Elastic NV (ESTC) 2026 Q3 法說會逐字稿

Good afternoon, and welcome to the Elastic third-quarter fiscal 2026 earnings results conference call. (Operator Instructions) Please note, this event is being recorded.

下午好，歡迎參加 Elastic 2026 財年第三季收益業績電話會議。（操作說明）請注意，本次活動正在錄影。

I would now like to turn the conference over to Eric Prengel, Global Vice President of Finance. Please go ahead.

現在我將把會議交給全球財務副總裁艾瑞克‧普倫格爾。請繼續。

Thank you. Good afternoon, and thank you for joining us on today's conference call to discuss Elastic's third-quarter fiscal 2026 financial results. On the call, we have Ash Kulkarni, Chief Executive Officer; and Navam Welihinda, Chief Financial Officer. Following their prepared remarks, we will take questions. Our press release was issued today after the close of market and is posted on our website.

謝謝。下午好，感謝各位參加今天的電話會議，共同討論 Elastic 2026 財年第三季的財務表現。參與電話會議的有執行長 Ash Kulkarni 和財務長 Navam Welihinda。在他們發言結束後，我們將接受提問。我們的新聞稿已於今日收盤後發布，並已發佈在我們的網站上。

Slides, which are supplemental to the call, can also be found on the Elastic Investor Relations website at ir.elastic.co. Our discussion will include forward-looking statements, which may include predictions, estimates or expectations regarding the demand for our products and solutions and our future revenue and other information. These forward-looking statements are based on factors currently known to us, speak only as to the date of this call and are subject to risks and uncertainties that could cause actual results to differ materially. We disclaim any obligation to update or revise these forward-looking statements unless required by law.

本次電話會議的補充幻燈片也可在Elastic投資者關係網站ir.elastic.co上找到。我們的討論將包含前瞻性陳述，其中可能包括對我們產品和解決方案的需求、未來收入及其他資訊的預測、估計或預期。這些前瞻性陳述是基於我們目前已知的因素，僅代表本次電話會議當日的情況，並受風險和不確定性的影響，這些風險和不確定性可能導致實際結果與預期結果有重大差異。除非法律要求，否則我們不承擔更新或修改這些前瞻性聲明的任何義務。

Please refer to the risks and uncertainties included in the press release that we issued earlier today included in the slides posted on the Investor Relations website and those more fully described in our filings with the Securities and Exchange Commission.

請參閱我們今天稍早發布的新聞稿中包含的風險和不確定性，這些風險和不確定性也包含在投資者關係網站上發布的幻燈片中，以及我們在提交給美國證券交易委員會的文件中更詳細描述的風險和不確定性。

We will also discuss certain non-GAAP financial measures. Disclosures regarding non-GAAP measures, including reconciliations with the most comparable GAAP measures, can be found in the press release and slides. Unless specifically noted otherwise, all results and comparisons are on a fiscal year-over-year basis. The webcast replay of this call will be available on our company website under the Investor Relations link.

我們也將討論一些非GAAP財務指標。有關非GAAP指標的披露信息，包括與最可比較GAAP指標的調節表，可在新聞稿和幻燈片中找到。除非另有特別說明，所有結果和比較均以財政年度同比為基礎。本次電話會議的網路直播回放將在公司網站的「投資者關係」連結下提供。

Our fourth-quarter fiscal 2026 quiet period begins at the close of business on Thursday, April 16, 2026. We will be participating in the Morgan Stanley Technology, Media and Telecom Conference on March 2.

我們 2026 財年第四季靜默期從 2026 年 4 月 16 日星期四營業結束時開始。我們將參加3月2日舉行的摩根士丹利科技、媒體和電信大會。

With that, I'll turn it over to Ash.

這樣，我就把麥克風交給阿什了。

Thank you, Eric, and good afternoon, everyone. Thank you for joining today's call. Elastic delivered yet another outstanding quarter, beating the high end of guidance across all key metrics and showcasing the power of the Elastic platform and our business model. Sustained platform demand, strong sales execution and our relentless focus on customers drove Q3 momentum. As LLM rapidly evolve their capabilities around inference and reasoning, it is becoming increasingly clear that context is the most important ingredient in making these models useful within an enterprise.

謝謝你，埃里克，大家下午好。感謝您參加今天的電話會議。Elastic 又迎來了一個出色的季度，所有關鍵指標都超出預期上限，充分展現了 Elastic 平台和我們商業模式的強大實力。持續的平台需求、強勁的銷售執行力以及我們對客戶的不懈關注推動了第三季的成長動能。隨著 LLM 在推理和推理方面的能力迅速發展，越來越明顯的是，上下文是使這些模型在企業中發揮作用的最重要因素。

With that backdrop in Q3, we continued to see enterprises choose Elastic to power context for their most critical AI needs. Translating the success to our performance, we achieved 18% total revenue growth and an 18.6% non-GAAP operating margin. Sales led subscription revenue accelerated to 21% alongside our growing cohort of $100,000 ACV customers, which now exceeds 1,660.

在第三季度，在這樣的背景下，我們繼續看到企業選擇 Elastic 來為其最關鍵的 AI 需求提供上下文支援。將這一成功轉化為我們的業績，我們實現了 18% 的總收入成長和 18.6% 的非 GAAP 營業利潤率。隨著年合約價值 10 萬美元的客戶群不斷壯大（目前已超過 1,660 家），銷售驅動的訂閱收入加速成長至 21%。

Q3 marked our sixth consecutive quarter of strong field execution, driving solid customer commitments and supporting healthy CRPO growth. That execution is also translating into a strong pipeline as we head into Q4.

第三季標誌著我們連續第六個季度在現場執行方面表現強勁，推動了穩固的客戶承諾，並支持了 CRPO 的健康成長。這種執行力也轉化為強勁的業務成長，使我們在進入第四季時擁有了充足的產品儲備。

The lifeblood of organizations is the proprietary data that they create, manage, and analyze every day to drive business decisions and operations. This data is massive, often many perabytes in scale and simply cannot be moved for cost and security reasons outside of the organization's control. For businesses to use agentic AI, the LLM needs to come to the data. This is where Elastic comes in, with our ability to help organizations store and manage all of their data in very cost-effective ways and by providing accurate real-time context to AI by searching through all of this organizational data in real time.

組織的命脈在於其每天創建、管理和分析的專有數據，這些數據用於驅動業務決策和營運。這些資料量龐大，通常達到數PB，而且由於成本和安全原因，根本無法在組織控制範圍之外進行遷移。企業要使用智能體人工智慧，LLM 需要取得數據。這正是 Elastic 的用武之地，我們能夠幫助組織以非常經濟高效的方式儲存和管理所有數據，並透過即時搜尋所有這些組織數據，為 AI 提供準確的即時情境。

Furthermore, Elastic is capable of doing this consistently across cloud and self-managed environments. This hybrid flexibility allows sensitive data and workloads to remain in their preferred environments, eliminating the need for costly replatforming. This unique flexibility is why we continue to displace legacy vendors and niche cloud-native players alike. And the results are clear. The number of commitments for over $1 million in annual commitment value signed this quarter grew over 30% compared to the same period last year, driven by new logos and customer expansion.

此外，Elastic 能夠在雲端和自管理環境中始終如一地實現這一點。這種混合靈活性使得敏感資料和工作負載能夠保留在其首選環境中，從而無需進行成本高昂的平台遷移。正是這種獨特的靈活性，讓我們能夠持續取代傳統供應商和利基雲端原生企業。結果顯而易見。受新客戶和客戶擴張的推動，本季簽署的年度承諾價值超過 100 萬美元的承諾數量比去年同期增加了 30% 以上。

Consolidation and AI are powerful tailwinds. As organizations manage exploding data volumes, they are turning to Elastic to drive both innovation and efficiency to their search, observability and security needs. For example, we signed a seven-figure new logo deal with a Fortune 100 insurance institution for Elastic Security.

整合與人工智慧是強勁的推動力。隨著企業面臨資料量爆炸性成長的挑戰，他們開始轉向 Elastic，以滿足其在搜尋、可觀測性和安全性方面的創新和效率需求。例如，我們與一家財富 100 強保險機構簽署了一份價值七位數的 Elastic Security 新標誌合約。

Seeking to modernize their security operations, the company initiated a competitive process to replace a legacy SIEM solution that was plagued by slow query speeds, inefficient data retention and rigid SOC workflows. By leveraging features like Logsdb and searchable snapshots, they're consolidating data into a single cyber data lake with integrated AI-powered SIEM workflows, all powered by Elastic and its capabilities, including AI assistant, attack discovery and AI-driven orchestration. This transition enables their analysts to achieve markedly faster cybersecurity detection and remediation outcomes while meeting strict regulatory requirements.

