Q3 2024 C3.ai Inc Earnings Call

Participants

Hitesh Lath; Chief Accounting Officer; C3.ai, Inc.

Timothy Kelly Horan; Analyst; Oppenheimer & Co. Inc.

Sanjit Singh; Analyst; Morgan Stanley & Co. LLC

Patrick D. Walravens; Analyst; JMP Securities LLC

William Kingsley Crane; Analyst; Canaccord Genuity Corp.

Presentation

Operator

Good day and thank you for standing by, and welcome to the C. three AIS. Third Quarter Fiscal Year 2024 conference call. At this time, all participants are in a listen only mode. After the speakers' presentation, there will be a question and answer session to ask a question. During the session, you will need to press star one one on your telephone. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Miss Berry. Please go ahead.

Good afternoon, and welcome to C. three AI.'s Earnings Call for the Third Quarter of Fiscal Year 2024, which ended on January 20th, January 31st, 2020. For my name is Amit. Very and I lead Investor Relations at C3 AI. With me on the call today is Tom Siebel, Chairman and Chief Executive Officer. You hope our Qinnan Chief Financial Officer and at a slot Chief Accounting Officer. After the market closed today, we issued a press release with details regarding our third quarter results as well as a supplemental to our results both of which can be accessed through the Investor Relations section of our website at ir dot c. three data. 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 related 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 material materially from expectations. For a further discussion of material risks and other important factors that could affect our actual results. Please refer to our filings with the SEC. All figures will be discussed on a non-GAAP basis unless otherwise noted.
Also during 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, our time in our prepared remarks in response to your questions, we may discuss metrics that are incremental to our usual presentation to give greater insight 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.
And with that, let me turn the call over to Tom.

