C3.ai Inc (AI) 2024 Q4 法說會逐字稿

Good day and welcome to the C3 AI’s fourth-quarter fiscal year 2024 conference call. (Operator Instructions) Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker, Mr. Amit Berry. Please go ahead.

美好的一天，歡迎參加 C3 AI 2024 財年第四季電話會議。 （操作員指示）請注意，今天的會議正在錄製中。現在我想將會議交給您的發言人阿米特·貝裡先生。請繼續。

Good afternoon and welcome to C3 AI's earnings call for the fourth-quarter fiscal year 2024, which ended on April 30 2024. My name is Amit Berry, and I lead Investor Relations at C3 AI. With me on the call today is Tom Siebel, Chairman and Chief Executive Officer; and Hitesh Lath, Chief Financial Officer. After the market closed today, we issued a press release with details regarding our fourth 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.c3.ai.

下午好，歡迎參加 C3 AI 於 2024 年 4 月 30 日結束的 2024 年第四季財報電話會議。今天與我一起參加電話會議的是董事長兼執行長湯姆·西貝爾 (Tom Siebel)；和財務長 Hitesh Lath。今天收盤後，我們發布了一份新聞稿，其中詳細介紹了我們第四季度的業績以及業績的補充，這兩個內容都可以透過我們網站 ir.c3.ai 的投資者關係部分存取。

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 the 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.

本次電話會議正在網路直播，電話會議結束後將在我們的 IR 網站上提供重播。在今天的電話會議中，我們將發表與聯邦證券法可能被視為前瞻性的業務相關的聲明。這些聲明僅反映我們今天的觀點，不應被視為代表我們任何後續日期的觀點。我們不承擔更新任何前瞻性陳述或展望的義務。

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 on 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.

這些陳述受到各種風險和不確定性的影響，可能導致實際結果與預期有重大差異。有關重大風險和其他可能影響我們實際結果的重要因素的進一步討論，請參閱我們向 SEC 提交的文件。除非另有說明，所有數據都將在非公認會計原則的基礎上討論。此外，在今天的電話會議中，我們將提及某些非公認會計準則財務指標。

A reconciliation of GAAP to non-GAAP measures is included in our press release. Finally, at times 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.

我們的新聞稿中包含了 GAAP 與非 GAAP 指標的調整表。最後，有時在我們準備好的評論中，為了回答您的問題，我們可能會討論對我們通常的演示來說是增量的指標，以便更深入地了解我們的業務動態或季度業績。請注意，我們將來可能會也可能不會繼續提供此附加詳細資訊。接下來，讓我把電話轉給湯姆。

Thank you, Amit. Good afternoon, everyone, and thank you for joining our call today. Hitesh and I are pleased to share with you our results for the fourth quarter and for the entire fiscal year of 2024. Q4 was a great quarter and the end of a huge year for C3 AI. We exceeded all expectations for revenue, cash flow, and profitability. Let me be clear: there were no expectations that we did not exceed.

謝謝你，阿米特。大家下午好，感謝您今天加入我們的電話會議。 Hitesh 和我很高興與您分享我們第四季度以及 2024 年整個財年的業績。我們超越了收入、現金流和獲利能力的所有預期。讓我明確一點：我們沒有超越任何期望。

This was our fifth consecutive quarter of accelerating revenue growth. Our quarterly year-over-year revenue growth has accelerated from 11% in Q1 to 17% in Q2, 18% in Q3, and now, 20% in Q4 of fiscal year '24. Our quarterly subscription revenue has also significantly accelerated, going from 8% in Q1 to 12% in Q2, 23% in Q3, and 41% in Q4 on a year-over-year basis. We finished the quarter with $86.6 million in revenue, exceeding the high-end of both our guidance and analyst expectations.

這是我們連續第五個季度營收加速成長。我們的季度年收入成長已從第一季的 11% 加速到第二季的 17%、第三季的 18%，以及現在 24 財年第四季的 20%。我們的季度訂閱收入也顯著加速，年成長從第一季的 8% 上升到第二季的 12%、第三季的 23% 和第四季的 41%。本季我們的營收為 8,660 萬美元，超出了我們的指導和分析師預期的上限。

I'll note that this is the 14th consecutive quarter as a public company in which we have met or exceeded our revenue guidance. For the quarter, subscription revenue was $79.9 million, accounting for 92% of total revenue and increasing 41% from a year ago. Our non-GAAP gross profit was $60.9 million, representing a 70% gross margin. Our GAAP operating loss was $82.3 million.

我要指出的是，作為一家上市公司，這是我們連續第 14 個季度達到或超過了我們的收入指導。該季度訂閱營收為 7,990 萬美元，佔總營收的 92%，較去年同期成長 41%。我們的非 GAAP 毛利為 6,090 萬美元，毛利率為 70%。我們的 GAAP 營運虧損為 8,230 萬美元。

Our non-GAAP operating loss was $23.4 million, better than our guidance for a loss of $43.5 million to $51.5 million. Our non-GAAP net loss per share was $0.11. We generated a free cash flow of $18.8 million, down the quarter with $750.4 million in cash, cash equivalents and investments, again exceeding analyst consensus. Full year results exceeded both the high-end of our guidance and analyst expectations with record revenue of $310.6 million, a 16% increase over last year.

我們的非 GAAP 營業虧損為 2,340 萬美元，優於我們指導的 4,350 萬至 5,150 萬美元虧損。我們的非 GAAP 每股淨虧損為 0.11 美元。我們的自由現金流為 1,880 萬美元，本季現金、現金等價物和投資為 7.504 億美元，再次超出了分析師的預期。全年業績超出了我們指導的上限和分析師的預期，收入達到創紀錄的 3.106 億美元，比去年增長 16%。

Subscription revenue was $278.1 million, a 21% increase over last year. Now, with the transition that we went through to pay-as-you-go consumption pricing, we are engaging in a much larger number of smaller transactions of shorter term. This offers us greater revenue visibility and greater revenue predictability. Our average TCV has plummeted as a result from over $16 million in fiscal year '19 to $900,000 last quarter.

訂閱收入為 2.781 億美元，比去年增長 21%。現在，隨著我們向現收現付消費定價的轉變，我們正在進行大量的短期小額交易。這為我們提供了更高的收入可視性和更高的收入可預測性。我們的平均 TCV 從 19 財年的 1,600 萬美元驟降到上季的 90 萬美元。

As we work through this pricing transition, we are seeing, as expected, okay, at first a decline, and now, a return to accelerating revenue growth. Also, as expected, we are seeing a reduction in RPO. We expect RPO to continue to decline in the next few quarters as we expect revenue to increase. This is a mathematical certainty from the change in our go-to-market model, and I am not certain at all that RPO is a valid leading indicator of our business in the short term going forward.

當我們完成這次定價轉型時，我們看到，正如預期的那樣，一開始是下降，現在又恢復了營收加速成長。此外，正如預期的那樣，我們看到 RPO 有所下降。我們預計 RPO 將在未來幾季繼續下降，因為我們預計收入將增加。這是我們進入市場模型變化的數學確定性，我完全不確定 RPO 是否是我們業務短期內的有效領先指標。

Let's take a look at the AI value stack. There clearly is a market frenzy today around AI infrastructure. Now, when you look at the value stack at AI, at the bottom you have silicon. Above that you have infrastructure. Above that you have foundation models. And on top of all of that you have enterprise AI Applications.

我們來看看AI價值棧。如今，人工智慧基礎設施顯然存在市場狂熱。現在，當你觀察人工智慧的價值堆疊時，你會發現最底層的是矽。除此之外，還有基礎建設。在其之上有基礎模型。最重要的是，您還有企業人工智慧應用。

C3 AI plays at the top of the stack, okay, focused exclusively on Enterprise AI applications. Now, we believe that in the long run, silicon and infrastructure get commoditized and AI applications dominate the value stack. As an analog, think about the early stages of the personal computer market. At the beginning, most of the value was in the silicon and the infrastructure.

C3 AI 在堆疊的頂部發揮作用，好吧，專門專注於企業 AI 應用程式。現在，我們相信，從長遠來看，晶片和基礎設施將商品化，人工智慧應用將主導價值堆疊。作為一個類比，想想個人電腦市場的早期階段。一開始，大部分價值都在晶片和基礎設施。

Think about the IBM PC/XT that you might have used in 1983, okay, it cost $7,900. In today's dollars, that would be $22,000. You might have had $200 to $300 worth of software running on that machine that you purchased from BusyCal or Lotus or wherever. Now, that PC that's on your desk today cost your company about $200 a year in depreciation expense for the hardware and another $200 a year or so for infrastructure cost.