為了實現安全營運的現代化，該公司啟動了一項競爭性流程，以取代一個飽受查詢速度慢、資料保留效率低下和 SOC 工作流程僵化困擾的傳統 SIEM 解決方案。透過利用 Logsdb 和可搜尋快照等功能，他們正在將資料整合到單一的網路資料湖中，並整合 AI 驅動的 SIEM 工作流程，所有這些都由 Elastic 及其功能提供支持，包括 AI 助理、攻擊發現和 AI 驅動的編排。這一轉變使他們的分析師能夠在滿足嚴格的監管要求的同時，大幅加快網路安全偵測和補救速度。

In another large deal from the quarter, a global leader in data resiliency software, chose Elastic Observability to power the monitoring layer for its new cloud offering. As they migrate their vast user base to the cloud, they are leveraging our full Observability suite, including AI assistant and Logsdb to transform from reactive troubleshooting to intelligent semantic aware analysis.

本季另一筆大交易中，一家全球領先的資料彈性軟體公司選擇 Elastic Observability 為其新的雲端產品提供監控層支援。隨著他們將龐大的用戶群遷移到雲端，他們正在利用我們完整的可觀測性套件，包括 AI 助理和 Logsdb，從被動故障排除轉變為智慧語義感知分析。

By integrating open telemetry and our vector search capabilities, the customer is now able to proactively detect anomalies and remediate issues using natural language queries significantly reducing mean time to resolution. They chose Elastic over incumbents due to our deep integration flexibility, superior handling of unstructured data, and the ability to provide a single source of truth across the organization. Crucially, as companies navigate their cloud migrations, they require a platform that doesn't force them to choose between their existing data centers and the cloud.

透過整合開放遙測技術和我們的向量搜尋功能，客戶現在能夠主動檢測異常情況並使用自然語言查詢來解決問題，從而顯著縮短平均解決時間。他們選擇 Elastic 而不是其他現有供應商，是因為我們具有深度整合靈活性、卓越的非結構化資料處理能力，以及為整個組織提供單一資料來源的能力。至關重要的是，當企業進行雲端遷移時，他們需要一個不會強迫他們在現有資料中心和雲端之間做出選擇的平台。

Our asymmetric advantage in supporting modern cloud and hybrid environments drove a significant win with a global financial group. During the quarter, we closed a seven-figure expansion deal for Elasticsearch, which serves as the core of their online banking application for tens of millions of users. They needed a central data repository capable of supporting both cloud and self-managed architectures, allowing them to run mission-critical workloads in their preferred environment without compromising performance.

我們在支持現代雲端和混合環境方面的不對稱優勢，為我們贏得了全球金融集團的重大勝利。本季度，我們為 Elasticsearch 完成了一筆七位數的擴張交易，Elasticsearch 是他們數千萬用戶的網路銀行應用程式的核心。他們需要一個能夠同時支援雲端架構和自管理架構的中央資料儲存庫，使他們能夠在自己偏好的環境中運行關鍵任務工作負載，而不會影響效能。

Elastic succeeded with the existing MongoDB implementation failed to provide the scalable retriever and precision necessary to move beyond simple search into production-grade context engineering. Moving forward, they are integrating semantic search and advanced AI features to further personalize the user experience through faster, more accurate retrieval.

Elastic 在現有的 MongoDB 實作方面取得了成功，但未能提供可擴展的檢索器和精度，從而無法超越簡單的搜索，進入生產級的上下文工程。展望未來，他們正在整合語意搜尋和進階人工智慧功能，透過更快、更準確的檢索，進一步個人化使用者體驗。

Central to these enterprise engagements is the rise of agentic AI. Customers are moving from passive Q&A to active agents that drive workflows. Precise action requires precise data. The conversation has shifted from which model we use to how to feed it the most accurate context. Enterprises realize that to unlock the value of AI, they must bridge the gap between their LLMs and their proprietary unstructured and structured data.

這些企業合作的核心是智慧人工智慧的興起。客戶正從被動的問答模式轉向由客服人員主導的工作流程模式。精準的行動需要精準的數據。討論的焦點已經從我們使用哪個模型轉移到如何為模型提供最準確的上下文。企業意識到，要釋放人工智慧的價值，就必須彌合其生命週期管理 (LLM) 與其專有的非結構化和結構化資料之間的差距。

Elastic makes this AI work. We are the engine that allows enterprises to build production-grade AI systems that are actually worthy of their business. While others offer simple vector databases, we know that vectors alone are not enough. We delivered the full retrieval toolkit from hybrid search to advanced reranking, ensuring that agents have the relevant context they need to take precise actions. This ability to bridge enterprise data to the LLM with our platform is directly translating into expanded AR adoption.

Elastic 讓人工智慧得以運作。我們是助力企業建構真正符合其業務需求的生產級人工智慧系統的引擎。雖然其他公司提供簡單的向量資料庫，但我們知道，僅僅有向量是不夠的。我們提供了從混合搜尋到進階重排序的完整檢索工具包，確保代理商擁有採取精確行動所需的上下文資訊。我們的平台能夠將企業數據與LLM連接起來，這直接轉化為AR的廣泛應用。

In Q3, new customer commitments with AI continue to grow. And we now have over 2,700 customers on Elastic Cloud using us as a vector database with additional customers using us for broader AI capabilities, including Agent Builder and Attack Discovery, bringing our total count of AI customers to over 3,000. We now have over 470 customers with an ACV of $100,000 or greater using us for AI. This includes more than 410 using us as a vector database. Cumulatively, AI use cases have now penetrated over a quarter of our $100,000 ACV customer cohort. We are seeing sustained demand from the largest companies in the world alongside interest from the new wave of AI native companies.

第三季度，人工智慧領域的新客戶訂單持續成長。目前，我們在 Elastic Cloud 上有超過 2700 位客戶使用我們的產品作為向量資料庫，另有客戶使用我們的產品來實現更廣泛的 AI 功能，包括代理構建器和攻擊發現，使我們的 AI 客戶總數超過 3000 位。目前，我們有超過 470 家年合約價值 (ACV) 為 10 萬美元或以上的客戶正在使用我們的人工智慧服務。其中包括超過 410 家將我們用作向量資料庫的公司。總體而言，人工智慧應用案例已滲透到我們年合約價值 10 萬美元的客戶群的四分之一以上。我們看到，來自全球最大公司的持續需求，以及新一代人工智慧原生公司的興趣。

During the quarter, we closed multiple new logo and expansion deals with AI-first innovators, validating that our platform is the standard for both established enterprises and disruptors. A leading AI recruiting platform used by large enterprises and startups alike chose Elastic's vector database to power their core customer-facing software because our search performance at scale was better than competitors.

本季度，我們與多家以人工智慧為先導的創新企業達成了多項新的合作協議和業務拓展協議，證明我們的平台是成熟企業和顛覆性企業的標準。一家領先的 AI 招募平台，被大型企業和新創公司廣泛使用，選擇 Elastic 的向量資料庫來支援其面向客戶的核心軟體，因為我們的大規模搜尋表現優於競爭對手。

An AI-enabled driver and fleet safety company expanded their use of Elastic search in Q3 as they scale into new global regions. Elastic provides the real-time retrieval necessary to power their platform, ensuring they can manage increasing data volumes without sacrificing performance. And a leading AI native cybersecurity company focused on AR automated penetration testing has integrated our SIEM solution into their product. Elastic centralizes all of their logs without complication, allowing them to effortlessly scale through their massive growth trajectory.

一家利用人工智慧技術提升駕駛員和車隊安全的公司在第三季擴大了對 Elastic Search 的使用，以拓展其在全球新地區的業務。Elastic 提供即時檢索功能，為其平台提供動力，確保他們能夠在不犧牲效能的情況下管理不斷增長的資料量。專注於 AR 自動化滲透測試的領先 AI 原生網路安全公司已將我們的 SIEM 解決方案整合到其產品中。Elastic 將所有日誌集中管理，操作簡便，使其能夠輕鬆應對其大規模成長帶來的挑戰。

At the heart of these wins is the performance of our Search AI platform. We aren't just adding features. We are aggressively optimizing our engine, focusing our development efforts on delivering market-leading relevance, speed, and efficiency. In the last 18 months, we have driven two orders of magnitude less RAM required for vector search through innovations like better binary quantization or BBQ, disc BBQ, and our ACORN filtering algorithm among other things. This investment makes Elasticsearch vector search up to 8 times faster than Open search.

這些勝利的核心在於我們搜尋 AI 平台的出色表現。我們不僅僅是在添加功能。我們正在積極優化我們的引擎，將研發重點放在提供市場領先的相關性、速度和效率。在過去的 18 個月裡，我們透過改進二進位量化或 BBQ、磁碟 BBQ 以及我們的 ACORN 濾波演算法等創新，將向量搜尋所需的 RAM 減少了兩個數量級。這項投資使 Elasticsearch 的向量搜尋速度比 Opensearch 快 8 倍。

Our superior performance led to one seven-figure deal with a global heavy equipment manufacturer. The customer continues to migrate mission-critical workloads over to Elastic Cloud from OpenSearch to improve scalability and performance. They are relying on our platform to power their high-speed search for telemetry data collected via the StarLink network.

我們出色的業績為我們贏得了與全球重型設備製造商價值七位數的交易。客戶持續將關鍵業務工作負載從 OpenSearch 遷移到 Elastic Cloud，以提高可擴展性和效能。他們依靠我們的平台來高速搜尋透過 StarLink 網路收集的遙測資料。

By leveraging Logsdb, they have achieved a significant reduction in cloud costs while managing seven years of historical customer data. Our focus on performance extends to our partnership with NVIDIA as well where together, we help enterprises deploy AI applications faster without draining IT infrastructure.

