數據狗 (DDOG) 2025 Q3 法說會逐字稿

Good day, and thank you for standing by. Welcome to the third quarter 2025 Datadog earnings conference call. (Operator Instructions) Please be advised that today's conference is being recorded.

您好，感謝您的耐心等待。歡迎參加 Datadog 2025 年第三季財報電話會議。（操作人員指示）請注意，今天的會議正在錄音。

I would now like to hand the conference over to your first speaker today, Yuka Broderick, Senior Vice President of Investor Relations. Please go ahead.

現在，我謹將會議交給今天的第一位發言人，投資者關係高級副總裁尤卡·布羅德里克。請繼續。

Thank you, Martin. Good morning and thank you for joining us to review Datadog's third quarter 2025 financial results, which we announced in our press release issued this morning. Joining me on the call today are Olivier Pomel, Datadog's Co-Founder and CEO; and David Obstler, Datadog's CFO.

謝謝你，馬丁。早安，感謝各位參加本次Datadog 2025年第三季財務業績回顧會議，該業績已於今天上午發布的新聞稿中公佈。今天和我一起參加電話會議的有 Datadog 的共同創辦人兼執行長 Olivier Pomel，以及 Datadog 的財務長 David Obstler。

During this call, we will make forward-looking statements, including statements related to our future financial performance, our outlook for the fourth quarter and the fiscal year 2025 and related notes and assumptions, our gross margins and operating margins, our product capabilities and our ability to capitalize on market opportunities.

在本次電話會議中，我們將發表前瞻性聲明，包括與我們未來財務業績、第四季度和 2025 財年的展望及相關說明和假設、毛利率和營業利潤率、產品能力以及我們把握市場機會的能力相關的聲明。

The words anticipate, believe, continue, estimate, expect, intend, will and similar expressions are intended to identify forward-looking statements or similar indications of future expectations. These statements reflect our views only as of today and are subject to a variety of risks and uncertainties that could cause actual results to differ materially.

「預期」、「相信」、「繼續」、「估計」、「期望」、「打算」、「將」等詞語以及類似表達旨在識別前瞻性陳述或對未來預期的類似指示。這些聲明僅反映我們截至目前為止的觀點，並受多種風險和不確定因素的影響，實際結果可能與這些聲明有重大差異。

For a discussion of the material risks and other important factors that could affect our actual results, please refer to our Form 10-Q for the quarter ended June 30, 2025. Additional information will be made available in our upcoming Form 10-Q for the fiscal quarter ended September 30, 2025, and other filings with the SEC.

有關可能影響我們實際業績的重大風險和其他重要因素的討論，請參閱我們截至 2025 年 6 月 30 日的季度 10-Q 表格。更多資訊將在我們即將提交的截至 2025 年 9 月 30 日的季度財務報告（10-Q 表格）以及向美國證券交易委員會提交的其他文件中公佈。

This information is also available on the Investor Relations section of our website, along with a replay of this call. We will discuss non-GAAP financial measures, which are reconciled to their most directly comparable GAAP financial measures in the tables in our earnings release, which is available at investors.datadoghq.com.

這些資訊以及本次電話會議的錄音回放也可在本網站的投資者關係版塊找到。我們將討論非GAAP財務指標，這些指標已在我們的收益報告中的表格中與其最直接可比較的GAAP財務指標進行了核對，該報告可在 investors.datadoghq.com 上查閱。

With that, I'd like to turn the call over to Olivier.

接下來，我想把電話交給奧利維爾。

Thanks, Yuka, and thank all of you for joining us this morning to go through our results for Q3. Let me begin with this quarter's business drivers. We have seen broad-based positive trends in the demand environment with an ongoing strength of cloud migration and digital transformation. Against this backdrop, we executed a very strong Q3 both in new bookings and usage growth of existing customers.

謝謝 Yuka，也感謝各位今天早上和我們一起查看第三季業績報告。首先，我想談談本季的業務驅動因素。我們看到需求環境呈現全面正面的趨勢，雲端遷移和數位轉型持續強勁。在此背景下，我們在第三季度取得了非常強勁的業績，無論是新訂單量還是現有客戶的使用量成長方面都表現突出。

As a notable inflection, we saw acceleration of year-over-year revenue growth across our non-AI customers. And the sequential usage growth for non-AI existing customers was the highest we have seen going back two quarters. This growth was broad-based as our customers are adopting more products and getting more value from the Datadog platform.

值得注意的是，我們的非人工智慧客戶的營收年增率加快。非人工智慧現有客戶的連續使用量成長是近兩個季度以來最高的。這種成長是普遍的，因為我們的客戶正在採用更多產品，並從 Datadog 平台獲得更多價值。

We also experienced strong revenue growth for our AI native customers and a broadening contribution to growth among those customers. There, too, we saw an acceleration of growth in our AI cohort in Q3 when excluding our largest customer.

我們的AI原生客戶也實現了強勁的營收成長，對這些客戶的成長貢獻也不斷擴大。同樣，在排除我們最大的客戶後，我們在第三季也看到了人工智慧用戶群的成長加速。

Looking at new business. Contribution from new customers increased in Q3 in both the amount of new customer bookings as well as the revenue contribution from new customers. And as usual, churn has remained low with gross revenue retention stable in the mid- to high 90s, highlighting the mission-critical nature of our platform for our customers.

尋找新的商機。第三季度，新客戶的貢獻增加，無論是新客戶的預訂量或是新客戶帶來的收入貢獻。與往常一樣，客戶流失率一直很低，總收入留存率穩定在 90% 以上，凸顯了我們平台對客戶的關鍵性。

Regarding our Q3 financial performance and key metrics. Revenue was $886 million, an increase of 28% year-over-year and above the high end of our guidance range. We ended Q3 with about 32,000 customers up from about 29,200 a year ago. We also ended with about 4,060 customers with an ARR of $100,000 more, up from about 3,490 a year ago. These customers generated about 89% of our ARR. And we generated free cash flow of $214 million with a free cash flow margin of 24%.

關於我們第三季的財務表現和關鍵指標。營收為 8.86 億美元，年增 28%，高於我們預期範圍的上限。第三季末，我們的客戶數量約為 32,000 人，高於一年前的約 29,200 人。我們最終擁有約 4,060 位客戶，其年度經常性收入 (ARR) 增加了 10 萬美元，而一年前這一數字約為 3,490 位。這些客戶貢獻了我們約 89% 的年度經常性收入。我們創造了 2.14 億美元的自由現金流，自由現金流利潤率為 24%。

Turning to customer adoption. Our platform strategy continues to resonate in the market. At the end of Q3, 84% of customers were using two or more products, up from 83% a year ago. 54% of customers were using four or more products, up from 49% a year ago. 31% of our customers were using six or more products, up from 26% a year ago and 16% of our customers were using eight or products from 12% a year ago.

轉向客戶採納。我們的平台策略持續在市場上引起共鳴。第三季末，84%的客戶正在使用兩種或兩種以上產品，高於一年前的83%；54%的客戶正在使用四種或四種以上產品，高於一年前的49%；31%的客戶正在使用六種或六種以上產品，高於一年前的26%；16%的客戶正在使用八種或八種以上產品，高於一年前的12%。

Digital experience is an example of an area with our platform where our rapid piece of innovation is turning into tangible value for our customers. Our digital experience products include RUM or Real User Monitoring, to observe and improve application beginning figure here in mobile products. Synthetic, to user flows and proactively detect user facing issues and product analytics to help users connect application behavior to business impact.

數位體驗是我們平台的一個領域，在這個領域中，我們快速的創新正在轉化為客戶切實的價值。我們的數位體驗產品包括 RUM 或真實用戶監控，用於觀察和改進行動產品中的應用程式。合成的、使用者流程的、主動檢測使用者問題和產品分析，以幫助使用者將應用程式行為與業務影響聯繫起來。

Over the years, we built our product breadth and depth in this area, and that is being recognized in the marketplace. For the second year in a row, Datadog has been named the leader in the 2025 Gartner Magic Quadrant for digital experience monitoring. We are pleased that today give digital experience products together exceed $300 million in ARR. And this includes, in particular, a very fast ramp for Product Analytics which has already seen adoption by more than 1,000 customers. We also want to call out our security suite of products where we are executing and accelerating growth.

多年來，我們不斷拓展和深化該領域的產品線，這一點也得到了市場的認可。Datadog 連續第二年被評為 2025 年 Gartner 數位體驗監控魔力像限的領導者。我們很高興地宣布，今天我們的數位體驗產品總收入已超過 3 億美元。其中尤其包括產品分析功能的快速發展，目前已有超過 1,000 位客戶採用了此功能。我們也要重點介紹一下我們的安全產品套件，我們正在這些產品上推進並加速成長。

Security ARR growth was in the mid-50s as a percentage year-over-year in Q3, up from the mid-40s we mentioned last quarter. We're starting to see success in including Cloud SIEM in larger deals, and we'll get back to that in a bit in our customer examples. And we're seeing positive trends beyond Cloud SIEM, including fast uptake of good security and an increasing number of wins in cloud security. Overall, we saw year-over-year growth acceleration in each one of our security products.

第三季安全業務年度經常性收入年增率達 50% 左右，高於上一季的 40% 左右。我們開始看到將雲端 SIEM 納入大型交易中取得了成功，稍後我們將在客戶案例中再詳細介紹這一點。我們看到，除了雲端安全資訊和事件管理 (SIEM) 之外，還出現了積極的趨勢，包括安全措施的快速普及和雲端安全領域取得的成功案例越來越多。總體而言，我們所有安全產品都實現了年成長加速。

Moving on to R&D. We continue to deliver on what is a very ambitious AI road map. We are seeing high customer interest in our Bits AI agents, which we announced at our DASH conference in June. We have now onboarded thousands of customers for access, the Bits AI SRE agent. And as we prepare for general availability, we are getting very enthusiastic feedback on the time and cost savings enabled by Bits AI.

接下來進入研發階段。我們正持續推進雄心勃勃的人工智慧路線圖。我們看到客戶對我們在 6 月 DASH 大會上發布的 Bits AI 代理商表現出了濃厚的興趣。我們現在已經為數千名客戶提供了存取權限，即 Bits AI SRE 代理程式。隨著我們準備全面推出，我們收到了許多關於 Bits AI 帶來的時間和成本節省的熱烈回饋。

As RUM user recently told us, with Bits AI SRE being on call 24/7 for us, meantime resolution for our services has improved significantly. For most cases, the investigation is already taken care of well before our engineers sit down and open their laptops to assess the issue. And this is not an isolated comment. We see the potential here for our agents who radically transform observability and operations.