Thank you and miss. Good afternoon, everyone, and thank you for joining our call today. C. three a., I had a great third quarter. Total revenue of $78.4 million grew 18% year over year, exceeding the high end of our guidance range. The total number of customer engagements was 445, an increase of 80% compared to 247 a year ago. Subscription subscription revenue was $70.4 million, constituted 90% of total revenue and increasing 23% from a year ago. Non-gaap gross profit was $54.7 million, representing a 70% gross margin. Our GAAP operating loss was $82.5 million. Our non-GAAP operating loss was $25.8 million better than our guidance for a loss of 40 to 46 million. Our non-GAAP Our non-GAAP net loss per share was $0.13. We ended the quarter with 723.3 million in cash, cash equivalents and investments. All of these numbers exceeded our guidance and exceeded analysts' consensus. This is the 13th consecutive quarter as a public company and which we have met or exceeded our revenue guidance range. None of this should have come as a surprise. The enterprise AI market is on fire. We have been predicting for some years that the market for enterprise AI would be quite large. Those predictions were subject to much speculation in the analyst community and media as of February 2024. I believe it's broadly Resolved that the enterprise and market opportunity is substantially larger than anyone predicted, constituting a secular change in the composition and growth rate. Enterprise Software writ large cloud infrastructure is scaling rapidly in video grew 265% year over year in video as data center GPU sales grew by 409% year over year. Now some believe that this capacity is built is being built TSLLM.s to write Christmas card from style to Charles Dickens, okay. And Wright college application SHDSL, but that's simply not the case, this capacity is being built to run enterprise AI applications, stochastic optimization of the supply chain, supply, network risk, predictive maintenance demand, forecasting, fraud detection, perception optimization, customer engagement for predictive medicine, precision medicine and government services. And that is what we do at C. three AI. So as we power into 2024 and 2025, the world is very much coming our way. C. three a. has been preparing for this enterprise AI market explosion for 15 years. We started in 2009 at the infancy of AWS. This is both for Zohr and before Google Cloud even existed.
Yes.
We carefully designed, developed and tested a reference AI software platform architecture now known as the C. three a. platform. We then use that platform to design, develop and bring to market over 45 production enterprise AI applications that address the value chains of manufacturing, financial services, agribusiness, chemicals, lumber paper products, utilities, oil and gas, state and local governments, defense and intelligence, the market for enterprise and the market interest in enterprise AI is stacked virtually all commercial, military and government organizations are focused today on leveraging AI to improve their operations, optimize their processes and transform their businesses. Our qualified opportunity pipeline has increased by 73% from a year ago and this is led by C3 generative AI opportunities. Our go to market with partners is driving strong pilot additions and it's still in the earliest innings. In the third quarter. We close 62% more bookings with our partner network than we did in Q2, 337% more bookings than a year ago. Bottom line, the market demand for enterprise AI products is overwhelming customers in the commercial sector. In Q3, we signed new agreements with Boston Scientific, particularly on Booz Allen, South Wire Carpenter Technology, Florida Crystals, Santa Ana Ag Service to Rio Guatemala, ABI, the T-Mobile Bloom Energy Ball Corporation, DLA Piper Carlisle Companies and wholesome, among others, wholesome, our European leader in sustainable building solutions embarked upon a production pilot with C. three AI. beginning in May 2023 to configure and deploy the C. three AI. reliability suite. Following a successful six month pilot hole, some entered into a four year subscription agreement with C3 Ai to scale the reliability application across its 100 in excess of 100 Cementbouw Paulson's predictive maintenance program monitors a large number of assets and will generate significant yearly economic value in reduced maintenance costs and production increases. Wholesale is also implementing C3 generative AI. to enrich the reliability application and to assist with complex machinery troubleshooting. Another example DLA, Piper of global law firm pioneering technology innovation in the legal sector, worked for C. three i. to create a first time generated a I. application to streamline the analysis of complex legal agreements in just three months. Dla Piper applied CJ generates a I hope to reduce the training time it takes to create over 200 points due diligence analyses of limited partner agreements, and it reduced the effort by 80% as a result of this application. Dla Piper is realizing new operational efficiencies and freeing up their attorneys time to focus on delivering increased value to their clients. State and local government had a huge quarter, generating 29% of our bookings Lighthouse agreements with San Mateo County, Daly City and Riverside County, California are spearheading growing awareness for our state local governments suite of applications, and we're now closing deals nationally. We see a huge potential to expand our footprint to the county cities and municipalities across the United States, San Mateo County Sheriff's Office and the Daly City Police Department. Both sides multi agency expansion contracts for the C. two A. law enforcement application as a countywide crime and investigation platform to combat organized retail vehicle and cargo theft. This contract, it involves a combined 15 local police departments and 16 agencies deploying the application in core and coordination, including Burlingame, Daly City, the city of San Mateo, San Bruno, others in Redwood City, South San Francisco, and Menlo Park Foster City Belmont Pacific up East, Palo Alto, Calmar, Broadmoor, Brisbane and others. These deployments promise to significantly decreased the investigated time lines to solve crimes and empower multi agency collaboration to help prevent crime. These are these engagements engagements are funded through the organized retail threat scrap from the California border state, the Board of state and community corrections and by the way, have all the submissions to the to this Board. San Mateo County submission ranked number one.
Okay.
As the primary priority, as is the best submission here in the States.
Okay. With C. three i. law enforcement being the top investment in their initiatives to combat retail theft in the state of California. We also executed an agreement actually multiple agreements, okay, with San Mateo County to deploy C. three AI. property appraisal, CGA loss and fall enforcement and C. three AI. generative and C3 generative AI applications. The assessor and county clerks recorders and elections office license fees, rehab, residential property appraisal and C. three AI. commercial property appraisal to kind of monetize the appraisal of over 230,000 parcels each year, a constituting more than 300 billion in assessed property values. And to do this more accurately more equitably, more expeditiously and more defensively.