透過利用 Logsdb，他們在管理七年歷史客戶資料的同時，顯著降低了雲端成本。我們對效能的關注也體現在我們與 NVIDIA 的合作中，我們共同幫助企業更快部署 AI 應用，而不會耗盡 IT 基礎架構。

We recently announced the technical preview of our Elasticsearch GPU plug-in for a GPU accelerated Vector database which allows for 12 times faster indexing. Additionally, the Dell AI data platform, now with NVIDIA and Elastic, delivers a tightly integrated AI stack that streamlines the ability to build, deploy, and scale AI. By making Elastic search a core component of the Dell and NVIDIA AI factories, we are meeting the critical demand for building AI on customer-controlled infrastructure. As we deepen these technical advantages, we strengthen our technical moat while removing friction from scaling AI.

我們最近發布了 Elasticsearch GPU 外掛程式的技術預覽版，該外掛程式支援 GPU 加速的 Vector 資料庫，索引速度可提升 12 倍。此外，戴爾 AI 資料平台（現已與 NVIDIA 和 Elastic 合作）提供了一個緊密整合的 AI 堆疊，簡化了 AI 的建置、部署和擴展能力。透過將 Elastic Search 作為戴爾和英偉達 AI 工廠的核心組件，我們滿足了在客戶控制的基礎設施上建立 AI 的關鍵需求。隨著我們不斷深化這些技術優勢，我們加強了技術護城河，同時消除了人工智慧擴展的阻力。

This quarter, we reached several product milestones designed to simplify the path from data to action for our customers. We are providing an end-to-end framework for building the next generation of intelligent applications.

本季度，我們實現了多個產品里程碑，旨在簡化客戶從資料到行動的路徑。我們正在提供一個端到端的框架，用於建立下一代智慧應用程式。

First, we officially launched the general availability of Agent Builder. Agent Builder allows developers to build secure, context-driven AI agents in minutes. Unlike consumer apps that serve the web, our focus is on internal business applications using company data. We piloted agent builder with a Global 100 financial group to investigate and troubleshoot its production infrastructure, demonstrating an order of magnitude improvement in performance for complex issues and democratizing the specialized expertise necessary for rapid troubleshooting.

首先，我們正式發布了 Agent Builder 的全面版本。Agent Builder 使開發人員能夠在幾分鐘內建立安全、情境驅動的 AI 代理程式。與面向網路的消費者應用程式不同，我們的重點是使用公司資料的內部業務應用程式。我們與一家全球 100 強金融集團合作，試用了代理構建器，以調查和排除其生產基礎設施的故障，結果表明，在解決複雜問題方面，性能提高了一個數量級，並且普及了快速故障排除所需的專業知識。

An international entertainment and media company created a [change] interface for customer interactions. They found the Agent Builder results to be significantly more reliable and accurate than the other LLM centric approaches they had tried.

一家國際娛樂和媒體公司創建了一個用於客戶互動的[更改]介面。他們發現 Agent Builder 的結果比他們嘗試過的其他以 LLM 為中心的方法可靠得多，也準確得多。

Building an agent is only half the battle. The other half is ensuring that agent has the most relevant information at its fingertips. This quarter, we expanded our Elastic influence service to include Jina AI's multilingual reranking models.

建立代理程式只是成功的一半。另一半則是確保代理人隨時取得最相關的資訊。本季度，我們將 Elastic 影響力服務擴展到了 Jina AI 的多語言重排序模型。

Jina AI delivers a best-in-class model for search accuracy with Jina v3 currently the number one ranker in its model size category on the MTEB-English retrieval benchmark, a gold standard for search and rag relevance. Jina AI's v5 Nano and v5 small models continue to outpace peers as well, scoring high in retriever, reranking and other tasks. By making these models available natively, we are allowing our customers to tune their AI applications for maximum precision and recall.

Jina AI 提供一流的搜尋準確率模型，Jina v3 目前在 MTEB-English 檢索基準測試中，在其模型規模類別中排名第一，該基準測試是搜尋和 rag 相關性的黃金標準。Jina AI 的 v5 Nano 和 v5 small 模型也繼續超越同類產品，在檢索、重新排序和其他任務中得分很高。透過提供這些原生模型，我們允許客戶調整其 AI 應用程序，以獲得最高的精確度和召回率。

[Rea] is the critical next step in a context engineering pipeline that ensures the most relevant data is presented to the LLM. Jina's state-of-the-art models delivered superior performance across over 80 languages.

[Rea] 是情境工程流程中的關鍵下一步，它確保將最相關的資料呈現給 LLM。Jina 的先進模型在 80 多種語言中都表現出色。

While AI provides the reasoning, enterprises still require the reliability of rule-based automation for critical business tasks. This is why we introduced Elastic Workflows in technical preview. Workflows adds automation capability directly into our platform, allowing agents to orchestrate actions across internal and external systems like Slack or ServiceNow. It moves Elastic from being a search box to a complete system of action.

雖然人工智慧可以提供推理能力，但企業仍需要基於規則的自動化來處理關鍵業務任務，以確保其可靠性。這就是我們推出彈性工作流程技術預覽版的原因。工作流程直接為我們的平台添加了自動化功能，使代理程式能夠協調跨內部和外部系統（如 Slack 或 ServiceNow）的操作。它將 Elastic 從一個搜尋框轉變為一個完整的作業系統。

Finally, we are delivering on our promise of hybrid flexibility with Cloud Connect for self-managed customers. We recognize that many of our largest customers, particularly in financial services and government maintain data on-premises for regulatory or sovereignty reasons. However, procuring and managing GPU hardware for AI is a massive hurdle for these teams. Cloud Connect allows customers to keep their data local while securely bursting to Elastic Cloud to leverage NVIDIA GPUs for high-performance inference. This ability to bridge modern AI capabilities with rigorous enterprise requirements is exactly why we are winning large-scale displacements against legacy providers. As organizations prioritize both innovation and operational efficiency, they're moving away from fragmented legacy tools in favor of Elastic's unified search platform.

最後，我們透過 Cloud Connect 為自管理客戶提供混合靈活性，兌現了我們的承諾。我們認識到，我們的許多大客戶，特別是金融服務和政府部門的客戶，出於監管或主權原因，將資料保存在本地。然而，對於這些團隊來說，採購和管理用於人工智慧的GPU硬體是一個巨大的挑戰。Cloud Connect 讓客戶將資料保留在本地，同時安全地擴展到 Elastic Cloud，以利用 NVIDIA GPU 進行高效能推理。正是這種將現代人工智慧能力與嚴格的企業需求結合的能力，讓我們能夠在大規模競爭中擊敗傳統供應商。隨著各組織將創新和營運效率放在首位，他們正在摒棄分散的傳統工具，轉而使用 Elastic 的統一搜尋平台。

The results of this quarter accelerating growth, large deal momentum and major competitive displacements, confirm that our strategy is resonating and that we are winning the race to become the essential infrastructure for the next generation of AI-powered businesses. I want to thank our customers for their partnership our shareholders for their trust and most importantly, our employees for their tireless spirit of innovation.

本季加速成長、大宗交易勢頭強勁以及主要競爭對手的更迭，都證實了我們的策略正在產生共鳴，我們正在贏得這場成為下一代人工智慧驅動型企業關鍵基礎設施的競賽。我要感謝顧客的合作，感謝股東的信任，最重要的是，感謝員工們孜孜不倦的創新精神。

With that, I will turn the call over to Navam to review our financial results in more detail.

接下來，我將把電話交給納瓦姆，讓他更詳細地回顧我們的財務表現。

Thank you, Ash. Good afternoon, everyone. We delivered yet another outstanding quarter. We outperformed the high end of revenue and profitability guidance ranges, driven by another quarter of consistent execution, strong consumption and strong customer commitments across search, security and observability. The momentum in our performance throughout this fiscal year is a testament to our team's ability to deliver rapid innovation and sales execution consistently quarter over quarter.

謝謝你，阿什。大家下午好。我們又完成了一個出色的季度。在搜尋、安全性和可觀測性領域，我們連續第二季保持穩定的執行力，強勁的消費需求和客戶的堅定承諾，推動我們超越了收入和盈利能力預期範圍的高端。本財年我們業績的持續成長動能證明了我們團隊有能力在每季持續實現快速創新和銷售執行。

The ongoing market demand we see is translating to total revenue growth, sales-led subscription revenue growth and healthy increases in pipeline generation to support our future growth. These factors together underscore our increasingly strategic value as a critical data platform in the age of AI. Our total revenue in the third quarter was $450 million, representing growth of approximately 18% as reported and 16% on a constant currency basis.

我們看到持續的市場需求正在轉化為總收入成長、銷售驅動的訂閱收入成長以及銷售管道的穩健成長，從而支持我們未來的成長。這些因素共同凸顯了我們在人工智慧時代作為關鍵數據平台日益增長的戰略價值。第三季總營收為 4.5 億美元，按報告匯率計算成長約 18%，以固定匯率計算成長約 16%。

Sales led subscription revenue in the third quarter was $376 million, growing 21% as reported and 19% on a constant currency basis. We saw commitment contribution from both our self-managed and cloud offerings, and aggregate consumption trends in the third quarter remained strong.