正如 RUM 用戶最近告訴我們的那樣，由於 Bits AI SRE 全天候為我們提供服務，我們的服務問題解決率已顯著提高。大多數情況下，在我們的工程師坐下來打開筆記型電腦評估問題之前，調查工作就已經完成。而且這並非個別評論。我們看到了我們的代理人能夠從根本上改變可觀測性和操作方式的潛力。

In LLM Observability, we recently launched LLM experiments and playgrounds for general availability, helping teams to rapidly iterate on LLM applications and AI agents. We also launched custom LLM as George evaluations for general availability, which lets customers write evaluation prompts to access application quality and safety.

在 LLM 可觀測性方面，我們最近推出了 LLM 實驗和測試平台，供大眾使用，幫助團隊快速迭代 LLM 應用程式和 AI 代理程式。我們還推出了面向公眾的客製化 LLM 作為 George 評估，讓客戶編寫評估提示來存取應用程式的品質和安全性。

As an illustration of both and adoption in the past month, the number of LLM spans customers attending Datadog has more than quadrupled. And we are seeing a lot of interest in the Datadog MCP servers. Our MCP server acts as a bridge between Datadog and AI agents, such as Codex, OpenAI, Claude Anthropic, Cursor, GitHub Copilot, Goose by Block and many more.

為了說明過去一個月來LLM和LLM的採用情況，參加Datadog的LLM跨度客戶數量增加了四倍多。我們看到大家對 Datadog MCP 伺服器非常感興趣。我們的 MCP 伺服器可作為 Datadog 和 AI 代理（例如 Codex、OpenAI、Claude Anthropic、Cursor、GitHub Copilot、Goose by Block 等）之間的橋樑。

Our previous customers are using real-time production data as a context to drive trouble shooting, root cause narrative and automation agents. One user told us, the Datadog MCP server is a great tool. You can now to get the last slide is my app and follow the spas and trace all the way to the goods have never been more hooked on Datadog. So we see MCP adoption as a great way to cement Datadog even further into our customers' workflows.

我們之前的客戶正在使用即時生產數據作為背景信息，以推動故障排除、根本原因分析和自動化代理的開發。一位用戶告訴我們，Datadog MCP 伺服器是一個很棒的工具。現在，您可以透過我的應用程式取得最後一張投影片，並追蹤水療中心，一路追蹤到商品，您從未如此迷戀 Datadog。因此，我們認為採用 MCP 是進一步鞏固 Datadog 在我們客戶工作流程中地位的絕佳方式。

Finally, we continue to see rising customer interest for next-gen AI observability with over 5,000 customers setting AI data to one or more of AI integrations. On the topic of integrations, we are very proud to now support over 1,000 integrations, which we believe is unparalleled in our space.

最後，我們看到客戶對下一代 AI 可觀測性的興趣持續增長，超過 5,000 名客戶將 AI 數據設定為一個或多個 AI 整合。關於集成方面，我們非常自豪地宣布，我們現在支援超過 1,000 種集成，我們相信這在我們的領域是無與倫比的。

By using our integration, customer called otherwise disparate data sources across editor products for deeper analysis. We can see from a customer's usage that this is a critical part of the Datadog platform. Our 32,000 customers use more than 50 integration average, while customers spending over $1 million annually with us use more than 150. And most importantly, as tech stack evolves, we continue to update and expand our integrations. So our customers can use that Datadog to deploy new technologies with confidence.

透過使用我們的集成，客戶可以呼叫編輯器產品中原本分散的資料來源進行更深入的分析。從客戶的使用情況可以看出，這是 Datadog 平台的關鍵組成部分。我們的 32,000 名客戶平均使用 50 多種整合方案，而每年在我們這裡消費超過 100 萬美元的客戶平均使用 150 多種整合方案。最重要的是，隨著技術棧的演進，我們將不斷更新和擴展我們的整合。因此，我們的客戶可以放心地使用 Datadog 來部署新技術。

Last but not least, I wanted to give a shout out to our AI research team for the amazing work they have published. Our Toto open-weight model has been one of the top-down lows and hedging space over the past few months, and that is across all categories. It is very impactful as mandate think, the high quality of this work allows us to attract world-class AI researchers and engineers.

最後，我要特別感謝我們的人工智慧研究團隊，他們發表了許多出色的研究成果。在過去的幾個月裡，我們的 Toto 公開權重模型一直是自上而下低迷和對沖領域的佼佼者，而這種情況涵蓋了所有類別。按照規定，這項工作影響非常大，高品質的工作使我們能夠吸引世界一流的人工智慧研究人員和工程師。

Now let's move on to sales and marketing. We had a number of great new logo wins in customer expansion this quarter. So I'll go through a few of them. First, we need a seven-figure annualized deal with a leading European telco, our largest ever land deal in Europe. This company's previous setup was expensive in efficient and wasn't scaling to meet their needs.

現在我們來談談銷售和行銷。本季我們在客戶拓展方面贏得了許多優秀的新logo客戶。那我將逐一介紹其中幾個。首先，我們需要與一家歐洲領先的電信公司達成一項年化七位數的交易，這將是我們在歐洲有史以來最大的土地交易。這家公司之前的架構成本高、效率低下，而且無法擴展以滿足其需求。

By using Datadog, they expect to save over $1 million annually on tool cost alone, along with millions of dollars more in reduce operation costs, lower engineering time and avoidance of the new loss. They will adopt 11 Datadog products to start, and we consolidate more than 10 commercial tools.

透過使用 Datadog，他們預計每年僅在工具成本上就能節省超過 100 萬美元，此外還能透過降低營運成本、縮短工程時間和避免新的損失節省數百萬美元。他們初期將採用 11 款 Datadog 產品，我們將整合 10 多款商業工具。

Next, we landed a seven-figure annualized deal with a leading financial risk and analytics company. The company's fragmented tooling has led to major incidents that sometimes took multiple days and hundreds of engineers to resolve. They plan to start with 11 Datadog products including OnCall, Clouds and Bits AI, will replace 14 commercial open source and hyperscale observability tools.

接下來，我們與一家領先的金融風險和分析公司達成了一項年化七位數的交易。該公司分散的工具導致發生重大事故，有時需要數天時間和數百名工程師才能解決。他們計劃首先推出 11 款 Datadog 產品，包括 OnCall、Clouds 和 Bits AI，以取代 14 款商業開源和超大規模可觀測工具。

Next, we landed a seven-figure annualized deal with a Fortune 500 technology hardware company. This is an exciting win for new -- sorry. This is an exciting win for our new go-to-market motions, targeting the largest and most sophisticated companies in the world. Datadog has been chosen as their strategy observability partner, and we are displacing commercial tools across availability, cloud team, and incident response. This customer is starting with 14 Datadog products.

接下來，我們與一家財富 500 強科技硬體公司達成了一項價值七位數的年度合約。這對新人來說是一場激動人心的勝利——抱歉。對於我們針對全球規模最大、技術最先進的公司所製定的新市場推廣策略來說，這是一場令人振奮的勝利。Datadog 已被選為他們策略可觀測性合作夥伴，我們正在可用性、雲端團隊和事件回應方面取代商業工具。該客戶最初訂購了 14 款 Datadog 產品。

Next, we signed a seven-figure annualized expansion with a Fortune 500 financial services company. This customer has pockets of silo term data, including one business unit, which minorly hosted and maintained 93 separate instances of open-source tooling.

接下來，我們與一家財富 500 強金融服務公司簽署了一份年化金額達七位數的擴張協議。該客戶擁有大量孤立的術語數據，其中一個業務部門託管並維護了 93 個獨立的開源工具實例。

With this expansion, this company will add up 15 Datadog products, including all three pillars in all of their business units. They will also replace their SIEM solution with Datadog Cloud SIEM in a seven-figure land deal for Cloud SIEM. And by bringing all their telemetry data into the Datadog platform, they expect better insights for their adoption of Bits AI agent today with Bits AI (inaudible).

透過此次擴張，該公司將新增 15 款 Datadog 產品，涵蓋其所有業務部門的三大支柱產品。他們還將用Datadog Cloud SIEM解決方案替換他們現有的SIEM解決方案，這是一筆價值七位數的Cloud SIEM交易。透過將所有遙測資料匯入 Datadog 平台，他們希望能夠更了解他們今天使用 Bits AI 代理程式的情況（聽不清楚）。

Next, we signed a seven-figure annualized expansion with a Fortune 500 heavy equipment company. With this expansion, this customer will replace its open-source log solution with Datadog log management and Flex Logs. They plan to adopt LLM Observability, and their IT team is using cloud cost management to improve cost visibility and governance.

接下來，我們與一家財富 500 強重型設備公司簽署了一份年化金額達七位數的擴張協議。透過此次擴展，該客戶將用 Datadog 日誌管理和 Flex Logs 取代其開源日誌解決方案。他們計劃採用 LLM 可觀測性，他們的 IT 團隊正在使用雲端成本管理來提高成本可見度和治理能力。

Next, we will come back a leading vertical SaaS company who is a seven-figure analyze deal. By returning to Datadog this customer benefits more alignment with open telemetry, and we'll implement the incident and reliability processes that they were able to execute on previously.

接下來，我們將分析一家領先的垂直產業SaaS公司達成的七位數交易。透過回歸 Datadog，該客戶將受益於與開放遙測技術的更緊密結合，我們將實施他們先前能夠執行的事件和可靠性流程。

Next, we signed a seven-figure expansion with a major American carmaker. This customer developing Datadog products faster than previously expected and segment support higher usage. With this expansion, they will adopt Datadog incident management and OnCall solution company-wide for a total of 5,000 users who support operational continuity across the business.

接下來，我們與一家美國大型汽車製造商簽署了一份價值數百萬美元的擴建協議。該客戶開發 Datadog 產品的速度比預期更快，並且支援更高的使用率。透過此次擴展，他們將在全公司範圍內採用 Datadog 事件管理和 OnCall 解決方案，共有 5,000 名用戶支援整個業務的營運連續性。

Finally, we signed a nine-figure annualized expansion with a leading AI company. This company has been a long-time Datadog customer and has expanded their usage of multiple products, securing better economics for a higher commitment with an early renewal.

