lot for a $300 billion company. So I'm not sure the initial outlays -- that I accept that. As you saw from the slides that I showed you, frequently, the initial outlay is $50,000 or $300,000 and then it grows every time.

So the average is...

Is 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.

There are no further questions waiting at the 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.