想想您可能在 1983 年使用過的 IBM PC/XT，好吧，它的價格為 7,900 美元。以今天的美元計算，這將是 22,000 美元。您可能在從 BusyCal 或 Lotus 或其他地方購買的電腦上運行了價值 200 到 300 美元的軟體。現在，您辦公桌上的那台 PC 每年會花費您公司約 200 美元的硬體折舊費用，另外每年還要花費 200 美元左右的基礎設施成本。

And by the time you have all the applications you're running on that computer, be it Bloomberg, SAP, CRM, okay, whatever it might be, those applications can exceed $8,000 a year in total cost. Well, the AI era will be no different and the same game is going to play out as we move forward. The bulk of the value is going to accrue to the applications that leverage the entire AI stack and deliver value to the business. Silicon will get commoditized; it always gets commoditized.

當您擁有在該電腦上運行的所有應用程式時，無論是 Bloomberg、SAP、CRM，好吧，無論它是什麼，這些應用程式每年的總成本可能會超過 8,000 美元。嗯，人工智慧時代也不會有什麼不同，隨著我們的前進，同樣的遊戲也會上演。大部分價值將來自利用整個人工智慧堆疊並為業務帶來價值的應用程式。矽將商品化；它總是被商品化。

Infrastructure will get commoditized. It always gets commoditized. What doesn't get commoditized in the long run are the applications and that's where C3 AI plays. Let's take a look at the market dynamics in AI, okay? This is proving a headwind for some companies as we're seeing, and it's proving a tailwind for some companies. For us, it is clearly a tailwind.

基礎設施將商品化。它總是被商品化。從長遠來看，應用程式不會商品化，而這正是 C3 AI 發揮作用的地方。我們來看看人工智慧的市場動態，好嗎？正如我們所看到的，這對一些公司來說是逆風，對一些公司來說則是順風。對我們來說，這顯然是順風順水。

Okay, the primary competitor to C3 AI remains, try to build versus buy. Building AI applications for an enterprise is incredibly difficult and unlike anything CIOs have encountered before. In fairness, most CIOs have their hands full trying to install single sign on, trying to get their security firewalls to work, and trying to figure out how to manage over budget, delayed, sometimes multi-billion dollar SAP upgrades from Accenture and Deloitte, okay? Developing enterprise scale application software is simply not what they do.

好吧，C3 AI 的主要競爭對手仍然存在，嘗試建造而不是購買。為企業建立人工智慧應用程式非常困難，這與資訊長以前遇到的任何事情都不一樣。公平地說，大多數 CIO 都忙於安裝單點登錄，試圖讓安全防火牆正常工作，並試圖弄清楚如何管理埃森哲和德勤的超出預算、延遲、有時甚至數十億美元的 SAP 升級，好的？開發企業級應用軟體根本不是他們所做的。

The extensive infrastructure and software services required to operate AI applications at scale are exceptionally complex and not feasible for most companies to manage with an in house team of IT engineers. Today, many companies are dabbling in trivial AI projects or relying on outside integrators to try to cobble together something that works. These are nothing more than large and expensive experiments nobody succeeds. In reality, enterprise customers don't want to buy tools to build applications. They want to buy applications.

大規模運行人工智慧應用程式所需的廣泛基礎設施和軟體服務異常複雜，對於大多數公司來說，透過內部 IT 工程師團隊進行管理是不可行的。如今，許多公司都在涉足瑣碎的人工智慧項目，或依靠外部整合商來嘗試拼湊出一些可行的東西。這些只不過是大型且昂貴的實驗，但沒有人成功。事實上，企業客戶不想購買工具來建立應用程式。他們想要購買應用程式。

We've already proven this. We've proven it in the relational database market. We've proven it in the ERP market. We've proven it in the CRM market. At C3 AI, we've dedicated 15 years and a couple billion dollars worth of software engineering in building a powerful AI platform that underpins some of the largest enterprise AI deployments on earth today. We started this effort in 2009 before anybody even talked about Enterprise AI, before Azure existed, before GCP existed, okay, before the GPU existed.

我們已經證明了這一點。我們已經在關係資料庫市場證明了這一點。我們已經在 ERP 市場上證明了這一點。我們已經在 CRM 市場證明了這一點。在 C3 AI，我們投入了 15 年時間和價值數十億美元的軟體工程來建立強大的 AI 平台，為當今地球上一些最大的企業 AI 部署提供支援。我們在 2009 年就開始了這項工作，甚至在任何人談論企業人工智慧之前，在 Azure 存在之前，在 GCP 存在之前，好吧，在 GPU 存在之前。

With significant first mover advantage, we serve the market today with 90 Enterprise AI and Generative AI applications that offer outsized economic benefit. Our business is focused on enterprise AI applications. In fiscal year '24, 88% of our bookings were driven by AI application sales and 12% of our bookings were driven by the C3 AI platform. Our pilot counts surged to 123 for the year as we closed 191 agreements now across 19 different industries, underscoring the effectiveness of these products in meetings complex business needs across many business sectors.

憑藉著顯著的先發優勢，我們為當今的市場提供了 90 種企業人工智慧和生成式人工智慧應用程序，可帶來巨大的經濟效益。我們的業務專注於企業人工智慧應用。在 24 財年，我們 88% 的預訂是由人工智慧應用程式銷售推動的，12% 的預訂是由 C3 人工智慧平台推動的。今年，我們的試點數量激增至 123 個，目前我們在 19 個不同行業簽署了 191 份協議，凸顯了這些產品在滿足多個業務部門複雜業務需求方面的有效性。

Our bookings distribution for the fourth quarter was approximately 50% federal, defense and aerospace, 15% oil and gas, 11% state government, 7% manufacturing, 6% energy and utilities, 5% consumer packaged goods, 5% crofessional services. This increase in bookings diversity would be a leading indicator for C3 AI. Our pilot distribution for the fourth quarter was 29% manufacturing, 21% federal, defense, and aerospace, 12% agriculture, 9% chemicals, 6% life sciences, 6% oil and gas, 6% state and local, 6% energy and utilities, and 3% logistics and transportation. This pilot diversity is a future indicator of where you expect this company to be going.

我們第四季的預訂分佈約為 50% 聯邦、國防和航空航太、15% 石油和天然氣、11% 州政府、7% 製造業、6% 能源和公用事業、5% 消費品、5% 專業服務。預訂多樣性的增加將成為 C3 AI 的領先指標。我們第四季的試點分配是29% 製造業，21% 聯邦、國防和航空航天，12% 農業，9% 化學品，6% 生命科學，6% 石油和天然氣，6% 州和地方，6%能源和公用事業，以及 3% 的物流和運輸。這種試點多樣性是您期望該公司未來發展方向的指標。

Now, let me provide a brief update on some of our recent product advancements: first, Version 8 of our Platform and Applications is providing customers with an order of magnitude improvement in speed, efficiency and overall performance. With Version 8, it is now more than 20 times faster to ingest data, train machine learning models and infer time series features, and customers can run thousands of applications in a single C3 AI platform cluster to reach highly scalable deployments. The C3 AI Community is the name of our interactive training, online help and developer platform. It is becoming a thriving ecosystem for engagement and collaboration amongst C3 developers and data scientists around the world.

現在，讓我簡要介紹我們最近的一些產品進展：首先，我們的平台和應用程式版本 8 為客戶提供了速度、效率和整體效能的數量級改進。借助版本 8，現在提取資料、訓練機器學習模型和推斷時間序列特徵的速度提高了 20 倍以上，客戶可以在單一 C3 AI 平台叢集中運行數千個應用程序，以實現高度可擴展的部署。 C3 AI 社群是我們的互動培訓、線上幫助和開發者平台的名稱。它正在成為一個蓬勃發展的生態系統，供世界各地的 C3 開發人員和資料科學家參與和協作。

This year, we supercharged the C3 AI community by delivering C3 Generative AI co-pilot, which instantly answers questions and generates code for programmers to massively increase developer productivity on the C3 AI platform. Let me talk a little bit about customer traction. We are witnessing increased usage amongst our customers. Cargill has expanded from 13 to 18 plants in production in the past year.

今年，我們透過提供 C3 Generative AI co-pilot 來增強 C3 AI 社群的實力，它可以立即回答問題並為程式設計師產生程式碼，從而大幅提高 C3 AI 平台上的開發人員生產力。讓我談談客戶吸引力。我們看到客戶的使用量不斷增加。去年，嘉吉已將生產工廠從 13 家擴大到 18 家。

Baker Hughes sourcing optimization is now deployed across 855 sites and three business segments with 2,000 users, offering a potential savings of $100 million a year. C3 AI reliability is now deployed at 12 plants at Petronas, monitoring 4,000 control valves, and realizing $25 million a year of annual loss avoidance. [Dow] is enhancing its predictive maintenance capabilities with C3 AI reliability and has announced that it's expecting to decrease downtime for steam cracking furnaces in polyethylene production facilities by 20%. Holcim, a large European construction products company, started with C3 AI reliability production pilot in May of 2023 and now has 31 facilities in production, running over 200 machine learning models to monitor 3,000 sensors from critical equipment, including vertical roller mills.