最後，我們與一家領先的人工智慧公司簽署了一份年化數達數億美元的擴張協議。這家公司一直是 Datadog 的長期客戶，並擴大了其對多種產品的使用，並透過提前續約獲得了更高的經濟效益。

Speaking of AI customers, we continue to help native customers big and small to grow and scale their businesses. And we continue to see this group broadly in number and size with more than 500 AI companies in this group, but 100 of which are spending more than $100,000 annually with Datadog and more than 15 who are spending more than $1 million annually with us.

說到人工智慧客戶，我們將繼續幫助各種規模的原生客戶發展壯大他們的業務。我們看到，這個群體在數量和規模上仍然非常龐大，該群體中有 500 多家人工智慧公司，其中 100 家每年在 Datadog 的支出超過 10 萬美元，超過 15 家每年在我們這裡的支出超過 100 萬美元。

While we know there's a lot of attention on this cohort, we primarily see it as an indication of what's to come as companies of every size and every single industry incorporate AI into their clarifications. And that's it for another very strong quarter from our go-to-market teams, who ran our very hard at work as we have a really exciting pipeline for Q4.

雖然我們知道這個群體受到了很多關注，但我們主要將其視為未來趨勢的一個標誌，因為各種規模和各個行業的公司都會將人工智慧融入他們的工作流程中。至此，我們的市場推廣團隊迎來了一個非常強勁的季度，他們辛勤工作，因為我們在第四季度有著非常令人興奮的產品線。

Before I turn it over to David for a financial review, I want to say a few words on our longer-term market. There is no change to our overall view that digital transformation and cloud migration are long-term secular growth drivers of our business. Meanwhile, we are advancing rapidly in AI, where we are incredibly excited about our opportunities. We're building a comprehensive set of AI Observability products to help our customers tackle the higher complexity of the com with the technologies. And we are building AI into Datadog, and I spoke earlier about the excitement our customers have for our Bits AI agents.

在將報告交給大衛進行財務審查之前，我想先就我們的長期市場談幾句。我們仍然堅持認為，數位轉型和雲端遷移是我們業務長期發展的驅動力。同時，我們在人工智慧領域也取得了快速進展，我們對所面臨的機會感到無比興奮。我們正在建立一套全面的 AI 可觀測性產品，以幫助我們的客戶利用這些技術來應對日益複雜的通訊挑戰。我們正在將人工智慧融入 Datadog 中，我之前也談到過我們的客戶對我們的 Bits AI 代理的興奮之情。

The market opportunity in cloud and AI is expected to grow rapidly into the trillions of dollars and companies of every size and industry are looking to adopt AI to deliver value to their customers and drive positive business outcome. So we're moving fast to help our customers develop, deploy, and grow into the cloud and into the AI world.

雲端運算和人工智慧的市場機會預計將迅速成長至數兆美元，各種規模和行業的公司都在尋求採用人工智慧來為客戶創造價值並推動積極的業務成果。因此，我們正在快速行動，幫助我們的客戶開發、部署並發展到雲端和人工智慧領域。

With that, I will turn it over to our CFO. David?

接下來，我將把這件事交給我們的財務長。大衛？

Thanks, Olivier. To start, our Q3 revenue was $886 million, up 28% year-over-year and up 7% quarter-over-quarter. To dive into some of the drivers of our Q3 revenue growth. First, overall, we saw sequential usage growth from existing customers in Q3 that was higher than our expectations and the strongest in 12 quarters in our non-AI native customer base.

謝謝你，奧利維爾。首先，我們第三季的營收為 8.86 億美元，年增 28%，季增 7%。深入探討我們第三季營收成長的一些驅動因素。首先，總體而言，我們在第三季度看到現有客戶的使用量環比增長高於預期，並且在非人工智慧原生客戶群中達到了 12 個季度以來的最高水平。

We saw year-over-year growth acceleration broadly across our business, including in new logos and existing customers, both enterprise and SMB with customers across our spending bands, big and small, and customers in a wide variety of industries.

我們看到公司各業務都實現了同比加速成長，包括新客戶和現有客戶，涵蓋了各個消費水平的客戶，無論規模大小，也包括各行各業的客戶。

Next, we saw strong and accelerating contribution from new customers. New logo annualized bookings more than doubled year-over-year and set a new record driven by an increase in average new logo land size, particularly in enterprise. We believe we are starting to see the benefits of our growth of sales capacity. And we are seeing new logos ramping faster, contributing more to revenue growth. The portion of our year-over-year revenue growth that related to new customers was about 25% in Q3, up from 20% in Q2.

其次，我們看到新客戶的貢獻強勁且不斷加速成長。新商標年度預訂量年增超過一倍，創下新紀錄，這主要得益於新商標平均面積的增加，尤其是在企業領域。我們相信，銷售能力的成長已經開始帶來好處。我們看到新商標的推出速度更快，對營收成長的貢獻也更大。第三季度，我們年收入成長中與新客戶相關的部分約為 25%，高於第二季的 20%。

Next, our AI native customers continue to exhibit rapid growth, while more customers in this group are growing to be sizable customers. As Olivier discussed, we extended the contract of our largest AI native customer. In addition, we now have more larger AI customers, including 15 of them spending $1 million or more annually with Datadog, and about 100 spending more than $100,000 annually. Year-over-year revenue growth from our AI native customers, excluding the largest customer, again, accelerated in Q3.

其次，我們的 AI 原生客戶持續保持快速成長，同時該群體中的更多客戶正在成長為規模可觀的客戶。正如奧利維爾所說，我們延長了我們最大的原生人工智慧客戶的合約。此外，我們現在擁有更多大型人工智慧客戶，其中 15 家每年在 Datadog 的支出達到或超過 100 萬美元，約 100 家每年的支出超過 10 萬美元。除最大客戶外，我們來自 AI 原生客戶的營收年增在第三季再次加速。

In Q3, this group represented 12% of our revenue, up from 11% last quarter and about 6% in the year ago quarter. I will note that over time, we think this metric will become less relevant as AI usage in production broadens beyond this group of customers. Our year-over-year revenue growth also accelerated amongst our non-AI native customers.

第三季度，該集團占我們營收的 12%，高於上一季的 11%，也高於去年同期的 6% 左右。需要指出的是，隨著人工智慧在生產上的應用範圍擴大到這部分客戶之外，我們認為這項指標的相關性會逐漸降低。我們的非人工智慧原生客戶群的年收入成長也加速了。

In Q3, our revenue growth, excluding AI native customer group, was 20% year-over-year, accelerating from 18% year-over-year in Q2, and we have seen this trend of accelerating growth continue in October. Regarding retention metrics. Our trailing 12-month net revenue retention percentage was 120% similar to last quarter and our trailing 12-month gross revenue retention percentage remain in the mid-to-high 90s.

第三季度，不包括 AI 原生客戶群，我們的營收年增 20%，高於第二季的 18%，我們看到這種加速成長的趨勢在 10 月仍在繼續。關於留存指標。過去 12 個月的淨收入留存率為 120%，與上一季相似；過去 12 個月的總收入留存率維持在 90% 以上。

And now moving on to our financial results. Our billings were $893 million, up 30% year-over-year. Our remaining performance obligations or RPO and was $2.79 billion, up 53% year-over-year, and current RPO growth was in the low 50 percentage year-over-year. Our strong bookings contributed to this acceleration of RPO. We continue to believe that revenue is a better indication of our trends in our business and billings and RPO.

接下來我們來看財務業績。我們的營業額為 8.93 億美元，年增 30%。我們剩餘履約義務（RPO）為 27.9 億美元，年成長 53%，而目前的 RPO 年成長率約為 50%。我們強勁的預訂量促進了RPO的加速發展。我們仍然認為，收入更能反映我們業務的趨勢，而帳單和 RPO 則更能反映我們的業績。

And now let's review some of the key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release. First, gross profit in the quarter was $719 million, and our gross margin was 81.2%. This compares to a gross margin of 80.9% last quarter and 81.1% in the year ago quarter.

現在讓我們來回顧一下一些關鍵的損益表結果。除非另有說明，所有指標均為非GAAP指標。我們在獲利報告中提供了GAAP財務報表與非GAAP財務報表的調節表。首先，本季毛利為 7.19 億美元，毛利率為 81.2%。相較之下，上季毛利率為 80.9%，去年同期毛利率為 81.1%。

As previously mentioned, we continue to see the impact of our engineer’s cost-saving efforts in Q3 as they deliver on our cloud efficiency projects. Our Q3 OpEx grew 30% -- 32% excuse me, year-over-year, down from 36% last quarter. We continue to grow our investments to pursue our long-term growth opportunities, and this OpEx growth is an indication of our execution on our hiring plan. Q3 operating income was $207 million for a 23% operating margin compared to 20% last quarter and 25% in the year ago quarter.

如前所述，我們在第三季度繼續看到工程師在節省成本方面所做的努力所帶來的影響，因為他們在雲端效率專案方面取得了進展。我們第三季的營運支出年增了 30%——抱歉，是 32%，低於上一季的 36%。我們不斷增加投資，以尋求長期成長機會，而營運支出的成長顯示我們招募計畫的執行情況。第三季營業收入為 2.07 億美元，營業利潤率為 23%，而上一季為 20%，去年同期為 25%。

And now turning to our balance sheet and cash flow statements. We ended the quarter with $4.1 billion in cash, cash equivalents and marketable securities and cash flow from operations was $251 billion in the quarter. After taking into consideration capital expenditures and capitalized software, free cash flow was $214 million for a free cash flow margin of 24%.

現在我們來看看資產負債表和現金流量表。本季末，我們持有現金、現金等價物和有價證券共 41 億美元，本季經營活動產生的現金流量為 2,510 億美元。考慮到資本支出和資本化軟體，自由現金流為 2.14 億美元，自由現金流利潤率為 24%。

And now for our outlook for the fourth quarter and the fiscal year 2025. First, our guidance velocity overall remains unchanged. As a reminder, we based our guidance on trends observed in recent months and imply conservatism on these growth trends.

接下來，我們展望一下第四季和 2025 財年。首先，我們的整體導引速度保持不變。再次提醒，我們的指引是基於近幾個月觀察到的趨勢，並暗示我們對這些成長趨勢持保守態度。

So for the fourth quarter, we expect revenue to be in the range of $912 million to $916 million, which represents a 24% year-over-year growth. Non-GAAP operating income is expected to be in the range of $216 million to $220 million, which implies an operating margin of 24%.