Our U.S. federal business continues to show significant strength third quarter revenue was up over 100% year-over-year and bookings were up 85%. We signed new and expansion agreements with the Missile Defense Agency, the Department of Defense the United States Air Force and the U.S. intelligence community, including seven new generative AI. agreements at the Missile Defense Agency, the United States, Air Force, J. Rob and the U.S. Marine Corps. We have a really substantial growth opportunity in federal general, laying the groundwork to see that we're getting strong traction with partners in this federal space, not the least of which is AWS, how we've deployed our Federal Solutions on the AWS marketplace for the US intelligence community in June of last year. And we're basically on speed, dial collaborating with federal with AWS federal executives every day in the defense and intelligence communities. Additionally, and importantly, we entered into an enhanced partnership agreement with paradigm that is a high end professional services, an organization in the federal sector. And we did this to increase our capacity for deploying appropriately cleared data scientists and application engineers into our classified government installations. We've aligned with Paradigm and our commitment to support the defense and intelligence communities in their critical missions related to national security. Under the new agreement, paradigm will significantly grow its number of dedicated CCS staff to accelerate joint selling and to accelerate the delivery of these secure classified and powerful AI applications predicting Brian predictive insights into these federal agencies. In addition, paradigm would jointly market the C3 generative AI. for defense application and the C. three AI. law enforcement applications.
I want to highlight the continued diversification in our E. in our go-to-market efforts. Our business continues to diversify across the industries. In the last quarter of Q3, our bookings distribution by industry was 29%, state and local government, 25% federal defense and aerospace, 16%, manufacturing 11%, agribusiness, 8%, chemical, 7%, professional services, 2%, energy and service utilities, 1%, food processing and consumer packaged goods and 1% oil and gas Now let's take a minute, and this is important. So please pay attention and look at the evolution of our go-to-market model. And I want to particularly talk about the transition to consumption-based pricing on your call that six quarters ago, we changed our go-to-market model from a leading with a subscription-based pricing model to leading with a consumption-based pricing model. The general idea being that rather than people licensing 10, 20, 30, 40, $50 million upfront, they would simply do a project a pilot project for, say, at 5 million for six months. And we'll bring that predictive maintenance application, the supply chain optimization, the demand forecasting application, whatever it may be into full production in six months. And then the customer will have a half a million of which insignificant at if the customer likes it, they could keep it and they pay depending upon the volumes you're generally, you know, 40 to $0.55 per VCPUR. to run the application, bring it live, if you like it keep it. That was the idea. And this clearly and substantially lower the price barrier for content for companies to engage with us. And we've seen this now in the mid size, the number of deals that we close each quarter, the size of the transaction that we're doing, it's been very effective. So this model has been and continues to be very successfully driving engagement and our contract volume has grown as we expected. At that time, we provided expectations of VCP consumption ramps, pricing and pilot conversion rates. And now we've compared this to the empirical data that we've realized over the past four quarters and it turns out those initial assumptions have been proved to be quite high. Our estimates on ZPCVCP. year usage and how that ramps those aggressively, how that ramp, say over a four or five, six, seven, eight quarters, they're pretty darn accurate.
It.
I would say that you think plus or minus 10% in, you know, it's about right out.
Okay.
We assumed a pilot conversion rate of 70%, and what we're seeing that appears to be.
All right, okay. We're also pleased to share that the pricing on the converting part of the converted pilots is pretty much in line with our expectations now. And when we began the transition, we assume that virtually almost all pilots actually would convert to month-to-month pay-as-you-go consumption based pricing, counterintuitively, it hasn't quite worked out that way. And the empirical data show that the majority of our customers are choosing to sign multiyear subscription contracts rather than after the trial, they have the option advantage using decide multiyear subscription contracts rather than month to month pay as you go. And so why are they doing that? After pilot completion, many customers are electing to deploy multiple applications across multiple business units, and they're electing for a multiyear subscription, committed subscription pricing model as it offers them a more predictable cost model at large scale.
Now note also, it's not quite this simple for those that you're working on models because that subscription agreement a hospital involves the consumption rate runtime component. So there's not going to be easy to model people for those who are working on your spreadsheet.
Okay. Now the good news is that our customers are making significant commitments to C. three AI. and our multiyear subscription agreements are a positive indicator of the depth of their commitment. And also our data shows that over the chairman of the contract, the revenue from new subscription agreements is generally equal to the revenue from our consumption agreements. So whatever the customer chooses is find us because it's revenue neutral over, say, 10 to 12 quarters bottom line, our go-to market transition is working as evident from the growth of our opportunity pipeline, the increase in our customer engagements and increased revenue.