第三季度，銷售帶動的訂閱收入為 3.76 億美元，以報告匯率計算成長了 21%，以固定匯率計算成長了 19%。我們看到自架和雲端產品都做出了承諾貢獻，第三季的整體消費趨勢仍然強勁。

Our current remaining performance obligations, or CRPO, which is a portion of RPO that we expect to recognize as revenue within the next 12 months, cross the $1 billion mark for the first time in Q3. CRPO accelerated to approximately $1.06 billion, growing 19% as reported and 15% on a constant currency basis.

我們目前的剩餘履約義務（CRPO）是我們預計在未來 12 個月內確認為營收的 RPO 的一部分，在第三季首次突破 10 億美元大關。CRPO 加速成長至約 10.6 億美元，以報告匯率計算成長 19%，以固定匯率計算成長 15%。

In our consumption business, we structured customer contracts based on their annual usage. So our CRPO gives us a very clear view into the revenue we will recognize in the next 12 months, giving us visibility and confidence in our business.

在我們的消費業務中，我們根據客戶的年度使用量來制定客戶合約。因此，我們的 CRPO 可以讓我們非常清楚地了解未來 12 個月將確認的收入，從而增強我們對業務的可見度和信心。

As Ash mentioned, we saw a deal momentum continue in Q3. This quarter's strength was balanced across all geographies, and we continue to see customers make multiyear commitments this quarter which serves as a clear indicator of how our customers view the Elastic platform as a critical foundational element in their long-term data architectures. The positive momentum was reflected in our RPO. We saw strong growth of 22% in the quarter as reported and 18% on a constant currency basis. Our deal momentum is also evident in the growth of the count of customers with over $100,000 in annual contract value. We ended the third quarter with over 1,660 customers with ACV of more than $100,000, growing 14%. Quarter over quarter, we added approximately 60 net new $100,000 ACV customers.

正如 Ash 所提到的，我們看到交易勢頭在第三季度得以延續。本季各地區的業績均表現均衡，我們繼續看到客戶在本季做出多年承諾，這清楚地表明我們的客戶如何將 Elastic 平台視為其長期資料架構中的關鍵基礎要素。這種正向動能反映在我們的RPO（跑分率）。本季報告顯示成長強勁，達到 22%；以固定匯率計算，成長達 18%。我們的交易動能也體現在年合約價值超過 10 萬美元的客戶數量的成長。第三季末，我們擁有超過 1,660 位年合約價值超過 10 萬美元的客戶，成長了 14%。與上一季相比，我們新增了約 60 位年合約價值 10 萬美元的淨客戶。

We saw strong field execution and healthy growth across our solutions where search continues to see ongoing momentum from AI. This demand is benefiting both cloud and self-managed where both form factors are relevant for AI use cases. We continue to see customers taking a self-managed license and deploying Elastic into their own modern cloud and hybrid environments. The demand reflects customers' preference for Elastic, which uniquely provides necessary control and cost efficiency for AI initiatives.

我們看到，我們的解決方案在實際​​應用中表現出色，實現了健康成長，其中搜尋功能在人工智慧的推動下持續保持成長勢頭。這種需求對雲端和自架網站都有利，因為這兩種形式都適用於人工智慧應用場景。我們不斷看到客戶選擇自行管理許可證，並將 Elastic 部署到自己的現代雲端和混合環境中。這項需求反映了客戶對 Elastic 的偏好，Elastic 為人工智慧專案提供了獨特的控制和成本效益。

AI also continues to be a powerful catalyst for customer expansion. 28% of our greater than $100,000 cohort now utilizes Elastic for AI, which includes incremental AI capabilities like Attack Discovery and Agent Builder. Today, we are still in the early stages of expansion and we see considerable opportunity for ongoing upside for both new and existing customers to accelerate their AI adoption in the years ahead, particularly as they scale into and within our $100,000 ACV cohort.

人工智慧也持續成為推動客戶拓展的強大動力。在我們年收入超過 10 萬美元的客戶群中，有 28% 的客戶目前使用 Elastic for AI，其中包括攻擊發現和代理建構器等新增的人工智慧功能。今天，我們仍處於擴張的早期階段，我們看到，在未來幾年，無論是新客戶還是現有客戶，都有相當大的機會加速採用人工智慧，尤其是在他們擴展到我們年合約價值 10 萬美元的客戶群之後。

Now turning to third-quarter margins and profitability. I will discuss all measures on a non-GAAP basis. Our commitment to balancing growth with disciplined spending, translated into robust operating leverage and strong bottom line results. We continue to focus on cost and efficiency in our business. We recorded subscription gross margins of 82% and total gross margins of 78%, delivering an operating margin of 18.6%.

現在來看第三季的利潤率和獲利能力。我將討論所有非GAAP指標。我們致力於在成長和嚴格支出之間取得平衡，這轉化為強勁的營運槓桿和良好的獲利績效。我們將繼續專注於業務中的成本控制和效率提升。我們實現了 82% 的訂閱毛利率和 78% 的總毛利率，營業利潤率為 18.6%。

The outperformance on Q3 operating margin was the result of our strong revenue performance, the sustained leverage in our model as well as some Q3 expenses moving into Q4. Due to this outperformance, we now expect to see our full-year margins to come in slightly ahead than previously anticipated, with updated FY26 operating margin guidance now at 16.3%.

第三季營業利潤率的優異表現得益於我們強勁的營收表現、我們模型中持續的槓桿作用以及一些第三季支出進入第四季。由於這一優異表現，我們現在預計全年利潤率將略高於先前的預期，更新後的 2026 財年營業利潤率預期為 16.3%。

Regarding cash flow, adjusted free cash flow was approximately $54 million in Q3, representing a margin of approximately 12%. Our cash flows are expected to fluctuate on a quarterly basis based on the timing of bookings and collections related to the enterprise booking seasonality. So we continue to manage cash flow on a full year basis.

關於現金流，第三季調整後的自由現金流約 5,400 萬美元，利潤率約 12%。我們的現金流量預計會根據企業預訂季節性相關的預訂和收款時間按季度波動。因此，我們繼續以全年為基礎進行現金流管理。

For fiscal 2026, we do not see any change in our full year outlook, where we continue to expect to sustain the level of adjusted free cash flow margins that we achieved in fiscal 2025. We have made significant progress on the $500 million share repurchase program that we announced in October.

對於 2026 財年，我們的全年展望不會有任何變化，我們將繼續保持 2025 財年調整後自由現金流利潤率的水平。我們在10月宣布的5億美元股票回購計畫方面取得了重大進展。

During the third quarter, we returned approximately $186 million to shareholders, representing purchases of approximately 2.4 million shares. Cumulatively, we have repurchased 3.8 million shares. I mentioned at our Financial Analyst Day in October that we expect to use more than 50% of the $500 million authorized amount in fiscal 2026, and we have already exceeded this goal. As of the end of Q3, we have completed 60% of our repurchase program, and we are continuing our repurchase program here in Q4.

第三季度，我們向股東返還了約 1.86 億美元，相當於購買了約 240 萬股股票。累計至今，我們已回購了380萬股股票。我在 10 月的財務分析師日上提到，我們預計在 2026 財年將使用 5 億美元授權金額的 50% 以上，而我們已經超額完成了這一目標。截至第三季末，我們已完成 60% 的回購計劃，我們將繼續在第四季實施回購計劃。

Let's move to our outlook for the fourth quarter and the remainder of fiscal 2026. For the fourth quarter of fiscal 2026, we expect total revenue in the range of $445 million to $447 million, representing 15% growth at the midpoint or 13% constant currency growth at the midpoint. We expect sales-led subscription revenue in the range of $371 million to $373 million, representing 18% growth at the midpoint or 15% in constant currency growth at the midpoint.

接下來，我們展望一下2026財年第四季及剩餘時間的業績。我們預計 2026 財年第四季總營收將在 4.45 億美元至 4.47 億美元之間，以中間值計算成長 15%，以固定匯率計算成長 13%。我們預計以銷售為主導的訂閱收入將在 3.71 億美元至 3.73 億美元之間，以中間值計算成長 18%，以固定匯率計算成長 15%。

We expect non-GAAP operating margins to be approximately 14.5%. We expect non-GAAP diluted earnings per share in the range of $0.55 to $0.57, using between 105.5 million and 106.5 million diluted weighted average ordinary shares outstanding. Based on our fourth-quarter guidance, we are raising our full-year total revenue and sales led subscription revenue targets as well.

我們預計非GAAP營業利潤率約為14.5%。我們預計，根據 1.055 億至 1.065 億股稀釋加權平均流通普通股計算，非 GAAP 稀釋後每股收益將在 0.55 美元至 0.57 美元之間。根據我們第四季的業績預期，我們也提高了全年總收入目標和以銷售為主導的訂閱收入目標。

We expect total revenue in the range of $1.734 billion to $1.736 billion, representing approximately 17% growth at the midpoint or 15% constant currency growth at the midpoint. We expect sales-led subscription revenue in the range of $1.434 billion to $1.436 billion, representing 20% growth at the midpoint or 18% in constant currency growth at the midpoint.