因此，我們預計第四季度營收將在 9.12 億美元至 9.16 億美元之間，年增 24%。非GAAP營業收入預計在2.16億美元至2.2億美元之間，這意味著營業利潤率為24%。

non-GAAP net income per share is expected to be in the range of $0.54 to $0.56 per share based on approximately 367 million weighted average diluted shares outstanding. And for the full year -- fiscal year 2025, we expect revenues to be in the range of $3.386 billion to $3.390 billion, which represents 26% year-over-year growth.

根據約 3.67 億股加權平均稀釋流通股計算，預計非 GAAP 每股淨收益在 0.54 美元至 0.56 美元之間。對於整個財年（2025 財年），我們預計營收將在 33.86 億美元至 33.9 億美元之間，年增 26%。

Non-GAAP operating income is expected to be in the range of $754 million to $758 million, which implies an operating margin of 22%. And non-GAAP net income per share is expected to be in the range of $2 to $2.02 per share, based on 364 million weighted average diluted shares.

非GAAP營業收入預計在7.54億美元至7.58億美元之間，這意味著營業利潤率為22%。根據 3.64 億股加權平均稀釋股計算，預計非 GAAP 每股淨收益將在 2 美元至 2.02 美元之間。

And finally, some additional notes on our guidance. We expect net interest and other income for the fiscal year 2025 to be approximately $170 million. We continue to expect cash taxes in 2025 to be about $10 million to $20 million, and we continue to apply a 21% non-GAAP tax rate for 2025 and going forward. And finally, we expect capital expenditures and capitalized software together to be 4% of revenues in fiscal year 2025.

最後，還有幾點關於我們指導原則的補充說明。我們預計 2025 財年的淨利息和其他收入約為 1.7 億美元。我們預計 2025 年的現金稅款約為 1000 萬美元至 2000 萬美元，並且我們將繼續對 2025 年及以後適用 21% 的非 GAAP 稅率。最後，我們預期 2025 財年資本支出和資本化軟體合計將佔營收的 4%。

To summarize, we are pleased with our execution in Q3. We are well positioned to help our existing and prospective customers with their cloud migration and digital transformation journeys, including their adoption of AI. And I want to thank Datadog's worldwide for their efforts.

總而言之，我們對第三季的表現感到滿意。我們有能力幫助現有客戶和潛在客戶進行雲端遷移和數位轉型之旅，包括採用人工智慧。我還要感謝Datadog全球團隊所付出的努力。

And with that, we'll open the call for questions. Operator let's begin the Q&A.

接下來，我們將開始接受提問。操作員，我們開始問答環節。

(Operator Instructions)

（操作說明）

Kash Rangan, Goldman Sachs.

Kash Rangan，高盛集團。

Appreciate it. Congratulations on the spectacular results and the showing of sequential improvement across the board. Oliver, I had a question for you. We've talked about GPU monetization versus CPU monetization. So how closer are we to the point where you can confidently expand and get your share of the customer wallet when it comes to whether it's training workload, inferencing workload on the GPU clusters, which are becoming more prevalent and increasingly a larger part of the compute build-out in the future? That's it from me.

謝謝。恭喜你們取得了輝煌的成績，並在各方面都展現出了持續進步。奧利佛，我有個問題想問你。我們已經討論過 GPU 貨幣化與 CPU 貨幣化的差異。那麼，在訓練工作負載、GPU 叢集上的推理工作負載（這些工作負載越來越普遍，並且在未來運算建置中將佔據越來越大的比例）方面，我們距離能夠自信地擴展業務並獲得客戶錢包份額的目標還有多遠呢？我的內容就到這裡。

Yes. So we have products that are getting into the market now for GPU monitoring. But these don't generate any significant revenue yet. So all the revenues we've shared, like the acceleration, et cetera, that's not related to us capitalizing more on GPUs, that's a future opportunity.

是的。所以我們現在有一些用於GPU監控的產品正在進入市場。但這些目前還沒有產生任何顯著的收入。所以，我們分享的所有收入，例如加速等等，都與我們更多地利用 GPU 無關，那是未來的機會。

Sanjit Singh, Morgan Stanley.

桑吉特辛格，摩根士丹利。

Congrats on the acceleration in growth this quarter. Olivier, I wanted to talk about some of those enterprise trends you're seeing in sort of your non-AI cohort. What do you sort of put the improved performance in growth this quarter on?

恭喜本季成長加速。奧利維爾，我想和你談談你在非人工智慧領域觀察到的一些企業趨勢。您認為本季成長業績的提升主要歸功於什麼？

You mentioned that the sales productivity or the benefit from some of the sales investments starting to come online. Is there sort of an uplift in sort of the cloud migration trends as you're starting to see enterprise build more AI applications. I just love to get your perspective on the underlying trends in the enterprise and the mid-market business.

您提到銷售效率或一些銷售投資帶來的收益開始出現。隨著企業開始建立更多人工智慧應用程序，雲端遷移趨勢是否出現了某種程度的提升？我非常想了解您對企業和中端市場業務潛在趨勢的看法。

Yes. I said there's three points to it. One part is the demand environment is not -- is positive in general. I don't know that we see massive acceleration of cloud migration, but at least the environment is not pushing the other way. We know which happens from time to time. So that's point number one.

是的。我說，這事有三點。一方面是需求環境並非──整體而言是正面的。我不認為我們會看到雲端遷移的大規模加速，但至少環境並沒有朝著相反的方向發展。我們知道這種情況時有發生。這是第一點。

Point number two is we've been growing sales capacity quite a bit, and we've created new go-to-market motions to go after the kind of customers who were not getting before like -- we've done quite a bit of investment over the past couple of years, and we see that starting to pay off. As I said also, we feel good about the Q4 in terms of pipeline on the sales side. So it's too early to tell yet. We still have to close those deals, but we feel good about the scaling of our go-to-market.

第二點是，我們的銷售能力已經大幅提升，我們制定了新的市場進入策略，以爭取以前無法獲得的客戶——我們在過去幾年裡投入了大量資金，現在我們看到這些投資開始獲得回報。正如我之前所說，我們對第四季的銷售通路前景感到樂觀。所以現在下結論還太早。我們仍需完成這些交易，但我們對市場拓展的規模感到滿意。

And point number three is we have a number of products that we've been developing over the years. Some of them are early, some of them a little bit further along, they are really clicking. We see -- we have a lot of success with getting large surprises to adult Flex Logs, for example, we have a lot of success, some of new products such as analytics that we mentioned on the call, we're seeing some large land deals or a lot of team. So all of that is contributing to the picture you're seeing today.

第三點是，我們多年來一直在開發許多產品。有些專案進展較早，有些專案進展稍快一些，它們都非常成功。我們看到——例如，我們在成人 Flex Logs 方面取得了巨大的成功，例如，我們在電話會議上提到的一些新產品（如分析）方面取得了巨大的成功，我們看到了一些大型土地交易或很多團隊。所以所有這些因素共同造就了你今天看到的景象。

And just as a follow-up on the AI observability opportunity. When you look at some of the independent software vendors that are releasing Agentic solutions, Agentic portfolios. A number of them are including observability as part of their sort of value proposition.

順便提一下人工智慧可觀測性的機會。當你查看一些發布代理解決方案和代理產品組合的獨立軟體供應商。其中一些公司將可觀測性納入了其價值主張的一部分。

Is there any work you think Datadog has to do to sort of infiltrate that market or make sure that customers look to Datadog as that Agentic monitoring capability as some of these independent software vendors try to bundle in observability into their solutions. I was look to your perspective on that?

您認為 Datadog 需要做些什麼工作才能滲透到這個市場，或者確保客戶將 Datadog 視為代理監控功能提供商，因為一些獨立軟體供應商正試圖將可觀測性捆綁到他們的解決方案中。我想聽聽你的看法？

Yes. I mean there's absolutely no doubt to us that the customers will even want a unified platform for capability for all of this. There's two parts to that. One is, historically, everything opco software we integrate with, whether that's SaaS or think that customers on themselves also has it to a management control and observability control, but you're not going to log into 17 or indicating customers we mentioned like they use 16 integrations for the smaller customers 15th one, it's not practical to actually grow and manage that separately.

是的。我的意思是，我們絕對毫不懷疑，客戶甚至會想要一個統一的平台來實現所有這些功能。這包含兩個部分。一方面，從歷史上看，我們整合的所有營運軟體，無論是 SaaS 還是我們認為客戶本身也需要進行管理控制和可觀察性控制，但你不會登入 17 個，或者像我們提到的那樣，客戶使用 16 個整合來管理較小的客戶，而對於第 15 個整合來說，單獨發展和管理這些整合是不切實際的。

So we think all of that belongs in a central place, and that's the historical trend we've seen. We also think that you can't separate the AI parts from the non-AI parts of the business. So you're not going to look at your agents separately that you do at your database and your everything else in your stack. So all of that in the end will be attached to observability.

所以我們認為所有這些都應該放在一個中心位置，這也是我們所看到的歷史趨勢。我們也認為，不能將人工智慧部分與業務中的非人工智慧部分分開。所以你不會像查看資料庫和堆疊中的其他所有內容那樣，單獨查看你的代理。所以，這一切最終都將與可觀測性掛鉤。

Raimo Lenschow, Barclays.

雷莫·倫肖，巴克萊銀行。

Perfect. Congrats from me as well. That sounded like an amazing quarter and nice to see it coming together. The -- on the AI side, and I don't want to talk about the customer, but more the other ones, like 15 customers over 1 million. That's like a big number and 100 over 100,000.

完美的。我也要向你表示祝賀。聽起來那是一個非常棒的季度，很高興看到它朝著目標穩步前進。——在人工智慧方面，我不想談論客戶，而是想談談其他方面，例如超過 100 萬的 15 位客戶。那可真是個大數字，比十萬還多一百個。

How do we have to think about the nature of those? Is this kind of -- are that kind of especially the bigger ones of those kinds of model builders, but then even 15 is a big number. And over 100 sounds like this whole new application world that we've all been kind of waiting for starting to come together. Is that kind of what's going on there? Because it does sound quite exciting and much more broader than we thought.

我們該如何看待這些事物的本質？這種——尤其是那些大型模型製造商，但即使是 15 也是一個很大的數字。超過 100 個應用程式聽起來像是我們一直期待的全新應用世界開始融合在一起了。那裡的情況大概是這樣嗎？因為它聽起來確實很令人興奮，而且比我們想像的要廣泛得多。

It's actually fairly broad. So there is model vendors, there's models -- model that can be the line that can be video, it can be sound generation to be all of the various parts of the stack you see as independent companies. It can be -- there's quite a few companies that do that work on the coding side. So coding assistance and coders and everything in that range.