Now let's take a minute and talk about generative they are because this is a this is a very significant market development. The opportunity ahead of us in generative. They are enormous step C. three AI. has been at the vanguard of enterprise AI innovation. Now for 15 years, we spent 15 years building ship enterprise AI applications for manufacturing, supply chain demand, change, finance, defense intelligence, smart grid, oil and gas et cetera. We in all fairness, we largely established the enterprise category. Now with the advent of general AI, I mean, this is fundamentally changing the nature of the market. It's changing the nature of the human computer interface is unlocking new use cases and it's breaking and it's creating kind of breakthrough opportunities for nonobvious applications in new industries and enterprises that we might that we would not have expected. And we're just in the earliest days that this Gartner predicts Gartner Group predicts that by 2026, over 80% of enterprise will be using generative AI, including of the deployment of January MAI., enabling applications in their production environments. This is up from basically zero in 2022 as per Gartner organizations. This is a quote that do not consistently manage ARAI. risks are exponentially inclined to experience adverse outcome such as security failures, financial and reputational Ross loss and social Hong Kong. We are leveraging our first-to-market advantage in a scalable, trusted enterprise AI to bring secure Germany, stick hallucination free traceable domain-specific, January of AI. solutions and generative at augmented applications to market. And we're seeing a groundswell of interest in all of our generative AI offerings out there and our remarkable uptake of the C. three generative AI Suite, our generative customer activity has ramped sharply since we introduced this product to market four quarters ago. We're now applying a generative AINO. kind of areas where we wouldn't have expected the operator assistance and a major manufacturing facility customer assistance at a global financial services company and field technical support at a major multinational manufacturing group. Dla Piper is using January that has significantly reduced the labor associated with limited partner agreement due diligence. Another leading law firm is using the corpus of S ones that are contained in SEC.gov to train a large language model to reduce the attorney labor.
Okay. And generating first draft of S ones for IPO candidates, I mean, imagine you train a large large learning model on the corpus of S ones and SEC.gov. And then you want to come up with their first draft of your ask one if and when the IPO market opens again, okay. You put in the name address of the answers. The key risk factors hit the carriage return episode facto. The first draft of the S-1 is there and we've saved God knows how many personal weeks of legal associates it isn't, where now they can just add it and get it done. So it's really this is this is pretty neat Baker Hughes is using C3 generative AI on top of Workday and ServiceNow to provide its global employees, brought an immediate answers to all employees.
Questions about employee questions, policies, benefits, compensation, what have you, Riverside County in California is using CT regenerative AI to assist their staff in answering questions about Citizens' questions about taxation, zoning, building codes, et cetera. We continue to be really impressed by the broad range of applications to which the generative AI technologies applicable income.
In Q3, we closed 17 generative AI application pilots across a broad range of industries, including federal defense, aerospace, ag, forestry, food processing, manufacturing, stable government chemicals, life science and others. And this generator that pilot spans Europe on Latin America, North America, you there are no bounds to this, we continue to drive innovation in general to the market with a highly differentiated should see three generative AIX. solution. Our newest innovations include Omni modal data support. You've heard about multimodal multimodal doesn't kind of multimodal includes text and images. That doesn't get you very far unit and includes unit your enterprise data, ERPCRMOSIPI. data, telemetry images, tech photos, a voice. So you're in order for this for this data, the hot, okay, it needs to heal a multimodal. It doesn't get you anywhere you need Omni model data support, which is what we support in the C. three i. product. Today, we have advanced parsing and embedding capability to increase reasoning on tables and images within D.R. Again, we have the planning and execution of complex multistep workflows, which support multilingual support and the automatic invocation of advanced map tooling.
Okay. We do this in a manner that is virtually hallucination free.
Okay. Anatel, I'm agnostic. So at some point you would our solution here is really quite unique and it's getting a lot of traction and we are installed today in some of the most secure installations on the planet Earth earlier this year, I will actually ask than we announced in last quarter's conference call, we made a well-considered decision to accelerate our investments in January date, and I have to seize market share in this large and rapidly growing market opportunities as a result of that investment.
Last quarter, our way our web page views are up 57% year over year. In Q3, our organic search traffic is up 68%, and our unique visitors to our website are up an eye-popping 230%. So this decision is already accelerating our business already accelerating our price, our product innovation, and it's driving definitely broader market awareness of what we do in enterprise AI and in Generative Design. That being said, we continue to expect that we will operate a positive free cash flow business.
Okay. In Q4 of in the next quarter. Now, while we're not giving fiscal year 25 guidance yet, we will continue to expect positive free cash. We continue to expect positive free cash flow for the full year of fiscal year 21. Todd talk a minute about our international users group conference. C3 transformed will be holding our fifth annual international users group conference. Ctu transform and brokered on next week, March fifth through seventh, over 500 customers and partners are registered to attend, including leaders from almost every industry sector, general sessions on March fifth and six will be substance packed, including C3, AI, product roadmaps, C3 AI, customer success stories, best practices in enterprise, AI from C3 as customers and partners via innovation in defense and intelligence and discussions from experts about the past and the future of generative. They are and I'm very pleased to announce that the C. three transform general sessions will be simulcast to qualified investors and analysts. And those of you are interested in can register online beginning this Friday and then to in real time to participate in any of us to shut those general sessions that you would like. And I think you'll find them. These are not cheesy sales pitches folks. This is this is this is pretty substantive stuff. And for those of you who are either interested in C3 or interested AI. in general, I think you'll find it out. I mean, we hope you'll join us and you're welcome to get in conclusion business has good prospects. Look, bright and C3 has returned to accelerating growth, talk about gates. So given current market conditions, we are increasing revenue guidance for Q4.
Okay. And for fiscal year. This fiscal year 2024 were for Q4. We're anticipating revenue in the range of 82 to $86 million. And for the year, we're anticipating revenue in the range of 306 to 310 million. Our non-GAAP loss from operations is expected to be in the range of 43.5 million to 51.5 million for the quarter. And our loss from a non-GAAP loss from operations for the year is expected to be in the range of 115 million to 123 million.
Now let me turn the call over to my colleagues, Yuko, your apartment and the Chief Financial Officer, and Hitesh lab, the Chief Accounting Officer for some additional detail.