我們預計總收入將在 17.34 億美元至 17.36 億美元之間，以中間值計算，成長率約為 17%，以固定匯率計算，成長率約為 15%。我們預計以銷售為主導的訂閱收入將在 14.34 億美元至 14.36 億美元之間，以中間值計算成長 20%，以固定匯率計算成長 18%。

We expect non-GAAP operating margin for full fiscal 2026 to be approximately 16.3%. We expect non-GAAP diluted earnings per share in the range of $2.50 to $2.54, using between 107 million and 108 million diluted weighted average ordinary shares outstanding.

我們預計 2026 財年全年非 GAAP 營業利益率約為 16.3%。我們預計，根據 1.07 億至 1.08 億股稀釋加權平均流通普通股計算，非 GAAP 稀釋後每股收益將在 2.50 美元至 2.54 美元之間。

A few other financial modeling points to keep in mind. The diluted weighted average shares outstanding reflect only share buybacks completed as of January 31, 2026. As you consider comparing sequential quarters, keep in mind that Q4 has three fewer days than we had in each of the first three quarters of the year, which creates a sequential headwind to revenue, which we have accounted for in our guidance. Also as is typical with prior Q4 periods, we expect to see seasonally higher expenses related to the timing of employee benefit costs.

還有一些其他的財務建模要點要注意。稀釋加權平均流通股數僅反映截至 2026 年 1 月 31 日完成的股份回購。在比較各季度之間的差異時，請記住，第四季度比今年前三個季度每個季度都少了三天，這會對收入造成環比不利影響，我們在業績指引中已經考慮到了這一點。與以往第四季的情況一樣，我們預期與員工福利成本的時間安排相關的費用將出現季節性上漲。

These expenses were already part of the guidance that we had initially laid out for the year. As in past years, we finalized our plans for the upcoming fiscal year during the fourth quarter, and we will provide our initial FY27 guide during our earnings call in May.

這些費用原本就包含在我們年初制定的年度預算指南中。與往年一樣，我們在第四季度最終確定了下一財年的計劃，我們將在 5 月的財報電話會議上提供 2027 財年的初步指導。

In summary, Q3 was another very strong quarter elastic. Consistent sales execution throughout FY26 continues to drive our sales-led subscription revenue growth expectations higher for the year, validating the durability of this business motion. As I said last quarter, while quarter revenue can naturally vary in a consumption model, our strong customer commitments drive strong annual growth.

總而言之，第三季依然是一個非常強勁的季度彈性。2026 財年持續穩定的銷售業績，不斷提升了我們對全年銷售驅動型訂閱收入成長的預期，驗證了這個業務模式的持久性。正如我上個季度所說，雖然在消費模式下季度營收自然會有波動，但我們強大的客戶承諾推動了強勁的年度成長。

Fueled by a highly differentiated platform and the expanding value we deliver to our customers, we remain on track to achieve our medium-term targets for both sales-led subscription revenue growth and adjusted free cash flow. Looking forward, we are confident in our ability to continue to drive profitable growth. We are the critical technology that accelerates data discovery, secures infrastructure, and maximizes application performance.

憑藉高度差異化的平台以及我們為客戶提供的不斷增長的價值，我們仍有望實現中期目標，包括銷售驅動的訂閱收入成長和調整後的自由現金流。展望未來，我們有信心繼續實現獲利成長。我們是加速資料發現、保護基礎架構和最大限度提高應用程式效能的關鍵技術。

With that, I'll open it up for Q&A.

接下來，我將開放問答環節。

(Operator Instructions)

（操作說明）

Sanjit Singh, Morgan Stanley.

桑吉特辛格，摩根士丹利。

Congrats on the stability that we're seeing across the business. Navam, I wanted to go back to some of the themes on the Investor Day a couple of months ago. There was a data point that you provided around the AI native customers or the AI customers being a relatively small amount of the customers in fiscal year '24, but driving an outsized degree of expansion, that's sort of year one to year two expansion.

祝賀公司整體業務的穩定發展。Navam，我想回顧一下幾個月前投資者日的一些主題。您提供的數據顯示，在 2024 財年，AI 原生客戶或 AI 客戶在客戶中所佔比例相對較小，但卻推動了不成比例的增長，這有點像是第一年到第二年的增長。

And so the gist of this question is, is that as we get to like 25% penetration of your $100,000 customer cohort, is there an opportunity here for growth to not just be stable, but actually to accelerate on a more sustained basis as we hit those critical tipping points, if you will?

所以這個問題的要點是，當我們達到 10 萬美元客戶群 25% 的滲透率時，是否有機會實現成長，不僅可以保持穩定，而且隨著我們達到這些關鍵的轉折點，成長還能以更持續的方式加速？

Yes. Thanks for the question, Sanjay. The trends that we laid out during the financial Analyst Day for the generative AI cohort, they remain the same. So we continue to perform well and we're seeing stronger growth on those generative AI cohorts today as it was when we disclosed it to you during Financial Analyst Day. So we're seeing these tailwinds right now, and we're seeing more of our customers reached the $100,000 mark.

是的。謝謝你的提問，桑傑。我們在金融分析師日上為生成式人工智慧群體提出的趨勢仍保持不變。因此，我們繼續保持良好的業績，並且與我們在金融分析師日上向您披露的情況一樣，我們看到這些生成式人工智慧群體如今成長勢頭更加強勁。所以我們現在看到了這些利多因素，我們看到越來越多的客戶達到了 10 萬美元的里程碑。

Now remember that each of these customers in the $100,000 mark are also early in their journey. So there's this other dimension of additional penetration and maturation in their own AI journey, which will drive faster growth as well. So we're seeing the tailwinds right now. We've seen tailwinds that average to 5%, but there's obviously more that there are some customers that have higher growth than that.

請記住，這些消費額達到 10 萬美元的客戶，也都處於消費歷程的早期階段。因此，他們在人工智慧發展歷程中還存在著進一步滲透和成熟這一另一個維度，這將推動更快的成長。所以我們現在正處於順風期。我們看到一些順風因素平均成長了 5%，但顯然也有一些客戶的成長率高於這個水準。

And to answer your question, yes, absolutely, there is a possibility. The art of the possible is there for us to actually accelerate beyond that 5% that we laid out during Financial Analyst Day, and the trends remain positive.

至於你的問題，是的，絕對有可能。我們完全有能力超越我們在金融分析師日上設定的 5% 的目標，而且發展趨勢仍然積極。

And Sanjit, just to add to that, that is exactly why we are so focused on the penetration of AI within our customer base. And as these customers right now, every quarter, you're seeing us increase the penetration. The penetration initially starts with them using us in some small way.

Sanjit，我還要補充一點，這正是我們如此專注於人工智慧在客戶群中的滲透的原因。而現在，每個季度，您都會看到這些客戶的滲透率正在提高。滲透最初是從他們以某種小方式利用我們開始的。

And as that usage grows, as you rightly pointed out, that's going to add to the consumption, it's going to add to the overall revenue, and that's going to show in the continued strength and acceleration of the business.

正如您所指出的，隨著使用量的成長，這將增加消費量，增加整體收入，這將體現在業務的持續強勁成長和加速發展上。

Understood. And maybe a question for you. You made the point in your script about vector search and vector databases are not enough in terms of building a resilient and powerful AI applications. And I think a lot of people would agree with that statement.

明白了。也許我有個問題想問你。你在腳本中指出，就建立具有彈性和強大功能的 AI 應用而言，向量搜尋和向量資料庫是不夠的。我想很多人都會同意這種說法。

So when we brand the company has a context engine, what are the core pieces that are mandatory to secure status as the leading provider of context for AI applications?

因此，當我們為公司打造一個擁有上下文引擎的品牌時，要確保成為人工智慧應用上下文的領先供應商，哪些核心要素是必不可少的？

That's a great question. I think the most important thing to keep in mind is context is going to change from task to task. And so the data platform, the context engineering platform that you provide needs to be able to do a whole bunch of things all together in a very consistent way. The first is the ability to bring in any and all kinds of data. And as you know, we have some unique capabilities in our ability to bring in not just structured information, but also unstructured really, really messy information.

這是一個很好的問題。我認為最重要的是要記住，任務的具體情況會因任務而異。因此，您提供的資料平台、情境工程平台需要能夠以非常一致的方式同時完成很多事情。首先是能夠導入任何類型的資料。如您所知，我們擁有一些獨特的能力，不僅可以匯入結構化訊息，還可以匯入非常非常混亂的非結構化訊息。

The second is to then take that data and convert it into vectors for vector search, which is a very powerful technique, especially in the AI world for semantic search, but then also to be able to mix it with hybrid search techniques.

第二種方法是將這些資料轉換為向量，用於向量搜尋。向量搜尋是一種非常強大的技術，尤其是在人工智慧領域進行語義搜尋時，而且還可以將其與混合搜尋技術結合。

That includes textual search and then being able to rerank against multiple techniques to get the most accurate context. So the Jina AI embedding models, the Jina AI Reranker models, those are a key part of their overall platform infrastructure. On top of it, then you need something that will allow you to assemble agents using all of these capabilities, and that's what Agent Builder was all about. As you know, it's a relatively new feature from us and a relatively new capability, but we are seeing great traction and adoption within our customer base.