Baker Hughes 採購優化現已部署在 855 個站點和三個業務部門，擁有 2,000 名用戶，每年可節省 1 億美元。 C3 AI 可靠性現已部署在 Petronas 的 12 家工廠，監控 4,000 個控制閥，每年實現 2,500 萬美元的避免損失。 [陶氏]正在利用 C3 AI 可靠性增強其預測維護能力，並宣布預計將聚乙烯生產設施中蒸汽裂解爐的停機時間減少 20%。 Holcim 是一家歐洲大型建築產品公司，於2023 年5 月開始進行C3 AI 可靠性生產試點，目前擁有31 座生產設施，運行200 多個機器學習模型，以監控關鍵設備（包括垂直輥磨機）的3,000 個感測器。

According to Roze Wesby, who is Head of Plants of Tomorrow at Holcim, and this is a quote, C3 AI is playing an important role in Holcim's digital transformation, providing innovative AI solutions that drive efficiency and sustainability. She continues, the collaboration between C3 AI and Holcim has led to advancements in operational efficiency at scale, raising the bar for predictive maintenance in our sites. Thanks to C3 AI's platform, Holcim has achieved a step function change, okay, in asset life cycle management, improving our reliability and capacity for our customers, as well as reducing environmental impact.

Holcim 未來植物負責人 Roze Wesby 表示，C3 AI 在 Holcim 的數位轉型中發揮重要作用，提供創新的 AI 解決方案來提高效率和永續性。她繼續說道，C3 AI 和 Holcim 之間的合作極大地提高了營運效率，提高了我們站點預測性維護的標準。借助 C3 AI 的平台，Holcim 在資產生命週期管理方面實現了階躍功能變革，提高了我們為客戶提供的可靠性和能力，並減少了對環境的影響。

Con Edison, a C3 AI customer since 2017, uses the C3 AI platform to improve everything from operational and energy efficiency to public safety, billing performance, and customer satisfaction. According to Tom Magee, who is general manager for Con Ed's advanced metering infrastructure project, and I quote, the AMI project, the largest in Con Edison history included the deployment of 5.3 million smart meters and resulted in significant benefits such as improved outage management and energy efficiency. The use of AI and machine learning has enhanced public safety, optimized grid operations, and achieved substantial energy savings, and emissions reductions for our customers. We monitor our customer satisfaction very closely, and our customer satisfaction levels are well above industry averages for enterprise application software.

聯合愛迪生公司自 2017 年起成為 C3 AI 客戶，使用 C3 AI 平台來改善從營運和能源效率到公共安全、計費效能和客戶滿意度的各個方面。根據聯合愛迪生公司高級計量基礎設施項目（我引用的是AMI 項目）總經理Tom Magee 的說法，聯合愛迪生公司歷史上最大的項目包括部署530 萬個智慧電錶，並帶來了顯著的效益，例如改進的停電管理和能源效率。人工智慧和機器學習的使用增強了公共安全，優化了電網運營，並為我們的客戶實現了大幅節能減排。我們非常密切地監控客戶滿意度，我們的客戶滿意度遠高於企業應用軟體的行業平均水平。

We'll talk a little bit about the strength that we're seeing in the US federal market. We had a strong quarter and closed out a remarkable year for the federal business, with revenue growing more than 100% in 2024. Our transaction in this vertical is increasing, establishing it as a significant growth engine for C3 AI going forward. Last year, we closed 65 agreements with federal agencies and made inroads into 10 new federal organizations.

我們將談談我們在美國聯邦市場看到的實力。我們度過了一個強勁的季度，為聯邦業務帶來了非凡的一年，2024 年收入成長超過 100%。去年，我們與聯邦機構達成了 65 項協議，並進入了 10 個新的聯邦組織。

In Q4, we entered into 13 new and expanded agreements with the US Air Force, the US Navy, the US Intelligence Community, the Defense Counterintelligence and Security Agency, the Chief Digital and Artificial Intelligence Office, the Thales group, and the US Marine Corps. Our expertise and leadership in predictive maintenance is clear when you look at the work we do with the US Air Force and now, the Navy. The US Air Force Rapid Sustainment Office continues to expand their C3 AI footprint by increasing the capabilities in the number of weapons systems monitored on the predictive analytics and decision-assisted application. This system they call Panda.

第四季度，我們與美國空軍、美國海軍、美國情報界、國防反情報和安全局、首席數位和人工智慧辦公室、泰雷茲集團和美國海軍陸戰隊簽訂了 13 項新的和擴展的協議。當您看到我們與美國空軍以及現在的海軍所做的工作時，我們在預測性維護方面的專業知識和領導地位就顯而易見。美國空軍快速保障辦公室透過增加預測分析和決策輔助應用程式監控的武器系統數量的能力，繼續擴大其 C3 AI 足跡。他們稱這個系統為Panda。

This is the system of record for all predictive maintenance projects within RSO and the United States Air Force, optimizing fleet maintenance, increasing aircraft availability, and minimizing downtime. This application is now being applied to monitor two new weapon systems, the T7 and the KC46, and it's been expanded to include new capability for the B-1 Bomber, the C5, or the KC-135. According to Jimmy Lawrence, who is the Deputy Program Executive Officer for the Rapid Sustainment Office, and this is a quote. C3 AI's cutting-edge technology has been a game changer for the US Air Force, driving unparalleled advancements in predictive analytics and maintenance. The implementation of C3 AI solutions have revolutionized the operational capabilities of the Air Force, leading to significant improvements in aircraft readiness and efficiency.

這是 RSO 和美國空軍內所有預測性維護項目的記錄系統，可優化機隊維護、提高飛機可用性並最大限度地減少停機時間。該應用程式現在用於監控兩種新武器系統：T7 和 KC46，並且已擴展到包括 B-1 轟炸機、C5 或 KC-135 的新功能。據快速維持辦公室副項目執行官吉米勞倫斯說，這是一句話。 C3 AI 的尖端技術改變了美國空軍的遊戲規則，推動了預測分析和維護方面無與倫比的進步。 C3 AI 解決方案的實施徹底改變了空軍的作戰能力，顯著提高了飛機的戰備狀態和效率。

We've also been working with the US Navy, building on predictive maintenance program for C3 AI and the US Air Force on the Crowdsource flight data program at Nellis Air Force Base in Nevada. This new agreement also expands the Navy into the analysis of electronic emissions on the F-35 weapon system. Talk a little bit about the C3 AI Partner Network, our partners remain a key driver of growth and customer success, as we continue to deepen our relationships with the major hyperscaler providers and system integration partners. Last year, we closed 115 agreements through our partner network, representing a 62% increase from the prior year.

我們也一直與美國海軍合作，建立 C3 AI 的預測性維護計劃，並與美國空軍合作在內華達州內利斯空軍基地的眾包飛行數據計劃上。這項新協議也將海軍擴展到 F-35 武器系統的電子發射分析領域。談談 C3 AI 合作夥伴網絡，隨著我們不斷深化與主要超大規模供應商和系統整合合作夥伴的關係，我們的合作夥伴仍然是成長和客戶成功的關鍵驅動力。去年，我們透過合作夥伴網路達成了 115 項協議，比前一年增加了 62%。

This includes 91 agreements with AWS, Google Cloud, and Azure. Our joint 12-month qualified pipeline with partners grew by 63% year-over-year. Our business activity with Google Cloud has increased considerably. In Q4 alone, we closed 12 pilots with Google Cloud.

其中包括與 AWS、Google Cloud 和 Azure 簽訂的 91 項協定。我們與合作夥伴聯合開展的 12 個月合格管道年增 63%。我們與 Google Cloud 的業務活動大幅增加。光是在第四季度，我們就完成了 12 場 Google Cloud 試點。

There's a massive amount of support from GCP, in pursuing our state and local pilots, and Google has committed to invest with us in a big way in the first quarter. We've also substantially increased our partnerships with two firms, one Fractal, and the other called Paradyme, partnering with them for professional services to support our Version 8 upgrades, customer service engagements and pilot delivery. These organizations have established dedicated practices around C3 AI and are committed to train over 200 C3 AI qualified engineers and data scientists in the coming year. Let's double click on C3 Generative AI.

在推行我們的州和地方試點過程中，GCP 提供了大量支持，Google 也承諾在第一季與我們進行大量投資。我們也大幅加強了與兩家公司的合作關係，一家是 Fractal，另一家是 Paradyme，與他們合作提供專業服務來支援我們的版本 8 升級、客戶服務參與和試點交付。這些組織圍繞著 C3 AI 建立了專門的實踐，並致力於在來年培訓 200 多名 C3 AI 合格工程師和資料科學家。讓我們雙擊 C3 Generative AI。

Folks, this is a massive opportunity. There is substantial and growing demand for our C3 Generative AI products. The market is very much coming our way. The company launched 30 generative AI products in fiscal year '24, and we are being overwhelmed with market interest for these products.