實際上範圍相當廣泛。所以有各種型號的供應商，有各種型號——型號可以是視頻生產線，可以是音頻生成，可以是堆疊中的各個部分，你會看到它們都是獨立的公司。確實有－－有很多公司從事編碼方面的工作。所以，包括程式設計協助、程式設計師以及所有相關服務。

Some of these are very new companies. Some of these are not very new companies, some of these started seven, eight years ago. And we're sort of not necessarily AI native from day one, but very quickly, that would give them the growth they see today with the people to AI.

其中一些是非常新的公司。這些公司有些並不算新，有些已經成立七、八年了。我們可能並非從一開始就是人工智慧原生企業，但很快，人工智慧的發展就讓他們獲得如今人們轉向人工智慧的趨勢。

So we see a little bit of that. We have companies that are other parts of the stack in AI on the, say, the side, the other components of the infrastructure. And we have a lot of the companies that are more purely applications filled with AI. So we have a bit of everything in there. Like it's actually fairly representative of the space.

所以我們能看到一些這樣的情況。我們還有一些公司，它們構成了人工智慧技術堆疊的其他部分，例如，基礎設施的其他組件。我們有許多公司更專注於開發純粹的人工智慧應用。所以裡面什麼都有一點。感覺它確實相當具有代表性。

Mark Murphy, JPMorgan.

馬克墨菲，摩根大通。

You had mentioned the expansion of the contract with your largest AI native customer. And I believe you said better economics for a higher commitment. Can you speak to that because I would assume a higher commitment would carry a volume-based discount. I'm just trying to understand if for some reason, if that was not the case here, what did you mean by better economics and then I have a quick follow-up.

您曾提到擴大與最大的AI原生客戶的合約。我相信你說過，更高的投入才能帶來更好的經濟效益。您能解釋一下嗎？因為我猜想更高的訂購量應該會享受大量折扣。我只是想弄清楚，如果出於某種原因，情況並非如此，那麼你所說的「更好的經濟效益」是什麼意思？然後我還有一個後續問題。

Yes. Yes. I mean, look, this is -- we're not getting to the detail of any specific customer that this is the motion is always the same. Like customers grow they commit to more, they get better prices. So you see again, talking about customers in general, you see growth of usage, drops in revenue as customers renew and get higher commit and a better price and then unit growth after that for those customers. That's the motion that we've had. We have about 30,000 customers so far.

是的。是的。我的意思是，你看，我們並沒有深入探討任何特定客戶的具體情況，但這種做法始終如一。顧客越消費越多，就能獲得越優惠的價格。所以你再次看到，就客戶而言，你會看到使用量成長，收入下降，因為客戶續約後會獲得更高的承諾和更好的價格，然後這些客戶之後會實現單位成長。這就是我們提出的動議。我們目前擁有約 3 萬名客戶。

Okay. And the -- what -- so the better economics part of it is just where it's going to be netting out like 12 months down the road? Is that what you mean?

好的。那麼——什麼——所以，更合理的經濟效益部分就在於，12 個月後它的淨收益會是多少？你的意思是這樣嗎？

Well, the bigger economics means you coming tomorrow, you get a better price. And as we -- remember, we have a usage model. So we charge people every month on what they use at the crises we agreed. So if you get better economics, and your usage is somewhat similar month to month less. But the overall backdrop of our business is increased consumption.

從更宏觀的角度來看，如果你明天來，就能享受更優惠的價格。請記住，我們有一個使用模式。因此，我們會按月向人們收取他們在危機期間使用的費用，這是我們雙方商定的。所以，如果你的經濟效益比較好，而且你的每月用量大致相同，那麼你的用量就會減少。但我們業務的整體背景是消費成長。

Okay. And then as a quick follow-up, Olivier, the acceleration that you saw in the security growth is pretty noticeable too. We recall, I think about six months ago, you had ramped up and engaged a lot more of a channel partners, which is a key ingredient, to grow in the security business. Is there a function of that? Or is there a mindset change happening out there where customers want observability to be the central point of collection so that all the security teams and the ops teams are working with the same set of metrics and logs and tracers?

好的。奧利維爾，作為後續補充，你看到的安全成長加速也相當明顯。我們記得，大概六個月前，你們加大了與通路夥伴的合作力度，這是安防業務發展的關鍵因素。它有這個功能嗎？或者，目前是否存在一種思維方式的轉變，客戶希望將可觀測性作為收集資料的中心點，以便所有安全團隊和維運團隊都能使用同一組指標、日誌和追蹤器？

Look, I think it's -- it's a number of things. Definitely, we've been investing in the channel, and that's certainly helpful to do the security business as a whole. The big win we mentioned on security that we mentioned a couple of Cloud SIEM.

你看，我認為這是──這是很多因素造成的。當然，我們一直在投資通路建設，這對整個安全業務的發展肯定是有幫助的。我們在安全方面提到的一個重大勝利是，我們提到了一些雲端安全資訊和事件管理 (SIEM) 解決方案。

This tends to be more related to product maturity. The strength of our underlying platform, especially when it comes to technology that Flex Logs, for example. And the fact also that we've been learning how to properly go to market for security, and I think we've still been clicking in a way that's very exciting.

這往往與產品成熟度有較大關係。我們底層平台的實力，尤其是在 Flex Logs 等技術方面。而且，我們一直在學習如何正確地將安全產品推向市場，我認為我們仍然以一種非常令人興奮的方式取得了成功。

Fatima Boolani, Citi.

Fatima Boolani，花旗銀行。

Olivier, I'll start with you and I have a follow-up for Dave. On the OnCall product, Oli, how do Agentic advancements in general, detract or enhance the value proposition here? And I'm very simplistically thinking about the core nature and value proposition of the OnCall product intelligently routing requests for remediation, right? So how you just broader advancements in AI help beef up and detract your ability to monetize this product? And then just a follow-up for David, please.

奧利維爾，我先問你，我還有後續問題想問戴夫。Oli，就 OnCall 產品而言，Agentic 的進步總體上會降低還是提升其價值主張？我這裡說的OnCall產品的核心性質和價值主張，其實很簡單，就是智慧地路由修復請求，對吧？那麼，人工智慧的廣泛進步究竟是增強還是削弱了你透過該產品實現盈利的能力呢？最後，請問大衛還有什麼後續問題嗎？

Well, I mean, if you zoom out, we entered the field with OnCall because we wanted to own the end-to-end incident resolution. So we want it to -- before that, we were detecting the incidence and sending the alerts. And then we were pretty much where the resolution happened after that. Customers were spending that time in that up to diagnose and understand what was going on. So we wanted to own the full cycle. And we thought that with AI, in particular, we'd have the ability to do things if we own or the whole cycle, that we couldn't do otherwise.

嗯，我的意思是，如果從更宏觀的角度來看，我們之所以選擇 OnCall，是因為我們想要掌控端到端的事件解決流程。所以我們希望它能夠——在此之前，我們一直在檢測事件並發送警報。然後，事情基本上就發展到了那個階段。顧客們花時間在診斷和了解發生了什麼事。所以我們希望掌控整個週期。我們認為，特別是藉助人工智慧，如果我們擁有整個流程，我們將能夠做到一些我們以前無法做到的事情。

So what you see right now is, I mean, these resonate with customers, they don't think the product. We've mentioned like some exciting customers with say, one with 5,000 seats for OnCall, which is very exciting. But in the future, there's many more things we can do in working on for that product.

所以你現在看到的是，我的意思是，這些能引起顧客的共鳴，他們並不認為產品本身有問題。我們提到過一些令人興奮的客戶，例如，有一家為 OnCall 提供 5000 個席位的客戶，這非常令人興奮。但未來，我們可以為該產品做更多的事情。

If we -- if we both detect incident and notify, we can do some settle things such as even predicting the incident and notify early or rerouting early or paying people before the incident actually takes place on who they can potentially fix it. So these are all things we're working on.

如果我們—如果我們都能偵測到事件並發出通知，我們可以做一些確定的事情，例如預測事件並及早通知，或及早重新路由，或在事件實際發生之前向可能解決問題的人支付費用。這些都是我們正在努力的方向。

I mean, look, if you look at the various product announcements we've made, whether that's Bits AI or the time series forecasting model we released when you assemble all that, you get to a very, very interesting picture of what we can do in the future. So we're excited about that our customer are excited by the vision there too, and that's why this product is successful.

我的意思是，你看，如果你看看我們發布的各種產品公告，無論是 Bits AI 還是我們發布的時間序列預測模型，當你把所有這些放在一起時，你就會對我們未來能夠做的事情有一個非常非常有趣的了解。所以我們很高興我們的客戶也對這個願景感到興奮，這就是這款產品成功的原因。

Appreciate that. David, on net retention rates, why aren't we necessarily seeing more upward pressure on the metric, just given the strength of expansionary bookings that you alluded to in the quarter from the installed base. And I mean I suspect it's because it's a trailing 12-month metric. But any directional color you can just share on that. And any high-level commentary on some of the non-AI native net retention rate trend behavior?

謝謝。David，關於淨留存率，考慮到你在本季度提到的來自現有用戶群的擴張性預訂的強勁勢頭，為什麼我們沒有看到該指標出現更大的上行壓力？我的意思是，我懷疑這是因為它是過去 12 個月的指標。但是任何方向性的顏色你都可以在上面分享。對於一些非人工智慧原生淨留存率的趨勢行為，您有什麼高層次的評論嗎？

Yes. You've noted it. It's a trailing 12 months, it's a number that's rounded, it has the dynamics that you might expect in that the growth of the non-AI natives has been, as we mentioned, a combination of landing and expanding at higher rates than we've seen in recent quarters. So if that continues as you go into a trailing 12-month metric, you see a directional movement.

是的。你已經記住了。這是過去 12 個月的數據，這是一個四捨五入的數字，其動態符合預期，正如我們所提到的，非 AI 原生企業的成長是落地和擴張速度比最近幾季更快的結合。因此，如果這種情況持續下去，以過去 12 個月的指標來衡量，你會看到一個方向性的趨勢。

Eric Heath, KeyBanc.

Eric Heath，KeyBanc。

David, Bits AI seems like a really exciting thing out of DASH. And I know it's still in preview, but you mentioned there's a lot of interest there. So I'm just curious how you think about the Agentic opportunity with Bits AI how meaningful this can be for 2026 as a differentiator versus competition and also as a revenue contributor?