這包括文字搜索，然後能夠根據多種技術進行重新排序，以獲得最準確的上下文。因此，Jina AI 嵌入模型、Jina AI 重排序模型是其整體平台基礎設施的關鍵部分。除此之外，你還需要一個能讓你利用所有這些功能來組裝代理的工具，而這正是 Agent Builder 的意義所在。如您所知，這是我們相對較新的功能，也是一項相對較新的技術，但我們看到它在我們的客戶群中獲得了極大的認可和應用。

Then on top of it, you need workflows because agents are not just about chat anymore. They're not just about conversations. They're about taking precise actions and that's where the workflow functionality that we released becomes really important.

此外，還需要工作流程，因為客服人員的工作不再只是聊天了。它們不僅僅是關於對話。它們旨在採取精準的行動，而我們發布的工作流程功能正是在這方面發揮了至關重要的作用。

And lastly, the ability to monitor all of this, and that's where our LLM observability functionality becomes key. So we believe that it's all of these capabilities, Sanjit, that taken together, make the platform a very compelling platform for context engineering.

最後，我們需要能夠監控所有這些，而這正是我們的 LLM 可觀測性功能的關鍵所在。所以我們相信，Sanjit，正是所有這些功能結合起來，使該平台成為一個極具吸引力的上下文工程平台。

And on top of that, we've also added our Elastic Inference service. So you don't need to bring your own LLM; we can help your proxy to any LLM of choice that you might want to use. We integrate with pretty much all of them.

除此之外，我們還加入了彈性推理服務。所以您無需自備法學碩士學位；我們可以幫助您的代理人獲得您選擇的任何法學碩士學位。我們幾乎與他們所有人都有合作。

Rob Owens, Piper Sandler.

羅布歐文斯，派珀桑德勒。

Great. I apologize upfront for the flurry of questions in one here, but I will keep it to one question, but maybe three parts. Really wanted to focus on the outperformance in other subscription. And I understand you're going to meet customers where they want to buy. So I guess, upfront, was some of that strength potentially push outs that you saw in the prior quarter?

偉大的。我先為一下子問這麼多問題表示歉意，但我會盡量只問一個問題，不過可能會分成三個部分。真正想重點關注的是其他訂閱服務的優異表現。我知道你們會去顧客想買的地方與他們見面。所以我想，首先，你認為上一季出現的某些強勁勢頭是否可能源自於業務下滑？

Then if I look at your sales-led subscription forecast for Q4 and the fact that it's down quarter over quarter, which you haven't seen historically, it's usually a little bit up. Is that really a function of the strength you saw here in the January quarter or something else to be read into that?

然後，如果我看一下你們第四季的銷售主導型訂閱預測，就會發現它環比下降，這在歷史上是從未發生過的，通常情況下都會略有上升。這真的是一月份季度強勁表現的結果，還是其他因素需要考慮？

And lastly, when we think about monetization of self-managed versus cloud customers and your ability to expand them over the coming years. Can you maybe articulate the difference between the two if there's much there. So again, I apologize for the three questions, but hopefully, they're brief answers.

最後，當我們考慮自管理客戶與雲端客戶的獲利模式以及您在未來幾年內擴展這些客戶的能力時。如果兩者之間有很大區別，您能否詳細說明一下？再次為這三個問題道歉，但希望答案簡潔明了。

Yes, Rob. Let me start. This is Ash. Let me start and then pass it on to Navam. In terms of our strength in self-managed, this is not just about pushouts or anything of that sort.

是的，羅布。我先開始。這是艾什。我先開始，然後交給納瓦姆。就我們自主管理的優勢而言，這不僅僅是指外包或類似的事情。

We are continuing to see a lot of strength in our self-managed business. At the end of the day, what we are seeing now, especially with AI is a lot of customers are applying AI on data that they consider to be extremely critical, extremely sensitive. This is not just with government customers. This is also in other regulated industries. And for that reason, they're choosing or they're preferring to keep the data where it's within their control, within their environment.

我們持續看到自主經營業務的強勁勢頭。歸根究底，我們現在看到的，尤其是在人工智慧領域，是許多客戶正在將人工智慧應用於他們認為極其關鍵、極其敏感的資料。這不僅僅是針對政府客戶。其他受監管行業也存在這種情況。因此，他們選擇或更傾向於將資料保存在自己能夠控制的環境中。

And that doesn't always mean in their own data centers. It might also mean within their own cloud VPCs and we give them the flexibility to be able to do that. So these are modern workloads, that continue to grow as that usage of AI grows, and we are going to continue to benefit from it, which is why we believe it is really important to not just look at cloud, but to look at the whole picture and take into account the strong growth that we are seeing even on self-managed.

但這並不總是意味著在他們自己的資料中心。這也可能意味著在他們自己的雲端 VPC 內，我們賦予他們這樣做的靈活性。所以這些都是現代工作負載，隨著人工智慧的使用不斷增長，這些工作負載也在不斷增長，我們將繼續從中受益，因此我們認為，真正重要的是不僅要關注雲，還要關注整體情況，並考慮到我們即使在自管理方面也看到的強勁增長。

And I'll let Navam address the other questions.

其他問題就交給納瓦姆來回答吧。

Yes, Rob, I'll address your quarterly sequential question. So overall, I'll start with how the business is doing. We're continuing to execute very well on the sales-led motion. This is another quarter of good execution from the sales side. And we saw that play out in our CRPO and RPO numbers accelerating as well.

是的，羅布，我會回答你每季提出的順序問題。所以總的來說，我先從公司目前的經營狀況說起。我們在銷售主導型策略方面持續保持良好的執行力。這是銷售方面又一個執行良好的季度。我們看到，CRPO 和 RPO 的成長速度也印證了這一點。

If you're looking at commitments, we're seeing a good commitment volume, and there's no deceleration on that. And on top of that, the pipeline is very healthy and growing each quarter. So overall, from a business perspective, very happy with where the quarter turned out and very positive about the future quarters as well. So that leads us to the guide. So when you think about the guide, we always guide with an appropriate amount of prudence on what we can achieve and outperform every quarter.

如果你看一下承諾情況，我們看到承諾量良好，而且沒有放緩的跡象。此外，產品線非常健康，並且每個季度都在成長。總的來說，從商業角度來看，我對本季的業績非常滿意，並且對未來的幾季也非常樂觀。所以這就引出了指南部分。所以，在製定業績指南時，我們總是會根據每個季度能夠達到和超越的目標，保持適當的謹慎態度。

So when you look about -- look at historical numbers versus actuals and guidance, you're comparing an actual number against the guidance number, and the guidance number has risk incorporated into that forward-looking projections. So I'll first point to that.

所以，當你觀察——觀察歷史數據與實際數據和指導數據時，你是在將實際數據與指導數據進行比較，而指導數據已經將風險納入了前瞻性預測中。所以我首先要指出這一點。

And the second point I'd make is that the fourth quarter has three less days, which translates to a 3% headwind or $14 million -- $14 million to $15 million headwind for us on a revenue basis because there's just less days of revenue to recognize. And all of that is incorporated in the guidance. And if you look at last year's Q4 guide or Q4 guidance in the past, there have been occasions where we've guided lower than the current quarter.

第二點是，第四季少了三天，這意味著收入將減少 3%，也就是 1,400 萬美元到 1,500 萬美元，因為需要確認的收入天數減少了。所有這些都已納入指導方針中。如果你看看去年的第四季業績指引或以往的第四季業績指引，你會發現我們曾經有過低於當季業績指引的情況。

So just keep that in mind, we continue to keep well on track with achieving our midterm targets and we feel very positive about the strength of the business itself.

所以請記住，我們繼續穩步推進中期目標的實現，並且我們對公司本身的實力感到非常樂觀。

Matt Hedberg, RBC.

Matt Hedberg，RBC。

Ash, I wanted to ask you about AI and obviously, we've all seen the pressure in the software market. And I appreciate your comments at the start of the past was really helpful, kind of get your perspective on AI. And it seems like there's a lot of great momentum from a customer perspective.

Ash，我想問你關於人工智慧的問題，顯然，我們都看到了軟體市場面臨的壓力。我很感謝您之前的評論，真的很有幫助，讓我了解了您對人工智慧的看法。從客戶的角度來看，似乎勢頭非常強勁。

I guess my question is, when we're looking at these frontier models, do you see them as future competition or more of a partnership opportunity?

我想問的是，當我們審視這些前沿模型時，您認為它們是未來的競爭對手，還是更傾向於合作機會？

Really, we don't -- in our opinion, AI doesn't displace us, it really depends on us. Because if you think about these frontier models, there are amazing reasoning engines. Like the way I think about them is they are going to be the operating systems of tomorrow.

真的，我們並不這麼認為——在我們看來，人工智慧不會取代我們，它實際上取決於我們。因為如果你仔細想想這些前沿模型，你會發現它們擁有令人驚嘆的推理引擎。我認為它們將會是未來的作業系統。

But just as operating systems today also require data systems to feed appropriate data and context to these operating systems to actually build applications with, you're going to need the same thing going forward. And our role in this whole ecosystem is to make sure that we can very quickly in real time across all of the petabytes of data that every organization holds give the right context to these LLM so they can do their job. And that's the reason why I believe that in the world of tomorrow, you're going to have agents talking to each other.