各位，這是一個巨大的機會。對我們的 C3 生成式人工智慧產品的需求巨大且不斷增長。市場正朝著我們的方向發展。該公司在 24 財年推出了 30 款生成式人工智慧產品，市場對這些產品的興趣讓我們不知所措。

In Q4 alone, we received almost 50,000 inquiries from 3,000 businesses, each with revenue greater than $500 million, all expressing interest in our generative AI Applications. 50,000, 10,500 in the 28 days of February alone. We currently expect this to expand to 90,000 inquiries in the first quarter of '25. Over the past year, C3 Generative AI was piloted across 15 different industries, driving us deeper into new verticals and accelerating our industry diversification. If we look at the industries that we touched with these pilots, be like 21% federal, defense, and aerospace, 12% manufacturing, 10% ag, 10% state and local government, 7% financial services, 5% chemicals, 5% construction, 5% CPG, 5% energy utilities, 5% oil and gas, 5% pharmaceuticals and life sciences.

光是在第四季度，我們就收到了來自 3,000 家企業的近 50,000 份詢問，每家企業的收入都超過 5 億美元，所有企業都表達了對我們的生成式 AI 應用程式的興趣。光是二月的 28 天就增加了 5 萬人、10,500 人。目前，我們預計 2025 年第一季的諮詢量將增加至 9 萬次。過去一年，C3 Generative AI 在 15 個不同產業進行試點，推動我們更深入地進入新的垂直領域，加速我們的產業多元化。如果我們看看這些試點涉及的產業，例如 21% 聯邦、國防和航空航太、12% 製造業、10% 農業、10% 州和地方政府、7% 金融服務、5% 化學品、5%建築業、CPG 5%、能源公用事業5%、石油和天然氣5%、製藥和生命科學5%。

The C3 generative AI remains a highly differentiated product offering in the generative AI market, providing customers with safe, secure, fast, reliable information from across their enterprise. It enables retrieval and reasoning across omni-modal data with deterministic responses fully traceable to ground truth sources. It offers robust enterprise controls, no incremental cybersecurity risk caused by or LLM caused data leakage, minimal hallucination risk, poses no IP liability exposure from the LLM, and provides flexibility to be completely LLM agnostic. And we further differentiated C3 generative AI from other market offerings in the course of the year in many, many ways.

C3 生成式人工智慧仍然是生成式人工智慧市場中高度差異化的產品，為客戶提供來自整個企業的安全、可靠、快速、可靠的資訊。它能夠跨全模態資料進行檢索和推理，確定性反應完全可追溯到地面真實來源。它提供強大的企業控制，不會因法學碩士或法學碩士導致的資料外洩而增加網路安全風險，幻覺風險最小，不會造成法學碩士的智慧財產權責任風險，並提供完全與法學碩士無關的靈活性。在這一年裡，我們在許多方面進一步將 C3 生成人工智慧與其他市場產品區分開來。

We have a rich product roadmap for the coming year, and we will continue to invest in this product to drive innovation in the generative AI market. Okay, so to wrap this up, over the decades and as inflation goes up and inflation goes down and markets boom and market bust, here we see equity market mood swings, okay. And great management teams don't build companies based upon the fad of the week. As it relates to equity markets, with increased inflation, the current pendulum has swung to a demand for instant cash generation and instant profitability.

我們為來年制定了豐富的產品路線圖，我們將繼續投資該產品，以推動產生人工智慧市場的創新。好吧，總結一下，幾十年來，隨著通貨膨脹的上升和下降以及市場的繁榮和市場蕭條，我們在這裡看到股市情緒波動，好吧。優秀的管理團隊不會根據當下的流行趨勢來建立公司。就股票市場而言，隨著通貨膨脹的加劇，當前的鐘擺已轉向對即時現金產生和即時獲利的需求。

Now, let's put this into perspective. It took Apple over a quarter of a century to be consistently profitable, a quarter of a century. How did that work out for Apple investors? It took Amazon 29 years to be consistently profitable, okay?

現在，讓我們正確看待這一點。蘋果花了四分之一個世紀的時間才持續獲利，四分之一個世紀。蘋果投資人的反應如何？亞馬遜花了 29 年才持續獲利，好嗎？

That generated roughly, okay, $2 trillion in investor value, okay? These companies were going after large market opportunities and they had conviction to invest for growth and market share along the way. Regardless of the current fad that happened in response to market fluctuations quarter-to-quarter and kind of day-to-day. C3 AI is looking at addressing a potentially $1 trillion addressable software market.

這大約產生了 2 兆美元的投資者價值，好嗎？這些公司正在尋求巨大的市場機會，並且他們有信心一路投資以實現成長和市場份額。不管當前的時尚是為了應對季度與季度和日常的市場波動而發生的。 C3 AI 正在尋求解決潛在 1 兆美元的可尋址軟體市場。

We believe this is the largest market opportunity in the history of software. We raised $1 billion in December of 2020. Think back, before the world at large was even talking about enterprise AI, and we raised that money to invest in growth, to invest in technology leadership, to invest in brand leadership, and to invest in market leadership. The investments we've made since then have been well considered, prudent, and consistent with what we communicated to investors.

我們相信這是軟體史上最大的市場機會。我們在 2020 年 12 月籌集了 10 億美元。從那時起，我們進行的投資都是經過深思熟慮、審慎的，並且與我們向投資者傳達的訊息一致。

Our investment plan is a lot longer than day-to-day investment cycles. So as it relates to guidance, we are expecting additional acceleration of C3 AI revenue to approximately 23% in fiscal year '25. At the same time, make no mistake, we plan to continue to invest in growth as necessary, to establish market share, to establish a market leadership position, and to build a long-term cash generating profitable market-leading enterprise AI software company. Our revenue guidance for Q1 of fiscal year '25 is going to be $84 million to $90 million.

我們的投資計劃比日常投資週期長得多。因此，就指導而言，我們預計 C3 AI 收入在 25 財年將進一步加速至約 23%。同時，毫無疑問，我們計劃繼續進行必要的成長投資，建立市場份額，建立市場領導地位，並建立一個長期創收盈利的市場領先的企業人工智慧軟體公司。我們對 25 財年第一季的營收指引將為 8,400 萬至 9,000 萬美元。

For the fiscal year we're looking at $370 million to $395 million. Our non-GAAP loss from operations, we're expecting to be for Q1 between a $22 million to $30 million loss and for the year $125 million to $95 million loss. And now, I'll turn the call over to our most competent CFO, Hitesh, for additional color and detail. Hitesh?

我們預計本財年的預算為 3.7 億至 3.95 億美元。我們預計第一季的非 GAAP 營運虧損為 2,200 萬至 3,000 萬美元，全年虧損為 1.25 億至 9,500 萬美元。現在，我將把電話轉給我們最有能力的財務長 Hitesh，以獲取更多資訊和細節。海特什？

Thank you, Tom. I will now provide a recap of our financial results and additional color on our business. All figures are non-GAAP unless otherwise noted. As Tom mentioned, total revenue for the fourth quarter increased 20% year-over-year to $86.6 million. Subscription revenue increased 41% year-over-year to $79.9 million and representing 92% of total revenue.

謝謝你，湯姆。現在，我將回顧我們的財務業績，並對我們的業務進行更多介紹。除非另有說明，所有數據均非公認會計原則。正如 Tom 所提到的，第四季總營收年增 20%，達到 8,660 萬美元。訂閱收入年增 41% 至 7,990 萬美元，佔總營收的 92%。

Professional services revenue was $6.7 million. This represented 8% of total revenue in the fourth-quarter of fiscal '24 as compared to 21.5% of total revenue in the fourth quarter of fiscal '23, demonstrating an improved mix of subscription revenue. Gross profit for the fourth quarter was $60.9 million and gross margin was 70%. Gross margin for professional services was higher this quarter due to a greater mix of higher margin professional services like prioritized engineering services.

專業服務收入為 670 萬美元。這佔 24 財年第四季總營收的 8%，而 23 財年第四季佔總營收的 21.5%，顯示訂閱營收組合有所改善。第四季毛利為 6,090 萬美元，毛利率為 70%。由於優先工程服務等利潤率較高的專業服務的組合增多，本季專業服務的毛利率較高。

Operating loss for the quarter was $23.4 million. Our operating loss was lower than guidance due to continued focus on expense management as well as the timing of additional investments we are making to capture market share. As we discussed last quarter, we expected fourth quarter free cash flow to be positive. Free cash flow for the quarter was $18.8 million. We continue to be very well-capitalized and closed the quarter with $750.4 million in cash, cash equivalents, and marketable securities.