Thank you, Tom. And I will now provide a recap of our Q3 financial results and some additional color on pilot activity. Then I'll discuss factors that would drive our financials in Q4 and in FY 25. All figures are non-GAAP unless otherwise noted.
Total revenue for the third quarter increased 17.6% year over year to $78.4 million. Subscription revenue increased 23.4% year over year to $70.4 million and represented 89.8% of total revenue professional services revenue was 88.0 million and represented 10.2% of total revenue. Gross profit for the third quarter was $54.7 million and gross margin was 69.7%. As a reminder, we continue to expect short term pressure on our gross margins due to a higher mix of pilots, which carry a greater cost of revenue during the pilot phase of the customer lifecycle. Also, as we discussed last quarter, we expect short term pressure on our operating margin due to the investments we're making in generative AI and upgrading customers to our platform.
Version 8.3 operating loss for the quarter was negative 25.8 million compared to our guidance range of negative 40 million to negative 46 million. The improvement in operating loss versus guidance was driven by our team's ongoing focus on disciplined expense management as well as the timing of additional investments we're making to capture market share. At the end of Q3, our accounts receivable balance was 173.5 million, including unbilled receivables of 102.6 million. Total allowance for bad debt remains low at 400,000, and we have no concerns regarding collections. The general health of our accounts receivable remains strong six quarters ago, we announced the transition from subscription-based pricing to consumption-based pricing standard in the industry. We anticipated and announced that this transition would have a short to medium term negative effect on revenue growth in RPO as the average sales price was significantly reduced and the contract often lack the time certain multi-period commitments. As the transition progresses, we expect it to return to revenue growth of customer engagements accelerate and customers expand their consumption, reflecting our turns out the transition to a more consumption-based contracts.
We reported third quarter GAAP RPO of 286.9 million, which is down 28.8% from last year and current GAAP RPO of $172 million, which is down 2.4% from last year. Free cash flow for the quarter was negative 45.1 million. We continue to be very well capitalized and closed the quarter with $723.3 million in cash, cash equivalents and marketable securities.
Now I'll provide some additional metrics for the third quarter. During the quarter, we started 29 pilots, a 71% increase from last year and down 19.4% from last quarter due to timing of the sales activity, 10 industries were represented in our pilot starts. At quarter end, we had cumulatively signed 138 pilots, of which 132 are still active. This means they're still in their original three to six month term extended for some duration converted to consumption or a license contract or currently being negotiated for a production license. Our customer engagement count for the quarter was 445, an 80.2% increase from 247 a year ago.
As a last item on our call today, I wanted to inform you that after three wonderful years at C. three I. I will be stepping down as the Company's CFO and assuming a role as VP of Finance, I have been at C. three AI. for three amazing years and two of its CFO. I'm grateful to Tom and the Board of Directors for the opportunity. It has been a privilege to work beside Tom and the entire executive team in this role. As you all are aware, C. three AI. is a unique hyper performance technology company, 100% in the office incredibly hard working fast-paced, you have to beyond 150% all the time. And for me, personally, I need to take a break and step aside for a bit and spent more time with my family. I am pleased to inform you that my colleague Hitesh left is assuming the role as CFO. I hired Hitesh about three months ago as our Chief Accounting Officer. Hitesh comes to us from Ernst & Young, where he was a partner for over eight years and brings a total experience of 24 years spent serving large multinational technology clients. I've known Hitesh for over a decade. And in fact, when I was at Ernst & Young, I worked for him at some of the engagements from day one. It has jumped right in and was heavily involved in preparing the financials for this quarter. And I'm very excited to have the finance team to test his capable hands and expect him to continue the progress we have made and take the team to new heights. I will remain as C. three AI. employee advising Hitesh and Tom and assisting the team as necessary to make sure our operations are smooth on our financial reports continue to be pristine.
Hitesh, would you like to say something?