但正如今天的作業系統也需要資料系統向這些作業系統提供適當的資料和上下文，以便實際建立應用程式一樣，未來你也需要同樣的東西。我們在整個生態系統中的作用是確保我們能夠非常快速地即時處理每個組織擁有的所有PB級數據，為這些LLM提供正確的上下文，以便它們可以發揮作用。這就是為什麼我相信在未來的世界裡，特工之間會互相溝通。

You're going to have agents that you build with Elastic agent builders that are talking to cloud cowork, that are talking to things that you build with open AI frontier and we already support the MCP protocols, the A2A protocols that allow for that kind of communication. So this is a world where we feel that the fact that we have this tremendous position, the capabilities with our vector database, the capabilities with our entire context engineering platform to become a critical part of the infrastructure going forward.

您可以使用 Elastic Agent Builder 建立代理，這些代理可以與 Cloud Cowork 通信，也可以與您使用 OpenAI Frontier 建立的事物通訊。我們已經支援 MCP 協議和 A2A 協議，從而實現這種通訊。因此，我們認為，憑藉我們強大的實力、向量資料庫的能力以及整個上下文工程平台的能力，我們有能力成為未來基礎設施的關鍵組成部分。

And we're already partnering with hyperscalers, and we already integrate with all of these frontier class models today.

我們已經與超大規模資料中心營運商建立了合作關係，並且目前已經與所有這些前沿模式進行了整合。

It's a great perspective. And then maybe just one quick follow-up about Elastic internally using AI how are you seeing some of the tangible benefits? And how might that impact head count in the future?

這是一個很棒的視角。最後，能否再快速問一下 Elastic 內部使用 AI 的情況？您認為有哪些實際的好處？那這會對未來的員工人數產生什麼影響呢？

Yes. Look, we are all in on AI, not just in terms of what we are doing externally in terms of providing the platform that we are building, but also in terms of how we are using AI internally. Just to give you some context on this, a couple of years ago, we built out our first agent, our first support agent within the company and that's been in production for a long time now.

是的。你看，我們全力投入人工智慧，不僅體現在我們對外提供的平台建置方面，也體現在我們內部對人工智慧的應用。為了讓大家更了解情況，幾年前，我們建構了公司內部的第一個代理，也就是第一個支援代理，而且它已經投入生產很長時間了。

It's what our customers first hit when they have support questions and the amount of queries it's able to answer and the number of support tickets it's able to deflect has not only improved the overall performance, the overall experience for our customers when they come to us for support, but it has also significantly reduced the demand on head count from our side.

這是我們的客戶在遇到支援問題時首先接觸到的系統，它能夠回答的問題數量和能夠處理的支援工單數量不僅提高了整體性能，改善了客戶尋求支援時的整體體驗，而且還大大減少了我們這邊的人力需求。

So in the last two years, even as our business has been growing, and as you can imagine, typically support workloads grow with the business, we have been able to manage that workload growth without adding any head count to that support team.

因此，在過去的兩年裡，儘管我們的業務一直在成長，正如您所想，通常支援工作量也會隨著業務的成長而成長，但我們能夠在不增加支援團隊任何人員的情況下管理這種工作量的成長。

In other parts of the business, whether it's in HR, whether it's in finance, in legal, we are heavily using AI tools. Some of these are built on our stack. Some of them might be external products that we are leveraging. And even in engineering, we are finding tremendous value in using multiple different code generation tools that we use within the company.

在公司的其他部門，無論是人力資源部、財務部或法務部，我們都在大量使用人工智慧工具。其中一些是基於我們的技術棧構建的。其中一些可能是我們正在利用的外部產品。即使在工程領域，我們也發現使用公司內部多種不同的程式碼產生工具具有巨大的價值。

So overall, we believe that this is going to definitely help us not just accelerate the pace of innovation, which we're already seeing now but also improve the productivity and improve the overall efficiency of the business. And that's what's exciting about this. We are able to help our customers with this, but we're also able to benefit from it ourselves.

總的來說，我們相信這不僅會幫助我們加快創新步伐（我們現在已經看到了這一點），而且還會提高生產力，提高企業的整體效率。這就是它令人興奮的地方。我們能夠幫助客戶做到這一點，但我們自己也能從中受益。

Brian Essex, JPMorgan.

Brian Essex，摩根大通。

I appreciate your response to the last question with regard to your vector database capabilities and content engineering platform. I guess as you look at the changing landscape and you look at different approaches, different ways to think about things?

感謝您對最後一個問題（關於您的向量資料庫功能和內容工程平台）的回應。我想，當你觀察不斷變化的環境，並審視不同的方法、不同的思考方式時，你會怎麼想呢？

Are there any -- anything -- how do we think about the platform and its ability to adhere to some of those approaches, like, for example, the page index approach to RAG. You -- if they saw the cost and latency issues involved with that approach, are you well positioned to benefit from something like that and pivot with your approach?

有沒有什麼——任何——我們該如何看待這個平台及其遵守某些方法的能力，例如，頁面索引方法與 RAG 的比較。如果他們看到了這種方法所涉及的成本和延遲問題，你是否能夠從中受益並調整你的方法？

Yes. Look, RAG, retrieval augmented generation itself has progressed a lot since the last several years when it was first introduced as a concept -- but fundamentally, this comes down to finding the most appropriate context that is relevant for the LLM to do its job. Sometimes that requires you to understand specific data relationships that might exist. Sometimes it requires you to just search through all of your data. Sometimes it requires you to understand specific things, things like preferences and so on that you might have captured in other data systems and it's an amalgamation of all of this.

是的。你看，RAG，檢索增強生成本身自幾年前首次作為一個概念提出以來已經取得了很大的進步——但從根本上講，這歸根結底是找到與LLM工作相關的最合適的上下文。有時，這需要你了解可能存在的特定數據關係。有時候，你需要搜尋所有數據。有時，它需要你了解一些具體的事情，例如你可能在其他資料系統中記錄的偏好等等，它是所有這些的融合。

And as RAG continues to evolve, as these techniques become more and more sophisticated, we are actually on the leading front of capturing more than one single technique into our platform. We were one of the first to adopt hybrid search, and we were the first to talk about it. And since then, we have continued with that kind of momentum. So absolutely, I feel very, very confident that we're going to be on the bleeding edge. This is, at the end of the day, what Elastic was born to do, we've always been in the business of relevance.

隨著 RAG 不斷發展，這些技術也變得越來越複雜，我們實際上正處於將不只一種技術整合到我們平台的前沿。我們是最早採用混合搜尋技術的公司之一，也是最早談論混合搜尋技術的公司之一。從那時起，我們就一直保持著這種發展勢頭。所以，我絕對非常有信心，我們將處於技術的最前沿。歸根究底，這就是 Elastic 的使命所在，我們一直致力於提供相關性服務。

Without relevance, you don't get good search. Without relevance, you don't get good accurate AI.

如果搜尋結果不相關，就無法獲得好的搜尋結果。如果沒有相關性，就無法獲得好的、精準的人工智慧。

Great. That's super helpful. Maybe just one quick follow-up. Any traction from the recent [indiscernible] win that you had, are any Fed agencies leveraging that for SIEM referenceability? And are you seeing better activity on the back of that win? It's been a great success.

偉大的。這太有幫助了。或許只需要一個簡短的後續問題。您最近取得的[無法辨認的]勝利有任何進展嗎？是否有任何聯邦機構利用它來提高 SIEM 的參考性？那場勝利之後，你的業務活動是否有改善？非常成功。

Yes. Thank you. It's been a great success for us already. I think we mentioned it in our press release as well. That SIEM as a service with [CIS] continues to grow and we saw additional agencies coming on board even in Q3.

是的。謝謝。這對我們來說已經取得了巨大的成功。我想我們在新聞稿中也提到了這一點。SIEM 即服務與 [CIS] 的結合持續成長，我們在第三季也看到了更多機構加入。

So I would expect that CSI to be just the beginning of multiple agencies coming onto that service over the next several quarters. And fundamentally, [CISA] is considered to be the primary agency responsible for cybersecurity in the civilian government in the United States. And that just -- that kind of endorsement is something that goes a long way. So it's a very exciting win. Like I said, we are going to benefit from it for many quarters and many years to come.

因此，我預期 CSI 只是一個開始，未來幾季會有多個機構加入這項服務。從根本上講，[CISA] 被認為是美國民用政府網路安全的主要負責機構。而這種認可——這種認可意義重大。這是一場非常激動人心的勝利。正如我所說，我們將在未來的許多季度和許多年裡從中受益。

Brent Thill, Jefferies.

布倫特‧蒂爾，傑富瑞集團。

Ash, just on the CRPO, 15% constant currency, 15% last quarter. I guess I mean, good mid-teen growth, but I think everyone is asking why aren't we seeing a faster inflection?