該季度營運虧損為 2,340 萬美元。由於我們繼續關注費用管理以及我​​們為奪取市場份額而進行額外投資的時機，我們的營運虧損低於指導。正如我們上季度討論的那樣，我們預計第四季度自由現金流將為正值。該季度的自由現金流為 1880 萬美元。我們的資本仍然非常充足，本季末擁有 7.504 億美元的現金、現金等價物和有價證券。

Please note that the professional services mix in our revenue depends upon the nature and size of revenue deals in any given quarter. However, we expect the professional services revenue to generally stay within 10% to 20% of total revenue. As a reminder, we continue to expect short-term pressure on our gross margins due to higher mix of pilots, which carry a greater cost of revenue during the pilot phase of the customer life cycle. We also expect short-term pressure on our operating margin due to additional investments we are making in our business, including in our sales force, research and development, and marketing spend.

請注意，我們收入中的專業服務組合取決於任何特定季度收入交易的性質和規模。然而，我們預期專業服務收入將普遍維持在總收入的10%至20%以內。提醒一下，我們仍然預計，由於試點組合的增加，我們的毛利率將面臨短期壓力，這在客戶生命週期的試點階段帶來了更大的收入成本。我們也預計，由於我們對業務進行額外投資，包括銷售團隊、研發和行銷支出，我們的營運利潤率將面臨短期壓力。

At the end of Q4, our accounts receivable balance was $130 million including unbilled receivables of $62.3 million. Total allowance for bad debt remains low at less than $400,000 and we do not have concerns regarding collections. The general health of our accounts receivables remains strong. During the fourth quarter, we signed 34 pilots, a 79% increase from last year and up 17% from last quarter.

截至第四季末，我們的應收帳款餘額為 1.3 億美元，其中未開立應收帳款為 6,230 萬美元。壞帳準備金總額仍然很低，低於 40 萬美元，我們不擔心收款問題。我們的應收帳款整體健康狀況依然強勁。第四季度，我們簽署了 34 名試點項目，比去年增加 79%，比上個季度增加 17%。

At quarter end, we had cumulatively signed 172 pilots, of which, 157 are still active. This means they are either in their original three to six-month term or extended for some duration or converted to a subscription or consumption contract, or are currently being negotiated for conversion to subscription or consumption contract. Seven quarters ago, we announced the transition from subscription-based pricing to consumption-based pricing, a standard in the industry. We also announced that this transition would have a short to medium-term negative effect on revenue growth.

截至季度末，我們已累計簽約 172 名飛行員，其中 157 名仍然活躍。這意味著它們要么處於原來的三到六個月期限，要么延長一段時間，要么轉換為訂閱或消費合同，或者目前正在協商轉換為訂閱或消費合同。七個季度前，我們宣布從基於訂閱的定價過渡到基於消費的定價，這是行業標準。我們也宣布，這項轉變將對收入成長產生短期到中期的負面影響。

Accordingly, our GAAP RPO at the end of Q4 was $244.3 million, which is down 36% from last year. And our current GAAP RPO was $163.8 million, which is down 12% from last year. Now, I would like to turn the call over to the operator to begin the Q&A session. Operator?

因此，第四季末我們的 GAAP RPO 為 2.443 億美元，比去年下降 36%。我們目前的 GAAP RPO 為 1.638 億美元，比去年下降 12%。現在，我想將通話轉給接線員以開始問答環節。操作員？

(Operator Instructions) Timothy Horan, Oppenheimer.

（操作員說明）蒂莫西·霍蘭，奧本海默。

Thanks, guys and congratulations. Can you talk a little bit how did you get the 20-fold increase in improvements in Version 8? And how sustainable are those type of improvements? How long did that take to get?

謝謝你們，恭喜你們。您能談談您是如何在版本 8 中實現 20 倍的改進的嗎？這些類型的改進的可持續性如何？花了多久時間才得到？

And then secondly, obviously, the sales inquiries are off the charts. I mean, how scalable are these inquiries at this point? Both, I guess, to deal with the sales operations and the implementation of these inquiries. Thank you.

其次，顯然，銷售詢問量破紀錄。我的意思是，目前這些查詢的擴充性如何？我想，兩者都是為了處理銷售業務和執行這些查詢。謝謝。

Hi, it's Tom, Version 8 was a four-year engineering effort. I mean, it was a very large scale effort, and we basically gutted the product. We re-engineered the very core of it. And so it was a major release of the product and it's difficult to get into all the specifics, but we were heads down for four years on this, and it's a major architectural revamp.

嗨，我是 Tom，第 8 版是經過四年的工程努力。我的意思是，這是一項非常大規模的工作，我們基本上毀掉了這個產品。我們重新設計了它的核心。因此，這是該產品的一個主要版本，很難詳細了解所有細節，但我們為此埋頭苦幹了四年，這是一次重大的架構改造。

And we won't see performance increases like that again for a while. Sales inquiries, well, it's just been overwhelming what's been going on in generative AI. I think we reached 10,500 in February and then almost 50,000 last quarter. How scalable is it? Right now, we can believe that we can generate order of 90,000 a quarter.

我們在一段時間內不會再看到這樣的效能提升。銷售詢問，嗯，這對生成人工智慧領域正在發生的事情來說是壓倒性的。我認為我們在 2 月達到了 10,500 人，然後上個季度達到了近 50,000 人。它的可擴展性如何？現在，我們可以相信我們每季可以產生 90,000 個訂單。

And now, is that going to diminish at some point? We really don't know, but this is all brand new territory. But every time we look at this generative AI market, it looks bigger than it did before, so that is just a huge opportunity. And it's important to note we have a highly differentiated product there because all of these issues associated with hallucination, this new thing they call ramps, IP liability, access controls, stochastic responses, we've solved all those problems by coupling the learning models with the capabilities of the C3 AI platform.

現在，這種情況會在某個時候減少嗎？我們真的不知道，但這都是全新的領域。但每次我們審視這個生成式人工智慧市場時，它看起來都比以前更大，所以這是一個巨大的機會。值得注意的是，我們有一個高度差異化的產品，因為所有這些問題都與幻覺相關，他們稱之為斜坡、IP 責任、存取控制、隨機回應，我們透過將學習模型與C3 AI平台的功能。

So omni-modal data ingestion, we have that nailed. Identity, we have that nailed. Access control, we have that nailed. And so the marriage of the work we did in the first 15 years of the company with these new innovations in generative AI enables us to solve the problems that all the hobgoblins that are preventing these large language models from being installed in many corporations around the world.

因此，全模式資料攝取，我們已經解決了。身份，我們已經確定了。存取控制，我們已經解決了。因此，我們在公司成立前 15 年所做的工作與生成式人工智慧的這些新創新相結合，使我們能夠解決所有阻止這些大型語言模型在世界各地的許多公司中安裝的問題。

Thank you.

謝謝。

Pat Walravens, JMP securities.

帕特·瓦爾拉文斯 (Pat Walravens)，JMP 證券公司。

Great, thank you and congratulations, it's really impressive. So, I mean, 50% of bookings, Tom, from federal, defense, and aerospace, if you could drill into that more and talk about what you see for the pipeline for that vertical for this coming year, that would be great.

太棒了，謝謝你，恭喜你，這真的很令人印象深刻。所以，我的意思是，湯姆，50% 的預訂來自聯邦、國防和航空航天，如果你能深入研究這一點，並談談你對來年該垂直領域的管道的看法，那就太好了。

Federal looks like a growth engine, Pat. Business is good and we've had a lot of inroads in the Air Force, the Navy, the Intelligence Community, and we are investing in the Federal business in a big way. The Federal community is investing in AI in a big way. This is kind of an existential issue where a little bit of war going on with AI against the United States and China and we're on the side of the good guys and we're on the team. So I'm not sure how big it is, but it's big.

聯邦看起來像是成長引擎，帕特。生意很好，我們在空軍、海軍、情報界取得了巨大進展，而且我們正在大力投資聯邦業務。聯邦社會正在大力投資人工智慧。這是一個關乎生存的問題，人工智慧正在與美國和中國發生一些戰爭，我們站在好人這邊，我們是團隊中的一員。所以我不確定它有多大，但它很大。

Yeah, and as a follow-up on that, so your partnerships with AWS, Microsoft, Google, Booz Allen, I guess what's bearing the most fruit in federal?

是的，作為後續行動，您與 AWS、微軟、谷歌、博思艾倫的合作，我想什麼在聯邦取得了最大的成果？

Well, AWS is probably, they're the company by far that has the most tentacles into Federal and I would say probably 11 out of 12 of our applications are running on the AWS GovCloud. And so in our relationships with the Federal, AWS Federal group and the International Federal Group that deals with the allies, NATO, Five Eyes, what have you, is very deep and rich. And as it relates to hyperscalers, that's where we're seeing the most action. And AWS it just is the dominant-installed platform.