David，Bits AI 看起來是 DASH 公司推出的一個非常令人興奮的產品。我知道它目前還在預覽階段，但你提到很多人對此很感興趣。所以我很好奇您如何看待 Bits AI 的智慧代理機會，它在 2026 年作為一項差異化優勢（相對於競爭對手）以及一項收入貢獻因素，其意義有多大？

Yes. So -- I mean, look, it's super exciting. The feedback is very good on it. I mean, we've been collecting all the -- so I read one quote, we have dozens that look just like that that was sent to us by customers. And so that's very, very exciting.

是的。所以——我的意思是，你看，這太令人興奮了。反饋非常好。我的意思是，我們一直在收集所有——我讀到一條評論，我們有幾十條評論看起來和這條一模一樣，都是客戶發給我們的。所以這非常非常令人興奮。

The -- we also started I think some customers buy -- come to it just to show value and to make sure we're on to the right product mix. And so we feel good that this is something that is high quality and we can monetize. In terms of the impact for next year, on the packaging side, I'm not completely sure yet whether the biggest impact will be seen from what we charge for itself or for the rest of the platform, that it gets what it is on the differentiation of Bits AI.

我們也開始認為一些顧客購買——只是為了展示價值，並確保我們擁有正確的產品組合。因此，我們感到很高興，因為這是一款高品質且可以獲利的產品。就明年的影響而言，在包裝方面，我還不完全確定最大的影響是來自我們自身的收費，還是來自平台其他部分的收費，畢竟 Bits AI 的差異化優勢使其獲得了應有的價值。

I think that's more of a broader question of packaging and monetization of AI. And remember that we have a product that is usage based. So anything that drives usage of and adoption from customers is good for us and is very, very monetizable.

我認為這更多的是一個關於人工智慧的包裝和貨幣化的更廣泛的問題。請記住，我們的產品是基於使用量的。因此，任何能夠促進客戶使用和採納的產品對我們來說都是好事，而且非常容易變現。

But what we can tell you is this is differentiating. This is good. It works significantly better than anything else we've seen order in the market, and we are doubling down on it. We have many, many teams now working on deepening CSRs to making sure it goes further into the resolution doesn't just point to the issue, but it is the code have all these kind of things, working hard on that.

但我們可以告訴你的是，這是區別性的。這很好。它比我們目前在市場上看到的任何其他訂購方式都有效得多，我們正在加倍投入。現在有許多團隊正在努力深化客戶滿意度調查 (CSR)，以確保它能更深入地解決問題，而不僅僅是指出問題所在，而是深入到程式碼中，涵蓋所有這些方面，我們正在為此努力。

We're also working on breadth, making sure that we train it on many more types of data, I mean, in terms of sources sometimes even systems that are also systems that are not tap so we can cut across to other systems our customers are using. So we are very, very aggressively developing Bits AI. It's resonating by well in the market.

我們也在努力擴大廣度，確保我們用更多類型的資料來訓練它，我的意思是，就資料來源而言，有時甚至是那些並非直接存取的系統，這樣我們就可以跨系統存取我們的客戶正在使用的其他系統。所以我們正在非常積極地開發Bits AI。它在市場上反應很好。

Gray Powell, BTIG.

Gray Powell，BTIG。

Congratulations on the great results. So maybe just like taking a step back, if we go back to the beginning of the year, Datadog was expecting 19% revenue growth. It looks like you're tracking to something over 26% growth now, and that's just the high end of your guidance.

祝賀你們取得如此優異的成績。所以，不妨回顧一下，如果我們回到年初，Datadog 當時預計營收成長 19%。看來你們目前的成長率預計將超過 26%，而這僅僅是你們預期成長率的上限。

So I guess my question is, what surprised you the most this year? And then just how do you feel about the sustainability of those drivers as you look forward? .

所以我想問的是，今年最讓你感到驚訝的是什麼？那麼，展望未來，您如何看待這些驅動因素的可持續性？。

I mean, look, the -- so first, I apologize for reading on the results. We might do it again, but we'll see. The -- I think the biggest surprise for us has been that the -- so AI in general has -- AI adoption has grown faster than we thought it would at the beginning of the year. So we've seen that across our AI cohort.

我的意思是，你看，首先，我為宣讀結果而道歉。我們或許會再這樣做，但到時候再說吧。我認為最讓我們感到意外的是，人工智慧的普及速度比我們年初預想的要快得多。我們在人工智慧領域已經看到了這種情況。

We've seen also that we got some of our new products and new -- like the changes we're making on the go-to-market side to click perhaps earlier than we would have thought otherwise. So all in all, we saw the leading part of the business with AI growth faster, not the lag, but the slower growing, more tensional property business also accelerate and that gives us where we are today.

我們也發現，我們的一些新產品和新措施——例如我們在市場推廣方面所做的改變——可能比我們預想的更早獲得了成功。總而言之，我們看到人工智慧引領的業務成長速度更快，而不是落後的那部分業務，而成長較慢、更具挑戰性的房地產業務也在加速發展，這造就了我們今天的局面。

And I'd add, we have a good demand environment, and we've been investing whether it be in the products that Oli's been talking about or in the sales capacity we made clear that we were in investment and we're seeing those investments pay off.

我還要補充一點，我們目前的需求環境良好，我們一直在進行投資，無論是奧利一直在談論的產品，還是銷售能力，我們都明確表示了我們正在進行投資，而且我們看到這些投資正在獲得回報。

Koji Ikeda, Bank of America Securities.

池田浩二，美國銀行證券。

Just one from me here. I wanted to ask a question on the inflection in the non-AI native growth and how to think about the area2s of strength in this cohort. Is it coming from your largest enterprises? Is it coming from a certain type of customer?

我這裡也想說一句。我想問一個關於非人工智慧原生成長拐點的問題，以及如何看待這群人的優勢領域。是否來自你們最大的企業？是否來自特定類型的客戶？

Is there a common theme in the workloads that you're seeing or the products that are being added on that is driving that strength? Or is it just really just broad-based? What I'm trying to get out here is I'm really trying to understand more the durability of this growth of collection.

您觀察到的工作負載或新增產品是否存在某種共同的主題，這推動了這種優勢？或者它真的只是基礎廣泛？我在這裡想要表達的是，我真的想更深入地了解這種收藏成長的持久性。

So it is broad-based. And I think, again, speaks to a couple of things. It speaks to the fact that, in general, the demand environment is good. Though I would say, there's been a very, very high growth of hyperscaler revenue that over the past -- next generation for the hyperscale’s in general. A lot of that is GPU related, but the 2growth we're seeing here and the exception we're seeing here is largely not GPU-related livery, but not autonomy. So that's not exactly what you've seen with some of the other vendors there.

所以它的基礎很廣泛。我認為這又說明了兩件事。這表明，總體而言，市場需求環境良好。不過我想說的是，過去一段時間以來，超大規模資料中心的收入成長非常非常快——下一代超大規模資料中心總體而言。其中許多都與 GPU 有關，但我們在這裡看到的 2growth 和我們在這裡看到的例外情況，很大程度上與 GPU 無關，但與自主性無關。所以，這跟你在其他一些攤販那裡看到的情況不太一樣。

One reason this is broad-based is these are the same products we sell to all customers, and this is largely the same go-to-market organization that we have a few segments, but -- and we've been doing well executing there. I think we've invested quite a bit in product, and we keep, and we will keep doing it, and we see the results of that.

之所以能取得如此廣泛的成功，其中一個原因是這些是我們向所有客戶銷售的相同產品，而且我們基本上採用的是相同的市場推廣組織模式，雖然我們有一些細分市場，但是——而且我們在那裡的執行情況一直很好。我認為我們在產品方面投入了相當多的資金，而且我們會繼續這樣做，我們也看到了成果。

Yes, I want to -- I'll add that it's across the customer base, enterprise SMB. And when we look at it, it's not just an AI SMB. If you remove these AI companies, you still see a strengthening SMB demand cycle going on. And unlike in previous periods, it also is across spending ranges. We're not seeing larger spenders or smaller spenders. We're just seeing a broad trend of improved demand across the spending trends.

是的，我想補充一點——它涵蓋了所有客戶群，包括企業和中小企業。當我們仔細觀察時，會發現它不僅僅是一家人工智慧中小企業。即使剔除這些人工智慧公司，你仍然可以看到中小企業需求週期持續增強。與以往時期不同的是，這種情況也發生在各個消費區間。我們沒有看到消費額較大的消費者或消費額較小的消費者。我們看到的是消費趨勢整體上需求改善的趨勢。

Remember that for us, SMB is any company at less than 1,000 employees. It includes a lot of very legitimate and growing businesses. It's -- it's not just anti.

請記住，對我們而言，中小企業是指員工人數少於 1000 人的公司。其中包括許多非常合法且不斷發展的企業。這不僅僅是反對。

Ittai Kidron, Oppenheimer & Co.

伊泰‧凱德倫 (Ittai Kidron)，奧本海默公司

Congrats guys. Really great numbers. Oli, your answer to one of the questions and kind of going into the drivers behind the upside. You've talked about sales capacity increase. You didn't talk much about sales efficiency. Is there a way you can give us some color on where do you stand on percent of salespeople that are hitting quota, where does that ratio stand relative to historical patterns for you guys? And as you approach '26 year, do you anticipate any material changes in the comp structure just given the breadth of product and the list of opportunities, how do you get people focused?

恭喜各位！非常棒的數據。奧利，你對其中一個問題的回答，以及對上漲背後的驅動因素的探討。您談到了提高銷售能力的問題。你很少談到銷售效率。能否透露一下貴公司銷售人員完成銷售目標的比例，以及該比例與貴公司歷史數據相比處於什麼水準？隨著 2026 年的臨近，考慮到產品範圍和機會眾多，您是否預期薪酬結構會發生任何實質變化？如何讓員工集中精力？

Yes. So we feel good about the SaaS productivity in general. And the rule generally, you grow by scaling capacity and maintaining productivity, it's hard to drive both up at the same time. And remember, if you want to go to 10 times, you can do that by scaling if you can't really do it by improving productivity, so you have to scale. And we've been doing that, and we've been successful at it opine.

是的。所以我們整體上對SaaS的生產力感到滿意。一般來說，成長是透過擴大產能和維持生產力來實現的，很難同時提高這兩者。記住，如果你想達到 10 倍的規模，如果你不能透過提高生產力來實現，那麼你就必須擴大規模。我們一直在這樣做，而且我們在這方面取得了成功。

In terms of the content, look, we keep changing the way we can dense the way we manage the sales force in general to make sure we have the right focus. One of the gifts of a business like ours is that we see -- we have a very heavy land mix and model.