Thank you, Yuval.

Hitesh Lath

I have been here at CTAI. for about three months, and I'm very excited to take on this role. These are great times for AI and for PTA, and I look forward to working with Tom and rest of the executive team and be a part of the growth story.
With that, I'd like to hand it over to the operator for Q&A.

Operator

Thank you.

Question and Answer Session

Operator

As a reminder to ask a question, you will need to press star one one on your telephone. Please stand by while we compile the Q&A roster. Sir, and our first question comes from Timothy Horan of Oppenheimer from.

Timothy Kelly Horan

Thanks, guys.

On could you give us a little bit more metrics on the productivity improvements your customers are saying or success stories and where is generative AI, adding the most value to AI. as you see it now our Tennessee.
Hi, it's Tom. Thanks for the question. I would yield to the extent you have time. You are one a year of associates dialed in next week to our users group conference because your customers are going to say with the product gave increases, they're getting a car. They shall I stood up and said they're getting a $2 billion in economic benefit to the United States Air Force who will be presenting against this at this has stood up and said that they're getting a 25% increase in aircraft availability, increasing aircraft availability from our predictive maintenance applications deployed as the standard of the Air Force. So I mean, that's 25% increase in capability. United States Air Force has a lot of capability. So on those are two examples of generative. They I can make this. There's just no telling where this goes on, whether it's sitting on top of Workday sitting on top of ServiceNow sitting on top of SAP and sitting on top of Salesforce driving contracts for lawyers on the work we're doing at DLA Piper. I mean, on one of the applications you're going to see like, you know, for those of you that tuned in to our user conference to talk about our cell application. This is that this is the application, which was one of the large die applications on earth. Dysport reported the United States Air Force. And now we're putting in this this is we've used the data from 22 weapons systems into a unified Federated image, F-15, F-16, F-18, F-35, KC. one 35 et cetera. And including the telemetry from many of these devices. And B-1 bomber has 42,000 sensors admitting telemetry at something like 800 cycles. There's a lot of data I think it's order of 100 terabytes of data. And like any application of this nature, it has a highly technical interface when we put generally have an eye on top of it. It has a mosaic browser user interface in the boat Mosaic browser. You guys know that is the basically the Google browser, okay, get Google copied it again at Mosaic browser came out of University of Illinois, I think in 1993. And they so now you simply anybody in their floors with the proper authority. Can ask any question about any weapons system or any weapons systems and immediately get the answer. Whatever I read at UPS levels were up 35 quadrants in Central Europe. What's my cost of running the B. one B. program and each of the last five years, I guess what are the biggest parts issues associated with the F-35 project, whatever it may be. So it really is though, as it relates to the as we deploy these enterprise AI applications in mass across organizations, it runs a user interface. It makes the change management project process, much simpler. So these are examples in both those areas. And, you know, I don't know how big how big this generative I think has, but it bigger than a breadbox. I can tell you that.
Thank you.

Operator

Thank you. One moment for our next question.
And our next question comes from Sanjit Singh of Morgan Stanley.

Sanjit Singh

Thank you for taking the questions. And sorry, you hope to see you go and best of luck for spending time with the family.
Tom?
Tom, I wanted to ask a little bit about the wants in generation. It seems like that's an AI. access pattern that's getting really, really popular across enterprises in costs and AI companies. And so there's a lot of companies sort of pursuing this opportunity and what I wanted to hear a little bit about how on C3 is sort of differentiate in terms on providing this capability to enterprises that sort of differentiates RAD from C3 versus some of the other plays at a better time to make this a reality for customers essentially covered our enterprise AI in general or specifically generative Our agenda today, I'm going to go into the retrieval augmented generation LADD seeing seems like what do you think this has Catching Fire with enterprises? And just wanted to see like how CCE is on allowing customers to pursue Iraqi case, okay, we'll RAG usually lower, very choose a technology that allows the answer to be traceable.
Okay, that allows you to do so when you asked the question, it tells you what the answer comes from. And most large language models will not do that fit the C3 generative by combining 15 years' worth of platform architecture with the large language model we're able to solve the generative value equation in a in a highly differentiated manner.
Okay. The C3, Ai generative AI, where we support generate all the answers, our deterministic, not not random. I mean, it's every day we ask the same question. You get the same answer, go on to Bard or go into jet GBT. It doesn't work that way every time you ask the same. If two people ask the same question, you get different answers or gap.
Secondly, everything that we do is traceable.
Okay. And would this is where we use or a rag eight are retrievable augmented generation technology. So we know exactly where the answer came from. Again, most large large mangoes robots do that.
Okay, because we have the temperature churn down to zero?
Okay.

We don't know.