嗯，AWS 可能是，他們是迄今為止對聯邦觸角最多的公司，我想說，我們 12 個應用程式中可能有 11 個在 AWS GovCloud 上運行。因此，在我們與聯邦、AWS聯邦集團和與盟國、北約、五眼聯盟等打交道的國際聯邦集團的關係中，關係非常深厚和豐富。由於它與超大規模企業有關，因此我們看到了最多的行動。 AWS 是主導的安裝平台。

All right, great. Thanks. And congratulations again.

好吧，太好了。謝謝。再次恭喜。

Thank you.

謝謝。

Sanjit Singh, Morgan Stanley.

桑吉特辛格，摩根士丹利。

Yeah, thank you for taking the questions, congrats on a strong close to the year. Tom, I'd love to get a, like an example, your favorite example of one of the customers coming out of the gen AI C3 pilot program and the role that C3 AI did in terms of getting them into production, I think that's a clear debate in the industry about are a lot of these projects experimental and can they actually get into production? It seems like you guys are getting your customers into production. And so I don't know if there's one of the 58 pilots that you signed this year that sort of catches your eye and provides like an example, or a model, if you will, of how C3 AI gets its customers into production for Gen AI use cases.

是的，感謝您提出問題，恭喜您今年圓滿成功。湯姆，我很想舉一個例子，你最喜歡的一個例子，其中一位客戶來自 gen AI C3 試點計劃，以及 C3 AI 在將它們投入生產方面所發揮的作用，我認為這是一個業界存在明確的爭論，這些項目中的許多項目是否處於實驗階段，是否能夠真正投入生產？看起來你們正在讓你們的客戶投入生產。因此，我不知道您今年簽署的 58 個試點項目中是否有一個能引起您的注意，並提供一個示例或模型（如果您願意的話）來說明 C3 AI 如何讓其客戶投入 Gen 的生產中。智能用例。

Well, Sanjit, it's very interesting is they're incredibly diverse. One example would be there's a large law firm that we all know that's very active in taking companies public, and what we did for them is that we ingested the corpus of sec.gov egger, okay, into an enterprise learning model. This would be all the S1s, all the 10-Ks, all the 10-Qs that ever been published. Now, what they're going to use this for, their first use is when they're taking the next company public, whoever that might be, okay, and they want to generate type in the name, they type in the financials, okay, they hit the carriage return and generate the first draft of the S1 and it does it in an hour rather than two weeks.

嗯，Sanjit，非常有趣的是它們非常多樣化。一個例子是，我們都知道有一家大型律師事務所非常積極地推動公司上市，我們為他們所做的就是將 sec.gov Egger 的語料庫納入企業學習模型中。這將是所有已發布的 S1、所有 10-K、所有 10-Q。現在，他們要使用這個的目的，他們的第一次用途是當他們讓下一家公司上市時，無論是誰，好吧，他們想要在名稱中生成類型，他們輸入財務數據，好吧，他們按下回車鍵並產生S1 的初稿，並且在一小時內完成，而不是兩週。

And this would be applicable to your business, so I can have it live. My offer to you is I'll have the system live and in production for $0.25 million dollars in 12 weeks. So give me a call, send me a check and we'll have it live. And another one is let's look at the application that we have in place for this application, it's called Panda; we've talked about this a lot.

這將適用於您的業務，因此我可以將其發布。我向您提出的條件是，我將在 12 週內以 25 萬美元的價格讓該系統上線並投入生產。所以給我打電話，給我寄一張支票，我們就會即時發布。另一個是讓我們看看我們為此應用程式準備的應用程序，它稱為 Panda；我們已經討論過很多次了。

This is where we've loaded all the underlying information and telemetry associated with 22 weapons systems in the United States Air Force; F-15, F-16, F-18, F-35, KC-135, F-22, et cetera. And we use this for try to identify system and subsystem failure before it happens, predictive maintenance. And so we can identify that their auxiliary power unit or the flap actuator or the igniter and the afterburner is going to fail in the next 50 or 100 flight hours. You fix it that night in Stuttgart or Munich and the plane doesn't fail.

我們在這裡加載了與美國空軍 22 個武器系統相關的所有基礎資訊和遙測數據； F-15、F-16、F-18、F-35、KC-135、F-22 等。我們用它來嘗試在系統和子系統故障發生之前識別它，即預測性維護。因此我們可以確定他們的輔助動力裝置或襟翼執行器或點火器和加力燃燒器將在接下來的 50 或 100 飛行小時內發生故障。當晚你在斯圖加特或慕尼黑修好它，飛機就不會故障。

Net-net 25% increase in aircraft availability at the scale of the United States Air Force. Now, you can imagine that the human interface for this is pretty tactical, right? And it's designed for use by highly technical maintenance people who manage sustainment and logistics at the scale of the United States Air Force, so it's as technical as you get, like a manufacturing application or other applications that you've seen. So here, where does generative AI play here? And I think this is probably the biggest impact of Generative AI, actually, it could be used to fundamentally change the nature of the human computer interface for enterprise applications.

美國空軍規模的飛機可用性淨增加 25%。現在，您可以想像這個人機介面非常具有戰術性，對嗎？它專為管理美國空軍規模的保障和後勤的高技術維護人員而設計，因此它具有盡可能高的技術性，就像製造應用程式或您見過的其他應用程式一樣。那麼，生成式人工智慧在這裡發揮什麼作用呢？我認為這可能是生成式人工智慧的最大影響，實際上，它可以從根本上改變企業應用程式人機介面的性質。

So when we put a Generative AI front-in on that, it looks like a mosaic browser, where you can ask any question in English or whatever, or 131 languages, by the way, and it gives you the answer. For example, now at the level of the Secretary of the Air Force or the Secretary of Defense or the Chairman of the Joint Chiefs, he or she might ask, what are my readiness levels from F-35 squadrons in Central Europe? And you have to grind through a lot of data, but a minute later, it generates a map of Europe, tells you each of your F-35 squadrons are and what their readiness levels are. Not only that, you can see ground troop.

因此，當我們將生成式 AI 置於前端時，它看起來就像一個馬賽克瀏覽器，您可以用英語或其他語言提出任何問題，順便說一句，或者 131 種語言，它會給您答案。例如，現在在空軍部長、國防部長或參謀長聯席會議主席級別，他或她可能會問，我在中歐的 F-35 中隊的戰備水平是多少？你必須仔細研究大量數據，但一分鐘後，它會產生一張歐洲地圖，告訴你每個 F-35 中隊的情況以及它們的戰備水準。不僅如此，你還可以看到地面部隊。

You can see right where the answer came from, and then you can continue to drill down and you get the answer right now. And today, it takes days to weeks in the Pentagon to get answers like that. Now, what's the impact of that? We can transfer the application from the utilization of the application from thousands of highly technical users to tens of thousands of users.

您可以清楚地看到答案的來源，然後您可以繼續深入研究，立即得到答案。如今，五角大廈需要幾天到幾週的時間才能得到這樣的答案。現在，這有什麼影響？我們可以將應用程式的使用從數千個高技術用戶轉移到數萬個用戶。

I mean, every pilot on the flight line knows how to use this. The Chairman of the Joint Chiefs knows how to use it. The Chairman of the Joint Chief's mother knows how to use it. Okay? So basically, it's a mosaic. You know it is the Google user interface.

我的意思是，航線上的每個飛行員都知道如何使用它。參謀長聯席會議主席知道如何使用它。參謀長聯席會議主席的母親知道如何使用它。好的？所以基本上，它是一個馬賽克。你知道這是Google使用者介面。

I know it as mosaic, but everybody knows how to use it. So those are the types of applications that we're seeing in Generative AI, and it's just staggering the diversity that we're seeing in the use cases. There's one of our very large customers has basically put it has 68,000 employees around the world, has all their HR systems in ServiceNow and Workday. So we put Generative AI on top of that so that any one of their 68,000 employees in God knows how many countries probably, order of 30, 40, 50, 60, 70 countries, and it may be Dubai, Qatar, Germany or Houston can ask any question about any of their HR policies, vacation days, insurance, what's in plan, what's out of plan, what are our holidays in, name the country.

我知道它是馬賽克，但每個人都知道如何使用它。這些就是我們在生成人工智慧中看到的應用程式類型，而且我們在用例中看到的多樣性令人震驚。我們的一個非常大的客戶基本上說它在全球擁有 68,000 名員工，所有的 HR 系統都在 ServiceNow 和 Workday 中。因此，我們將生成式人工智慧置於其之上，以便天知道他們的68,000 名員工中的任何一個可能有多少個國家，依次為30、40、50、60、70 個國家，可能是杜拜、卡達、德國或休士頓。

In some place, it's Ramadan, and the other place it's Rajasthan. But, what are my holidays? And so we're seeing it as a front-end to other enterprise applications like Workday, like ServiceNow. And those are three completely different use cases. But those would be examples.