就內容而言，我們一直在改變管理銷售團隊的方式，以確保我們擁有正確的重點。像我們這樣的企業的優勢之一在於，我們看到——我們擁有非常多元化的土地組合和模式。

And so we get a lot of growth from main customers. The challenge in create on the other hand, is how do we get to focus the sales force on the newer customers, the smaller ones and the new ones because it is more work to get an extra dollar for a smaller customer or formula new ones, than it is for an existing one that they already have scale.

因此，我們從主要客戶那裡獲得了大量的成長。另一方面，創造的挑戰在於，我們如何讓銷售人員專注於新客戶、小客戶和新客戶，因為從小客戶那裡多賺一美元或開發新客戶比從已經擁有規模的現有客戶那裡多賺一美元要困難得多。

And so a lot of the tweaks we met to our comp plans we like to that, to make sure we direct our attention and we reward people for what is going to generate the most long-term growth for us. And we've made a number of changes I won't go through them design changes. But we had a number of changes this year, we see a number of NPLs.

因此，我們對薪酬方案進行了許多調整，我們希望確保我們把注意力集中在那些能為我們帶來最大長期成長的事情上，並獎勵那些做出這些事情的人。我們也做了一些改動，我就不一一贅述了，這些都是設計上的改變。但今年我們經歷了一些變化，出現了一些不良貸款。

Another thing I mentioned on the call was we mentioned a win for one of our new go-to-market motions and that specifically getting in place multiyear plans to go after some larger customers that are tougher to land than what we've done in the past. And sometimes, it takes more than a year to types of customers.

我在電話會議上也提到，我們一項新的市場推廣策略取得了成功，具體來說，就是製定多年計劃，爭取一些比我們過去更難拿下的大客戶。有時，識別不同類型的客戶需要一年以上的時間。

And the problem is if you compliant only has a one-year horizon, like it doesn't give a great incentive for the sales force to go after those customers. And so we cordoned off a few of those companies. We have special plans to go after that, and we're starting to see success with that too is a general example.

問題在於，如果你的合規期限只有一年，那麼它就無法給銷售人員足夠的動力去爭取這些客戶。於是我們封鎖了其中幾家公司。我們有專門的計劃來推進這項工作，我們已經開始看到這方面取得了一些成功，這是一個普遍的例子。

Andrew Sherman, TD Cowen.

Andrew Sherman，TD Cowen。

Great. Congrats. I know you have a team focused on the Fortune 500, where there's still a lot of white space for you. Curious to hear how the team is ramping to productivity that help drive some of the strong new logo bookings and can this contribute even more next year?

偉大的。恭喜。我知道你們有一個專注於財富 500 強企業的團隊，但你們在這個領域還有很多空白市場。很想知道團隊是如何提高生產力以推動新商標預訂量成長的，以及明年能否做出更大的貢獻？

Yes. I mean, look, the key is not new. I mean, we've been focusing on that for many years, and we're tracking well. One thing I was mentioning just before was one challenge even the Fortune 500 is to make sure that we focus on landing new customers and make sure that there's the right amount of sales attention and we work for the landing a customer even if it's for a small amount, and I think we've done well.

是的。我的意思是，你看，這把鑰匙並不是什麼新鑰匙。我的意思是，我們多年來一直專注於此，而且進展順利。我剛才提到的一點是，即使是財富 500 強企業也面臨著一個挑戰，那就是確保我們專注於獲取新客戶，確保給予足夠的銷售關注，並且努力爭取客戶，即使金額很小，我認為我們做得很好。

I mean again, we can comment on that again after the next quarter when we have a full year of our new plants that have been validated. But so far, we feel very good about it.

我的意思是，我們可以等到下一個季度，也就是我們新工廠經過驗證運行滿一年之後，再對此發表評論。但到目前為止，我們對此感覺非常好。

Alex Zukin, Wolfe Research.

Alex Zukin，Wolfe Research。

And congrats on dropping some truly inspiring quotes in the script. Maybe Oli, one for you and then I have a quick follow-up for David. Just the duration of this acceleration of the non-AI cohort. It seems like from all your forward-looking metrics, whether it's billings, RPO, CRPO. Those were, again, really, really strong how long do you think we should think about the duration of this trend of this non-AI acceleration?

恭喜你在劇本中加入如此鼓舞人心的名言。奧利，或許我先問你一個問題，然後我再快速問大衛一個後續問題。僅是非人工智慧群體加速發展的持續時間。從你們所有的前瞻性指標來看，無論是帳單金額、RPO 或 CRPO，似乎都是如此。這些趨勢確實非常強勁，您認為我們應該考慮這種非人工智慧加速發展趨勢的持續時間嗎？

Well, our consumption business. So we -- the hardest thing to understand is what the future is going to look like for consumption. The way I would say it is we feel very good about it at the midterm, long term, not -- ebbs and flow than given month or quarter, that's harder to tell. And again, that's what we see through the life of the company.

嗯，我們的消費業務。所以，最難理解的是消費的未來會是什麼樣子。我的意思是，我們對中期和長期前景都感覺非常好——至於某個​​月份或季度的情況，則有起伏，這很難說。而且，我們在公司的發展歷程中也看到了這一點。

So we feel very confident about the motion in general for digital transformation and cloud migration is steady. And sometimes it slows down a little bit, but it reaccelerates after that. And we see that key going on for a very long time.

因此，我們對數位轉型和雲端遷移的整體發展趨勢感到非常有信心，而且這一趨勢也在穩步推進。有時速度會稍微減慢，但之後又會重新加速。而且我們看到這個關鍵因素持續了很長一段時間。

Okay. And then maybe, David, for you, look, gross profit dollar acceleration while you're seeing your largest customer kind of get better unit economics is also inspiring to see how should we think about the progression of gross margins and gross profit dollar growth, particularly as you continue to also see the AI cohort acceleration.

好的。然後，David，也許對你來說，你看，當你看到最大的客戶單位經濟效益有所改善時，毛利美元的加速增長也令人鼓舞，讓我們思考我們應該如何看待毛利率和毛利潤美元的增長進程，尤其是在你繼續看到人工智能群體加速發展的情況下。

Yes, there's a couple of things. I think we've mentioned that we've been focused and have focused over the many years on the efficiency of our cloud platform. We have significant engineering efforts around cost of sales and delivery of value. And so we've been able to deliver on that. We also have a very broad customer base distributed in terms of volume. So as customers get larger and maybe get volume discounts, we have a number -- a lot of customers coming in, it's smaller, so that balance there.

是的，有幾件事。我想我們已經提到過，多年來我們一直專注於提高雲端平台的效率。我們在銷售成本和價值交付方面投入了大量工程資源。因此，我們已經實現了這一目標。我們的客戶群也非常廣泛，銷售分佈也很廣泛。所以，隨著客戶規模增大，可能會獲得批量折扣，而隨著許多客戶湧入，規模較小，這就需要平衡。

And then in terms of the sort of the future -- I'll repeat what we've always said that we've been running the company with a gross margin plus or minus 80%, we've given that range and not changed it, and we watch it. And it gives us signals in terms of efficiency, how we're operating, it gives us signals in pricing and things like that and I wouldn't change the comments we made over the many years about looking at that and then developing operations and strategies around that.

至於未來發展方向——我會重申我們一直以來所說的，我們一直以毛利率正負 80% 為目標來經營公司，我們設定了這個範圍，並且沒有改變，我們會密切關注。它在效率、運營方式等方面為我們提供了信號，在定價等方面也為我們提供了信號，我不會改變我們多年來就此發表的評論，即要關注這一點，然後圍繞這一點制定運營和戰略。

Ryan MacWilliams, Wells Fargo.

瑞安‧麥克威廉斯，富國銀行。

Just one for me. On the large AI contract expansion that you provided commentary on, is there any way we can think about the contribution change from this customer over the next few quarters?

我只留一個。關於您評論過的大型人工智慧合約擴展，我們能否考慮一下該客戶在未來幾季內的貢獻變化？

No. I mean we don't provide that kind of information on individual customers. We're trying to give a picture of the overall business. Generally, I think as Oli mentioned, on our larger customers, we have a motion of the expansion of volume and then we talk when we work on the term and the volume-based pricing, but we don't give guidance like that on individual customers.

不。我的意思是，我們不會提供有關單一客戶的這類資訊。我們試圖展現整個業務的全貌。總的來說，我認為正如 Oli 所提到的，對於我們的大客戶，我們會逐步擴大交易量，然後在製定合約期限和基於交易量的定價方案時再進行討論，但我們不會對單一客戶提供這樣的指導。

Mike Cikos, Needham.

麥克·西科斯，尼德姆。

I just wanted to come back to it, Oli, for the non-AI native strength, I know we've kind of hit on this a number of times, whether it's road map sales capacity execution, but like kudos on the numbers here? I'm just trying to get a better sense of the why now. Is it just a composite of all those different pieces clicking together this quarter? Or is there anything more to impact there? And then I have a follow-up for David.

奧利，我只是想再說一遍，關於非人工智慧的原生優勢，我知道我們已經多次談到這一點，無論是路線圖銷售能力執行，還是這裡的數據，都值得稱讚？我現在只是想更好地理解其中的原因。是不是本季所有不同因素共同作用的結果？或者有其他因素會影響那裡嗎？接下來我還要問大衛一個問題。

Again, I don't think there's a lot more to back there. And I know it's growing away but it's also the way we've been growing for the past 15 years or so. So that's a -- that's -- I would call it the usual.

再說一遍，我覺得那邊也沒什麼好說的了。我知道它正在逐漸消失，但這也是我們過去 15 年左右的發展方式。所以，這——這——我會稱之為尋常事。

Awesome. Awesome here. Okay. And then for the follow-up to David. David, I don't want to take anything away from the Q3 results you guys just posted, and we obviously have the strong guide here for Q4. But I just can imagine myself a month from now starting to get inbounds from certain folks asking about the holiday season and the fact that we have the holidays landing on weekdays in Q4 here. Can you just kind of discuss how you thought about constructing guidance for this Q4 year?

驚人的。這裡太棒了。好的。接下來是戴維的後續報導。David，我不想貶低你們剛發布的第三季業績，而且我們顯然對第四季有很強的預期。但我可以想像，一個月後，我會開始收到一些人的來電，詢問有關假期以及我們這裡第四季度假期恰逢工作日的情況。您能否簡要談談您是如何制定今年第四季業績指引的？

Yes. We have years of experience of analyzing the day-by-day patterns. In the holidays, we know that the holiday period ends up in the usage side because of vacation holidays, and we incorporate that into our guidance. We're I think, evolved a lot over the years and sort of days adjusted types of days, et cetera. And so we would be incorporating that like we've incorporated in other years, if there are differences in this calendar period, we incorporate that as always.