We don't elucidate if it doesn't know the answer. It doesn't tell you where the answer is most of these other solutions are Una Modal, you know that.
Okay, big data input, anything you want as long as you put intact, that's not usual. Now they're thinking about multimodal multimodal or he ask Andrew Ang means tax plus images. That's not that usual either. If we're going to do generative AI, for example, on this airport application, it needs to be Omni mode, text images, graphics enterprise data, telemetry, voice signals, what have you and so were Omnia modal. We them well, almost all of these other LLM. solutions, whether they come from OpenEye R or Entropic or or Google or wherever they might be?
They are on specific. Our answer is well aware, I'm agnostic. So you can change out the large language battle every week as these guys out innovate each other one of the big hydrocarbons associated with large language models is data exfiltration. This is what's visible what is stopping these applications from being installed everywhere see Samsung for details. There's a lot of reinsurers, particularly coming out of university, Carnegie Mellon, okay. That is showing the cyber attack vectors that are opened by these large language models. And then you know the story about Samsung with the kind of massive data exfiltration of their intellectual property onto the public Internet.
Okay? Because the way that our system is structured we have the LLM. has no access to the data. Therefore, it can't actual trade and it's not a vector for cyber.
Okay.
It also because it doesn't have an access to the data it, it doesn't have the opportunity to elucidate.
Okay. Another reason why these LLM.s are not being installed has to do with IP liability. The IP. liability associated with these large language models that are traded on the public Internet are unbounded.
Okay. Unbounded liabilities, a problem for Bank of America, unbounded liabilities, a problem at cargo in problem at any responsible organization or even a Morgan Stanley.
Okay. And the on the ITO, the way that the way that our system works only your data are available to the large language model. So there is no IP liability problem.
And finally, our solutions, our LLP., as you always are you mentioned LLP out, I am agnostic. So our solutions are highly differentiated from the other solutions that are out there. And for any one of those reasons I mentioned that system does not get installed at Goldman Sachs does not get involved at Morgan Stanley Coke Industries, United States Air Force or the CA that doctors have hot and ours does that. That's the difference?
That's a super comprehensive answer, Tom, and I'm really looking forward to a flushing some of those sessions that I see three transform unless we and there is I'll mention specifically on that with with the Mayfield, Kristian, you know games launched in the US of outgoing and for Enron, current from Forrester Research out exactly that. And at that nine 15 on March sixth, I highly recommend it.
Perfect. I did have one follow-up and it goes to some of the color that you provided on node, the customers coming out of pilot and how they're choosing to license ARM going forward. And so with the kind of more of a shift or more of a preference, I guess, for final subscription contracts. So luckily, what does that imply for like quarterly revenue was in the next couple of quarters as we've been trying to think that there might be a headwind on assessments, neutralized consumption contracts and fuel consumption will eventually materialize should grow and that becomes revenue accretive and that was with the mix shift to directionally, how should I think about that impact quarterly revenue if that trend continues from here on going forward?
Firstly, on China, if I had a headwind in either the storage.
Okay.
Um, um, sometime thereafter like offline, Tom, you have heard that headwind is okay.
The of the bottom line is the customer has the option of licensing it for your biotech. It will take months and months and will pay for these up for the for for CPU, our okay or many of them. You don't want to deal with price certainty because their plan on expanding in a pretty big way. And they say, hey, guys, let's talk about a three-year commitment. We're going to give the mic to a certain amount of money in year one year, two year three, and there's consumption pricing component. Now the bottom line is Sanjit. It's revenue neutral to us over 10 quarters. So it doesn't matter at our business. Our business is the when the customer service business, however, the customer wants to buy it, we're going to sell it, but it has really no meaningful impact on our revenue modeling.
But it did come as a surprise is counterintuitive.
Yes. No, that's great. I'll leave it there. And I'll give the floor to you and we are in a thank you so much.

Operator

Thank you. One moment for next question.
And our next question comes from Pat Walravens of JMP Securities.

Patrick D. Walravens

Have a great day. I'd like to start with one sort of financial one and then Tom, I have a big picture one for you. So you hold maybe on your way out I mean, this is your Q three next quarters, Q4, and then you're going to you're going to give us some guidance for fiscal 25 just to keep us all in check or not kind of middle of the year?
Yes, we thought let's not get ahead of ourselves.

Can we just can you just get some sense of what some boundaries in terms of what we should think about for fiscal 25, either the top tax, first of all, for that question, but I mean, we're still we're still planning for FY 25. I mean, we think the opportunity is massive. We're very excited about the general debate I opportunity, but it's too early for us to give you any sort of guidance as to what their flight 25 revenues look like. We are confident on free cash flow positivity for 25, Howard.

Okay. Well, that's helpful. And then, Tom, the big one for you is. I'm just wondering about the sort of and think future demand curve for nation-state sovereign clouds. That's everything I had breakfast with a another a EXECUTIVE this week and one of the comments he made was if you don't have access, if you don't have your own committed access to AI. in-country, you are dead. So see overstating the case or is this some is this another area where there's potentially a lot of work for you guys to do Koos, you see don't have access trials, all our people, whatever pick, whatever pick that pick the Prime Minister President of any of our allies?
Well, I think you have France, Germany, UK, we do have sovereign access, okay? And so we're not finding this a problem, a data sovereignty, a problem because one or more of the cloud providers does guarantee data sovereignty. I think actually the interesting trend up, Pat, that we're seeing and this is really counterintuitive. I think I think we're going to see the return of in-house data centers.
Okay. And I think they see like what HP. is leading with what do they call it green green gas greenhouse with these supercomputers that will be inside of, you know, Goldman Sachs and U.K. and Bank of America and other firms. I think I think we're going to see a return to in-house data centers, believe it or not, okay, where people have the G, we get the GPUs inside, but data sovereignty is not a difficult problem to solve and we're able to address it and we have customers all over the world.
Yes, I believe it's a Level zero requirement and the the our friends at Zohr and AWS in particular do kind of nail that quite well, if I can, I can I go a little deeper on your comment about why we're returning to in-house data centers Why do I think that that will what are you seeing that's driving that sub hearing mission in the marketplace? And in even my engineers you've talked about, okay, that is going to be cost effective for us to build.
Now the constraint is it you think was somebody needs a call-up chance impact for GPUs. Let's say we could figure out how to do that maybe we know somebody knows Jen-Hsun, okay, the The hard part is we can't get power. So I think the constraint on this going for everybody sees the constraint is availability of GPUs. I think a good straight on this soon is going to be the availability of power. You cannot get power to build the data center in Silicon Valley. You notice right. Again, Northern Silicon Valley is SPG. and E., which is I have no comment on that Southern Southern Silicon Valley or some other power company. I know not what, but they will not give you a powerful data set. So it's I think I think this I think this GPU constraint is ephemeral as soon it's going to be power by us.
Thank you.