有些地方是齋月，有些地方是拉賈斯坦邦。但是，我的假期是什麼？因此，我們將其視為其他企業應用程式（例如 Workday、ServiceNow）的前端。這是三個完全不同的用例。但這些只是例子。

And our offer is, we'll bring the application live in 12 weeks for $0.25 million. So if any of you need it, you all know via my email, okay. And we'll be happy to do it in your organization.

我們的報價是，我們將在 12 週內以 25 萬美元的價格推出該應用程式。所以如果你們有人需要的話，你們都可以透過我的電子郵件知道，好嗎？我們很樂意在您的組織中做到這一點。

No, that's great. The breadth of use cases is super compelling. I had one follow-up for Hitesh. As we're coming up on almost two years now on the transition to consumption and you guys are seeing accelerating subscription growth of 41% with a really, really nice number this quarter, what percent of that subscription revenue is now consumption? If you can sort of give us a sense. And is that what's driving that re-acceleration in revenue growth? Thank you so much.

不，那太好了。用例的廣度非常引人注目。我對希特什進行了一項後續行動。我們向消費轉型已經快兩年了，你們看到訂閱成長加速了 41%，本季的數字非常非常好，那麼現在消費佔訂閱收入的百分比是多少？如果你能給我們一個感覺。這就是推動營收重新加速成長的原因嗎？太感謝了。

Yeah, Sanjit, we are still in early stages of our new business model. We haven't disclosed our consumption revenue separately before, but that is something which we continue to see a ramp in and it will be more meaningful in the future.

是的，Sanjit，我們仍處於新業務模式的早期階段。我們之前沒有單獨披露過我們的消費收入，但這是我們繼續看到的成長，並且在未來會更有意義。

Kingsley Crane, Canaccord Genuity.

金斯利起重機，Canaccord Genuity。

Hi, thanks for taking the question and congrats on the traction, it's encouraging to hear. As we think about how some of the customer engagement metrics will translate to revenue growth, where would the dollar or that incremental dollar of investment be most impactful? Is it in for deployed sales engineers? Is it in partner sales motion? Are you capacity constrained on the application development side? Just want to get a little bit more granular on the investment profile.

您好，感謝您提出問題並祝賀您的關注，聽到這個消息真是令人鼓舞。當我們思考一些客戶參與度指標將如何轉化為收入成長時，美元或增量投資在哪裡最有影響力？適合部署的銷售工程師嗎？是在合作夥伴銷售動議中嗎？您在應用程式開發方面的能力是否受到限制？只是想更詳細地了解投資概況。

Good question, Kingsley. I think as it relates to the idea of a land grab and market share, which we plan on doing, I would say the constraints that we're certainly not constrained by the market, okay? We're absolutely not constrained by competitive dynamics, okay? We're going to be constrained by sales capacity and service capacity to bring these pilots live. So that's the constraint, and I think that's where we would invest, okay, in terms of to get the biggest impact for the next dollar. Great question.

好問題，金斯利。我認為，由於這與我們計劃做的搶佔土地和市場份額的想法有關，我想說的是，我們當然不會受到市場的限制，好嗎？我們絕對不受競爭動態的限制，好嗎？我們將受到銷售能力和服務能力的限制來實現這些試點。這就是限制，我認為這就是我們要投資的地方，好吧，為了讓下一美元獲得最大的影響力。很好的問題。

Okay, perfect. Thanks for the clarity. And Hitesh, just on the gross margins, understand that we continue to invest, and there's a mix of pilots in there. You did improve in the quarter on the subscription side, I mean, should we expect that we've already troughed, or is this still sort of we're feeling it out on a quarter-to-quarter basis?

好的，完美。感謝您的澄清。 Hitesh 就毛利率而言，知道我們會繼續投資，並且有各種各樣的試點。您在本季度的訂閱方面確實有所改善，我的意思是，我們是否應該期望我們已經陷入低谷，或者這仍然是我們在每個季度的基礎上感受到的？

Yeah. You should expect our gross margins to decline from where they were in Q4 at 70%, as we plan to significantly increase the number of pilots and make additional investments.

是的。您應該預期我們的毛利率將從第四季的 70% 下降，因為我們計劃大幅增加試點數量並進行額外投資。

By the way, - my colleague, Amit, has noted an error in my comments, okay, where when I gave guidance for revenue for Q1, I misspoke. The guidance for revenue for Q1 is $84 million to $89 million in Q1. So I made a mistake. I said $84 million to $90 million, and that is an error. It's $84 million to $89 million. So I'm falling on my sword and correcting the wreckage. Next question.

順便說一句，我的同事阿米特注意到我的評論中有一個錯誤，好吧，當我給出第一季收入指導時，我說錯了。第一季營收指引為 8,400 萬至 8,900 萬美元。所以我犯了一個錯誤。我說的是 8400 萬到 9000 萬美元，這是一個錯誤。售價 8,400 萬至 8,900 萬美元。所以我用我的劍倒下並糾正殘骸。下一個問題。

Arvind Ramnani, Piper Sandler.

阿爾文德·拉姆納尼，派珀·桑德勒。

Hi. Thanks for taking my question. I wanted to ask about -- like an incredibly high number of inquiries for your product. Do you think that could drive, like, further upside on the revenue side in the next year or two or some of those inquiries are sort of less qualified and you think your guidance is kind of more realistic?

你好。感謝您提出我的問題。我想詢問有關您產品的大量詢問。您認為這是否會在未來一兩年推動收入方面進一步上漲，或者其中一些詢問的資格不太合格，而您認為您的指導更為現實？

You're talking about guidance beyond fiscal year '25. I don't have any comment, Arvind, on that. Right now, we're being overwhelmed by the numbers. We are sorting through the numbers.

您談論的是 25 財年之後的指導。 Arvind，我對此沒有任何評論。現在，我們被這些數字壓垮了。我們正在對數字進行排序。

We're actually using Generative AI to qualify these leads with something that sometime I'll show you. That's pretty cool. C3 Generative marketing. But it's too early to tell, and I'm not prepared to give you guidance for fiscal year '26.

我們實際上正在使用生成式人工智慧來確定這些潛在客戶的資格，有時我會向您展示。太酷了。 C3 生成行銷。但現在下結論還為時過早，我不准備為您提供 26 財年的指導。

Yeah, yeah. But what I'm trying to understand is with this incredible amount of kind of interest you're seeing in the product, how should we think about that impacting your income statement, revenue growth, or your margins? Because it seems like there's languages when you're kind of staggering, just like 50,000 inquiries. I'm just trying to qualify to take some of this commentary and can mess it up to what does that mean for either growth or for margins?

是啊是啊。但我想了解的是，隨著您對產品產生如此令人難以置信的興趣，我們應該如何看待這對您的損益表、收入成長或利潤的影響？因為當你有點令人震驚時，似乎有語言存在，就像 50,000 個查詢一樣。我只是想獲得一些評論的資格，並可能會搞亂這對成長或利潤率意味著什麼？

It means that we're facing a staggeringly large addressable market, okay? It means that the game that we're playing is to establish a market leadership position in this market, okay? I don't know what the stock trades for today, $20 or $30 or whatever it is, okay? But let's say that we succeed like we did at Oracle, okay, like we did at Seibel, and we established a market leadership position in Enterprise AI applications, I assure you, this is not a stock trading at $20,$30, okay?

這意味著我們面臨著一個巨大的潛在市場，好嗎？這意味著我們正在玩的遊戲是在這個市場上建立市場領導地位，好嗎？我不知道該股票今天的交易價格是 20 美元還是 30 美元，或者隨便什麼，好嗎？但是，假設我們像在Oracle 那樣取得了成功，就像我們在Seibel 所做的那樣，並且我們在企業人工智慧應用程式中建立了市場領導地位，我向您保證，這不是一支以20 美元、 30 美元交易的股票，好嗎？

Okay, it's multiples of that, okay? Maybe an order of magnitude larger than that. Maybe we fail. Maybe we fail and we end up number two or number three, okay? Do some math on that. I know it doesn't work. There's no formula for this in your spreadsheet.

好吧，是這個數的倍數，好嗎？也許比這個大一個數量級。也許我們會失敗。也許我們失敗了，最後變成第二名或第三名，好嗎？對此做一些數學計算。我知道這行不通。您的電子表格中沒有對應的公式。

But I don't think a spreadsheet is the right way to look at the opportunity. This is a large addressable market. We have first mover advantage. We have a strong technology foundation, and we are going for it, and that's. The way to model the business honestly, I would look at what we say revenue is going to be, because what we say revenue is going to be for the last 14 quarters has been pretty accurate. I think that's the best leading indicator you can have.