是的。我們擁有多年分析日常模式的經驗。我們知道，由於假期，假期期間的使用量會增加，我們將這一點納入了我們的指導方針中。我認為，這些年來我們發生了很大的變化，日子也隨之調整，等等。因此，我們會像往年一樣，把這些因素考慮進去；如果這個日曆時期有所不同，我們也會像往常一樣考慮進去。

Karl Keirstead, UBS.

瑞銀集團的卡爾·基爾斯蒂德。

Okay. Great. I'll ask one for David and one for Olivier. David, first of all, congratulations on the extension of the larger contract, I think everybody on the line is applauding that. I know you're reticent to get into any details, but maybe I could try. Are you able to clarify whether that was a one-year deal or multiyear?

好的。偉大的。我給大衛要一份，給奧利維爾要一份。大衛，首先祝賀你續簽了更大的合同，我想所有人都為此鼓掌。我知道你不太願意透露細節，但我或許可以試著說。您能否澄清一下，這是一份一年期的合約還是一份多年期的合約？

And then related to that, David, what is the contribution to CRPO from that deal, which I presume landed in your CRPO number. If it is a one-year deal does the entirety of that contract contribute to the sequential CRPO performance in the quarter? So that's it for you, David.

那麼，David，關於這一點，這筆交易對 CRPO 的貢獻是什麼？我猜這筆貢獻體現在你的 CRPO 數據中。如果這是一份為期一年的合同，那麼該合約的全部內容是否都會對當季的連續 CRPO 業績做出貢獻？大衛，你的任務就到此為止了。

And then Olivier, maybe I'll just ask both at once. Some of the very large AI natives are beginning to diversify to utilizing Oracle's OCI and Stargate. And I'm wondering what's the opportunity for Datadog to essentially follow that behavior and begin scaling on Oracle target or because a lot of what Oracle is doing with the AI native is training clusters, perhaps that near-term opportunity is more limited.

然後奧利維爾，也許我會同時問他們兩個。一些規模非常大的人工智慧原生企業開始轉向使用 Oracle 的 OCI 和 Stargate。我想知道 Datadog 是否有可能效仿這種做法，開始在 Oracle 目標平台上擴展規模？或者，由於 Oracle 目前在 AI 原生應用方面主要專注於訓練集群，因此這種近期機會可能比較有限。

Yes. On the first point, I think we give a lot of examples and our motion, which our customers would be following, including that one would be -- we fix out annual plus commits. We're not commenting on individual contracts here, but it would follow a typical path to other types of contracts. So that's what we would do.

是的。關於第一點，我認為我們給了許多例子，我們的行動（我們的客戶將會遵循）包括－我們解決年度承諾問題。我們在此不對個別合約發表評論，但這與其他類型的合約遵循著典型的發展路徑。所以我們會這麼做。

Yes. And on the one, look, this -- we've than OCI integration, and we see more demand from customers on OCI. Some of the things we see like the targets, et cetera, like these are extremely custom build out, like I don't know -- they're not necessarily exactly cloud because they are custom built for specific customers.

是的。而且，你看，我們已經比 OCI 整合做得更好了，我們看到客戶對 OCI 的需求也更大了。我們看到的一些東西，例如目標等等，都是高度客製化的，例如我不知道——它們不一定完全是雲，因為它們是為特定客戶量身定制的。

So the opportunity there is more remote today. But it's -- again, one completion is that it's not fantastic opportunity to productize, but if 10, 15, 20, 50 companies start using that, then that really becomes a commercial opportunity. And so we're very much plugged into all of that. And we go basically where our customers are.

所以如今這樣的機會更加渺茫了。但是——再說一遍，一個缺點在於，它並不是一個絕佳的產品化機會，但如果 10、15、20、50 家公司開始使用它，那麼它就真的變成了一個商業機會。因此，我們與這一切都息息相關。我們基本上是哪裡有客戶，我們就去哪裡。

I think you mentioned about the RPO. I think in this case, we've mentioned this current, and the total is roughly the same, and there wouldn't be anything in that contract that would have been materially around of those numbers. Those numbers, I think we mentioned are produced from the booking’s growth more generally and not from that particular contract.

我想你提到了RPO（復健點分配）。我認為在這種情況下，我們已經提到了當前的情況，總額大致相同，而且該合約中沒有任何內容會與這些數字有實質性的差別。我認為我們之前提到的那些數字，是預訂量整體成長帶來的，而不是來自那份特定合約的。

Jake Roberge, William Blair.

傑克‧羅伯格，威廉‧布萊爾。

Yes. Just on the recent go-to-market investments, obviously, it seems like there's been a lot of traction thus far with those. So I'm curious if there are any areas like security or the new logos or upmarket that that you could look to lean even deeper into just given the growth that you've seen here.

是的。就最近的市場投資而言，顯然，到目前為止這些投資似乎都取得了巨大的進展。所以我很好奇，鑑於你們在這裡看到的成長，在安全、新標誌或高端市場等領域，你們是否可以進一步深入研究。

Yes, definitely. And there are some things we didn't do this year that we'll definitely go to the next year. So there's a number of things we are -- we're in Q4, right? So we're in the middle of planning for next year, and we basically will keep scaling what's working, stop doing some of the things that conclusive and then charge a few more things. That's the way it was.

是的，當然。今年我們沒做成的一些事情，明年我們一定會去做。所以，我們現在有很多事情要做——我們現在處於第四季度，對吧？所以我們正在製定明年的計劃，基本上我們會繼續擴大那些行之有效的措施，停止一些已經結束的事情，然後再增加一些新的措施。事情就是這樣。

The -- interestingly enough, building a go-to-market is not that different from building software like you experiment together data you see what's working was not working and you build the systems.

有趣的是，制定市場推廣策略與建立軟體並沒有太大區別，就像你一起試驗數據，看看哪些有效哪些無效，然後建立相應的系統一樣。

That's helpful. And then just on the new Bits AI agents, can you just talk about the early feedback that you've gotten for those solutions and maybe how the engagement with those agents as compared to kind of the ramp of security Flex Logs. I know, obviously, much earlier days, but just how it compared when those were still largely in the preview phase?

那很有幫助。那麼，關於新的 Bits AI 代理，您能否談談您收到的早期回饋，以及與安全性 Flex Logs 的推廣相比，這些代理的用戶參與度如何？我知道，這顯然是更早的時期，但當時這些技術還主要處於預覽階段，情況又是如何呢？

I mean look, the Bits AI agent is -- it really has a real factor for customers. So what works really well is and we've seen that number of times. But the -- we set it up for them. It's running on their alert and they go through an outage and they still go to the motion, so they still go -- they still set up a bridge and they have 20 people and they spend two hours and in the end, they have an idea what went wrong.

我的意思是，你看，Bits AI 代理商——它對客戶來說確實具有真正的吸引力。所以真正行之有效的方法是，而且我們已經多次看到這一點。但是──我們為他們安排好了。他們的警報系統一直在運行，即使系統出現故障，他們仍然會採取行動，他們仍然會搭建一個橋接網絡，他們有 20 個人，花了兩個小時，最終，他們知道出了什麼問題。

And then they go to that or they see, there's an investigation that had run, and three minutes into the outage, it got the same conclusion that was up two hours later, it was 20 people in the call. And that completely are opening for customers when they see it.

然後他們查看了調查結果，或者發現已經進行了調查，在故障發生三分鐘後，調查得出了與兩小時後相同的結論，當時有 20 人參與了通話。當顧客看到時，一切都顯得那麼美好。

And we have -- so that's why we get many quotes about -- so now there's more we need to do there, like new customers say, Oh, it's great. Now make it for me, can you do this, can you do that? Can support that all the system that right now you can actually set it up for.

我們已經做到了——所以這就是為什麼我們收到了很多關於——所以現在我們需要在這方面做更多的工作，就像新客戶說，哦，這太棒了。現在幫我做一下，你能做到這個嗎？你能做到那個嗎？可以支援目前您可以實際設定的所有系統。

So we have a very, very full road map of things we need to do, and we're doubling the one. We also shipped -- I mean this one is in previous, but we shipped security agent that looks at vulnerabilities looks at security signal and those three ads that basically look at the trends to get what might be benign or what might be a real issue. We also are getting very, very positive feedback for that.

所以我們制定了一份非常非常完整的待辦事項清單，而且我們還要將清單上的事項數量加倍。我們也發布了——我的意思是，這個之前已經發布過了——我們還發布了一個安全代理，它可以檢查漏洞、檢查安全信號，以及三個廣告，它們基本上會查看趨勢，以確定哪些可能是良性的，哪些可能是真正的問題。我們也收到了非常非常正面的回饋。

And in fact, that would help us win some large land deals for our plate products because the combination of the theme that runs extremely efficiently on top of observability data that runs very efficiently on top of Flex Logs, but also send an immense amount of time by the gating 90% of the issues out of the way with automated the investigations, that's extremely attractive to customers.

事實上，這將有助於我們為我們的板材產品贏得一些大型土地交易，因為該主題在 Flex Logs 上高效運行，而 Flex Logs 又在可觀測性數據上高效運行，同時通過自動化調查排除 90% 的問題，從而節省大量時間，這對客戶來說極具吸引力。

All right. And I think with that, we're going to close the call. So before we go, I just want to give one quick shot out to the team because I know, as I said earlier, we have quite a lot going on in Q4, whether it's on the planning side, the product building side or on the sales side, where I said we have a really very exciting pipeline and -- so we have a lot to do. I want to thank the team for the hard work there. I also I'm looking forward to meeting a lot of our existing and new customers at Investor Day in a few weeks, and I'll see you there. Thank you all.

好的。我想，通話到此就結束了。所以在我們離開之前，我想快速地向團隊致謝，因為我知道，正如我之前所說，我們在第四季度有很多事情要做，無論是在計劃方面、產品開發方面還是銷售方面，我說過我們有一個非常令人興奮的產品線——所以我們有很多事情要做。我要感謝團隊的努力。我也很期待在幾週後的投資者日上見到我們許多新舊客戶，到時見。謝謝大家。

Thank you for your participating in today's conference. This does conclude the program. You may now disconnect.

感謝您參加今天的會議。節目到此結束。您現在可以斷開連線了。