Operator

Thank you. One moment for our next question.
And our next question comes from Mike Cikos of Needham & Company.

Have great. Thanks, guys. This is [Matt Litram] on for Mike because over a need of good to hear that the consumption transition is tracking in line with your initial target. On that note, what can you tell us about the size of your sales force, the ramping of these reps and the number of pilots being signed per sales rep relative to your expectations?

Hi, as you help, so the sales. We are still hiring activity in all of our sales functions, but not as fast as we'd like. So we our sales force is not as high as we initially projected when we provided these sort of assumptions, but we continue to ramp up on that as it becomes to the ramping up the sales force. I think previously we've said that everybody should make some sort of our expectations and assumptions in their models until they closed their first pilots. But a reasonable assumption would be 1.5, two quarters before they get fully ramped up and get going on on closing their first pilot and then what, Matt, what was your third question, just if anything has changed as far as like how many pilots you're expecting each rep because I know that was part of the initial assumptions, I think I'm wondering.
Yes, once Yes, once again, we lead with the pilot sales motion. So all the sales reps when they close new business is expected to get with a pilot. So we would expect each of the sales guys to bring in at least a positive quarter once they're fully ramped up and everything subscale, but we're not quite yet there.

Okay, great. Thanks for that. And then has the Company noted any change in the length of sales cycles this quarter versus the prior quarter, given management's comments on customer considerations for a U.S. government and as we've published it, when we took it up from the 10 Q so the sales cycle is about the same. About a it's about the same as yet hasn't changed, which is about 3.5 month.
Yes, beautiful. Thanks so much, guys.

Operator

Thank you One moment for our next question.
And our last question comes from Kingsley Crane of Canaccord Genuity Group business.

William Kingsley Crane

There's no question our commend you for the great Q3 and really strong momentum in the business.
With respect to your comments on in video and enterprise, a I think what we're all trying to figure out is when that is in videos, 200 plus percent growth in hardware investments start flowing into the software layer, and we're seeing some of that already.
But is that more like one year, five years?
I think we see the tidal wave coming, but we're all trying to time it.

Well, Gary change the it's a good question, Tito, but I could tell you all this infrastructure is not being put out there to like play games, okay, is put out there to run enterprise AI applications. And so these guys are out there building a highway for us and thank goodness for that. And I think that, you know, we.
Yes, in terms of we look at and I think here, January aware of the market interest in AI applications, and I think you're generally aware, maybe more than generally probably specifically aware of the of the interest in generative AI applications, and that's what those GPOs you're going to be doing and they're going to be running. And the good news is they'll be there show it's there's a lot of things coming into place.

Thank you, that that's really helpful. And the last one is just that we're seeing so much investment domestically, you've had such great success both with federal and state and local. Are you doing the international opportunity today both in Europe and then in regions like a back.

So I don't I disclosed I think last quarter that our performance in Amea was significantly substandard.
Okay. And any and that was a pretty clear about that and you know, come as a big surprise to everybody on this call that may we made some organizational changes and the AG. I'm pleased to report that those changes have been quite positive. And we're seeing the levels of sales activity and customer engagement increasing dramatically in the theater and interestingly enough, the South America theater to. So there's that that's thanks for the question, and we're seeing very positive news there.

That's great.

Thank you.

And you know, it's been fantastic work with you. I wish you the best of luck.

Thanks again.
Tactically.

Operator

Thank you. I would now like to hand it back, Mr. Siegel for closing remarks.

Ladies and gentlemen, thank you for your time this afternoon. We appreciate the opportunity to update you on the state of our business. I can tell you that for those of you who have visited us, you know, this is a very unique place. We have the only full parking lot in Silicon Valley. There are five or 600 people here working with us today shoulder to shoulder to their here Monday through Friday, and we're working in Chicago Atlanta station, this Washington, D.C., London, Rome, Paris, we're were all added. We have a very unique, high performance corporate culture that I think is going to serve as a real strong competitive advantage in the long run. So this places just kind of vibrating with excitement. And I think for all of us involved is the professional experience of a lifetime. And we thank you for the opportunity to share with you and we look forward to them.
Bring me up to speed next quarter lobbies. Last thought for those of you your time, I really encourage you to dial in to see three transform next week because I think you'll you'll find it. These are professional presentations that are quite substantive and it will be a good use of your time if you have time.
Ladies and gentlemen, thank you very much and we look forward to talking again.

Operator

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