但我認為電子表格不是看待機會的正確方法。這是一個巨大的潛在市場。我們有先發優勢。我們擁有強大的技術基礎，我們正在為此努力，僅此而已。誠實地對業務進行建模的方法是，我會看看我們所說的收入將會是多少，因為我們所說的過去 14 個季度的收入是相當準確的。我認為這是您可以擁有的最好的領先指標。

Terrific. And then, if you can maybe just double click on margins, right? There's some margin degradation by kind of next year because of the number of pilots. How does that work? Like, when you do pilots, you charge less or do the professional services go up more? Like, what drives lower margins by making a choice? (multiple speakers)

了不起。然後，如果您可以雙擊邊距，對嗎？由於飛行員數量的原因，明年的利潤率會下降。這是如何運作的？例如，當您進行試點時，您收取的費用會更少，還是專業服務的費用會更高？例如，是什麼導致了做出選擇後利潤率下降？ （多個發言者）

Good question. What drives lower? Essentially, our market offering today is for an Enterprise application, let's say Stochastic optimization of supply chain, let's say demand forecasting for a large agribusiness or predictive maintenance for a large manufacturer. We'll bring that application live at a multi-billion dollar corporation, basically, in one of their facilities for bring it live. Not a proof of concept, live, okay, in six months for $0.5 million, okay?

好問題。是什麼導致價格走低？本質上，我們今天的市場產品是針對企業應用程式的，例如供應鏈的隨機最佳化，例如大型農業企業的需求預測或大型製造商的預測性維護。我們將在一家價值數十億美元的公司中啟用該應用程序，基本上是在他們的一個設施中啟用該應用程式。不是概念驗證，而是在六個月內投入 50 萬美元，好嗎？

And by the way, the alternative is to do this with Accenture, Deloitte, who'll charge them $100 million to do it or $30 million to do it in two years. We'll have it live in six months. Okay, my application, as I mentioned in generative AI, is to have the application live in 12 weeks for $0.25 million. Now, we will do, honestly, Arvind, whatever it takes to make that customer live, okay.

順便說一句，另一個選擇是與埃森哲、德勤合作，他們將向他們收取 1 億美元的費用，或在兩年內收取 3000 萬美元的費用。六個月後我們就會讓它上線。好的，正如我在生成式 AI 中提到的，我的申請是在 12 週內讓應用程式上線，費用為 25 萬美元。現在，老實說，Arvind，我們會盡一切努力讓客戶活下去，好吧。

And do I really look at what the profitability level of every one of these pilots is? I do not. Okay. And if I'm looking with a Fortune 50 company about bringing their first enterprise AI application live, I'm going to invest whatever it takes, even at a loss if necessary, to make sure the customer is successful. So that's what drives the margins degradation. Are these, in aggregate, profitable? I'm sure they are, okay, and I'm sure they're enormously profitable. But at any given one, I mean, we are not going to fail and we have the resources to back that up.

我是否真正關注過每一個試點計畫的獲利水準？我不。好的。如果我正在與財富 50 強公司合作，推出他們的第一個企業人工智慧應用程序，我將不惜一切代價進行投資，甚至在必要時虧損，以確保客戶取得成功。這就是導致利潤率下降的原因。這些總的來說有利可圖嗎？我確信他們是，好吧，而且我確信他們利潤豐厚。但我的意思是，在任何特定的情況下，我們都不會失敗，而且我們有資源來支持這一點。

(multiple speakers) Thank you very much.

（多名發言者）非常感謝。

That's where the margin degradation is coming from. And I realize it's hard to model, but it's just we know that's who we are and that's what we are.

這就是利潤率下降的原因。我意識到建模很難，但我們知道這就是我們，這就是我們。

Yeah, terrific. Thank you so much, really appreciate it.

是啊，太棒了。非常感謝，真的很感激。

Mike Cikos, Needham & Co.

麥克‧西科斯 (Mike Cikos)，李約瑟公司

Hey, guys, this is Matt Calitri on for Mike Cikos over at Needham. Thanks for taking our questions. I wanted to ask how have newly converted customers ramp consumption versus customers who adopted the consumption model in previous quarters? Are you seeing consistency across cohorts?

嘿，夥計們，我是馬特·卡利特里 (Matt Calitri)，在尼達姆 (Needham) 替補邁克·西科斯 (Mike Cikos)。感謝您回答我們的問題。我想問的是，與前幾季採用消費模式的顧客相比，新轉變的顧客如何增加消費？您是否看到不同群體之間的一致性？

Yeah, I'm not sure I understand the question. I think we provided very specific guidance on that last quarter. Okay, Matt, okay, in the supplemental last quarter, we provided very specific guidance on what we're seeing, okay, in revenue consumption in basically the first quarter they go to production to the tenth quarter they go production. And if I am mistaken, this is from memory, but I think the first quarter they go production, they consume about 300,000 or 400,000 GPU hours.

是的，我不確定我是否理解這個問題。我認為我們在上個季度提供了非常具體的指導。好吧，馬特，好吧，在上個季度的補充中，我們就我們所看到的收入消耗提供了非常具體的指導，基本上是從第一季開始生產到第十季度開始生產。如果我沒記錯的話，這是根據記憶，但我認為他們投入生產的第一季度，他們消耗了大約 300,000 或 400,000 個 GPU 小時。

And by the time you get to the tenth quarter, I think it's 1.4 million. Yeah. What is it? How's my memory? I wish the initial assumptions, actual usage. First quarter they go production, 370,000, and it ramps up to 1.3 million in the tenth quarter. And -- so, if you look at our supplemental from last quarter, it is in this quarter too. Last quarter. It's provided there in great detail and that these are empirically accurate data.

到第十個季度時，我認為這個數字已經達到 140 萬。是的。它是什麼？我的記憶力怎麼樣？我希望初步的假設，實際的使用情況。第一季產量為 37 萬輛，第十季產量增加至 130 萬輛。而且 - 因此，如果您查看我們上季度的補充資料，您會發現本季也是如此。上個季度。那裡提供了非常詳細的信息，並且這些都是經驗上準確的數據。

Got it. Okay, I'll take a look there. Thank you. And then how are sales cycles compared to a year ago? Are customers demonstrated in a positive as they identify benchmarks and TCO to secure budget, or has it been pretty static?

知道了。好的，我去那裡看看。謝謝。那麼銷售週期與一年前相比如何？客戶在確定基準和 TCO 來確保預算時是否表現出積極的態度，還是相當靜態？

Did we talk about sales cycle this quarter?

我們是否討論過本季的銷售週期？

No, not this quarter. Last quarter we --.

不，不是這個季度。上個季度我們——。

Last quarter we said it was what?

上個季度我們說的是什麼？

3.5 months.

3.5個月。

3.5 months. I don't have the hard data before me, Matt, but I don't think it's changed appreciably.

3.5個月。馬特，我面前沒有確鑿的數據，但我認為它沒有明顯的變化。

All right, appreciate it.

好吧，欣賞一下。

Pinjalim Bora, JPMorgan.

平賈林·博拉，摩根大通。

Great, thanks for taking the question. This is Jaiden Patel on for Pinjalim Bora at JPMorgan. Just a quick one on our end. Last quarter you had mentioned that you expected positive free cash flow for the fiscal year '25. Just wanted to get any update on that commentary. If there's anything more this quarter. Thanks.

太好了，感謝您提出問題。我是摩根大通的 Pinjalim Bora 的 Jaiden Patel。我們這邊只是簡單介紹一下。上個季度您曾提到您預計 25 財年的自由現金流為正。只是想了解該評論的最新情況。如果這個季度還有什麼事情的話。謝謝。

As we have the business plan right now, we are expecting positive free cash flow for fiscal year '25.

由於我們現在有業務計劃，我們預計 25 財年將出現正的自由現金流。

Great, thanks.

萬分感謝。

Thank you.

謝謝。

Thank you. I would now like to turn the call back over to Mr. Siebel for any closing remarks.

謝謝。我現在想將電話轉回給西貝爾先生，請他發表結束語。

Thanks, everybody, for your time. Appreciate your continued attention. And stay tuned. I think we're just getting started here. So next year is looking good and we look forward to communicating with you and keep you posted on what's going on. We appreciate your interest and the courtesy of you following us. So we wish you all a great day and thank you for your time.

謝謝大家抽出時間。感謝您的持續關注。請繼續關注。我想我們才剛開始。因此，明年看起來不錯，我們期待與您溝通，讓您隨時了解最新情況。我們感謝您的關注以及關注我們的禮貌。祝大家有個愉快的一天，感謝您抽出寶貴的時間。

This concludes today's program. Thank you all for participating. You may now disconnect.

今天的節目到此結束。感謝大家的參與。您現在可以斷開連線。