Ash，僅以 CRPO 計算，以固定匯率計算為 15%，上季為 15%。我的意思是，青少年中期發展良好，但我認為每個人都在問，為什麼我們沒有看到更快的成長？

I know you have a true north of 20%. It seems like the numbers support that you can accelerate to 20%. But just curious kind of how you bridge to 20% and perhaps why maybe you're not seeing a little bit stronger AI tailwind in the near term?

我知道你的真北緯度是 20%。數據顯示，加速到 20% 似乎是正確的。但我很好奇，您是如何達成 20% 的目標的？或許您認為短期內人工智慧的發展動能不會更強勁？

Yes. Thanks for the question, Brent. So I'll start. CRPOs crossed over $1 billion. We're at 19% growth right now; RPOs at 22% growth.

是的。謝謝你的提問，布倫特。那我先來。CRPO 金額突破 10 億美元。我們目前的成長率為 19%；RPO 的成長率為 22%。

That's the best we've seen in two years, and we're very happy with the progress that we're making. And if you just look at the absolute dollar additions that we added in the quarter, it's progressing very, very well.

這是兩年來我們取得的最佳成績，我們對目前的進展感到非常滿意。如果只看本季新增的絕對美元金額，就會發現進展非常非常順利。

So that's all pointing to the core things that are driving that CRPO growth, which is strong customer commitments, which now we've been talking about for a couple of quarters now, and it's been yet another quarter of good very good sales execution leading to strong customer commitments.

所以這一切都指向了推動 CRPO 成長的核心因素，那就是強大的客戶承諾。我們已經連續幾個季度談論這一點了，而這又是一個銷售執行非常出色，從而帶來強大客戶承諾的季度。

So the AI tailwinds we talked about during Financial Analyst Day, we're seeing them right now, and they are continuing to grow as we see more and more of the 100,000 have -- or adopt AI workloads from us. So we're -- we think that there's a good strong trajectory from this point ahead as we see more AI penetration among our $100,000 customer base.

因此，我們在金融分析師日上談到的人工智慧順風，我們現在正在看到它們，而且隨著越來越多的 10 萬家公司擁有或採用我們的人工智慧工作負載，它們還在繼續成長。所以我們認為，從現在開始，隨著人工智慧在我們年收入 10 萬美元的客戶群中滲透率的提高，未來將呈現良好的發展勢頭。

The other thing that I will say to this, Brent, is that if you look at the full year guide for sales net subscription revenue, you can see that the strength in our business continues. And look, for us, the midterm guide that we laid out is not the place where we end up the place that we believe we can go beyond that. If you remember, we talked about 20% plus.

布倫特，我還要補充一點，如果你看一下全年的銷售淨訂閱收入指南，你會發現我們業務的強勁勢頭仍在持續。而且，對我們來說，我們所設定的中期目標並不是我們最終的目標，我們認為我們可以超越這個目標。如果你還記得的話，我們討論過20%以上的幅度。

And really, that's the way we see it. So as more and more customers adopt our AI functionality, given the fact that those cohorts tend to grow and expand faster, we feel very, very good about how we are tracking to that midterm, and we feel very good about the fact that as that traction continues, we feel good about even exceeding what we've talked about in the past.

而事實上，我們就是這麼看的。因此，隨著越來越多的客戶採用我們的 AI 功能，考慮到這些群體往往增長和擴張得更快，我們對中期目標的進展感到非常非常滿意，並且我們非常有信心，隨著這種增長勢頭的持續，我們甚至有望超越我們過去所談論的目標。

Howard Ma, Guggenheim.

Howard Ma，古根漢。

Great. I wanted to ask about cloud. And I guess this one's for Navam, I want to throw a caveat first, which is that I appreciate your deployment agnosticism and fewer days in Q4. When I look at cloud revenue in Q4 versus Q3 in FY22 and earlier, there was more of a sequential step-up than in FY23 through FY25, which were obviously impacted by you had industry-wide cloud optimization. Also Elastic had company-specific go-to-market issues.

偉大的。我想問一下關於雲端運算的問題。我想這番話是說給 Navam 聽的，首先我想說明一點，那就是我很欣賞你對部署方式的開放態度，以及第四季度較少的部署天數。當我查看 2022 財年及以前第四季和第三季的雲端收入時，發現其環比成長幅度比 2023 財年至 2025 財年更大，這顯然受到了全產業雲端優化的影響。此外，Elastic 也存在一些公司特有的市場推廣問題。

But now that the go-to-market execution has improved significantly. And given the visibility that you now have into how large customers ramp consumption relative to the commits, and that includes some of the $10 million-plus TCV contracts that you signed last quarter. The question is, is there any reason why the sequential cloud growth in Q4 would not be more in line with the earlier years?

但現在市場推廣執行情況已顯著改善。鑑於您現在可以清楚地了解大客戶如何根據承諾增加消費，其中包括您上個季度簽署的一些超過 1000 萬美元的總合約價值 (TCV) 合約。問題是，第四季雲端業務的環比成長為何沒有與往年同期水準更加一致？

So I'll start off with what I always start off on, which is sales-led subscription revenue growth is the right metric for you to focus on in measuring us as a barometer as the success of the company and the barometer of success of the company.

所以，我首先要說的就是我一直以來都會說的，那就是以銷售為主導的訂閱收入成長是衡量我們公司成功與否的正確指標，也是你們應該關注的指標。

And I talked about this during our prepared remarks as well. There's multiple examples including this quarter of AI workloads being sold as self-managed and deployed either in the customer's cloud or in their hybrid environments. So sales-led subscription grew a healthy 21% this year.

我在事先準備好的發言稿中也談到了這一點。包括本季在內，有許多人工智慧工作負載以自管理的方式出售，並部署在客戶的雲端或混合環境中。因此，今年以銷售為主導的訂閱模式實現了21%的健康成長。

If you look at just cloud and the number there again is what is the sales-led cloud number, that grew 27% year over year this quarter. So we're seeing very good traction on the metric that we matter -- metric that matters to us, which is sales-led subscription revenue. And also on the annual cloud number this quarter was very good as well at 27%. The forward quarters -- number one, you have three less days, so that's three less days to focus on. The forward quarter is a risk-adjusted number. So you can't really compare an actual to a guidance number.

如果只看雲端運算，那麼銷售主導的雲端運算業務量在本季同比增長了 27%。因此，我們在我們重視的指標（即銷售驅動的訂閱收入）方面取得了非常好的進展。此外，本季年度雲量數據也非常好，達到 27%。前幾季－第一，你們少了三天時間，所以需要集中精力的時間也少了三天。遠期季度數據是經過風險調整後的數值。所以實際數值和指導值根本無法直接比較。

But the point I'd like to make is that we're seeing very strong commitments and very strong performance on sales led.

但我想強調的是，我們看到銷售主導型企業展現了非常強勁的投入和非常出色的業績。

Ryan MacWilliams, Wells Fargo.

瑞安‧麥克威廉斯，富國銀行。

This is [Dusan] on for Ryan MacWilliams. I wanted to ask, it really seems that based on some of the work we've been doing that the number of agents and AI services and production have really increased over the past couple of months. And I wanted to hear from you what you're seeing within your customers? Like are you seeing the types of AI use cases broaden out compared to what you were seeing maybe 2 quarters ago how that's impacting usage and spend amongst those customers?

這是杜桑替補瑞安麥克威廉斯上場。我想問一下，根據我們所做的一些工作來看，過去幾個月裡，代理商、人工智慧服務和生產的數量似乎確實增加了。我想聽聽你們從客戶那裡觀察到的情況？您是否觀察到人工智慧的應用場景類型與兩個季度前相比有所擴大？這種擴大對客戶的使用情況和支出有何影響？

Yes, we are seeing the usage broaden out in the sense that we are seeing more and more variety of use cases that involve AI. Eight quarters ago, the bulk of what we were seeing was only around vector databases, vector search, hybrid search, semantic search, it was mostly around the chat style interface kind of work.

是的，我們看到人工智慧的應用範圍正在擴大，涉及人工智慧的應用案例也越來越多。八個季度前，我們看到的大部分內容都圍繞著向量資料庫、向量搜尋、混合搜尋、語義搜索，主要都是圍繞著聊天式介面之類的工作。

Now we are seeing agentic workflows being put together not just around what you would typically think of as search-related workflows but also around security workflows, around observability workflows. And that was the reason why we gave the stat around our total count of customers using us for various AI use cases beyond just vector database. And that includes things like Agent Builder. That includes things like Attack Discovery.

現在我們看到，代理工作流程不僅圍繞著你通常認為的搜尋相關工作流程構建，而且還圍繞著安全工作流程、可觀測性工作流程構建。這就是為什麼我們統計了使用我們服務的客戶總數，這些客戶將我們的服務用於各種人工智慧用例，而不僅僅是向量資料庫。這其中就包括 Agent Builder 之類的工具。這包括攻擊發現之類的功能。

And in these kinds of scenarios, people are trying to automate their workflows, their cybersecurity workflows for detection, for remediation, they're trying to do the same for SRE workflows around absorbability. So the variety of use cases is growing. And as that grows, we see an opportunity not just in our core search business, but also in the work that we're doing in security and observability.

在這種情況下，人們正在嘗試自動化他們的工作流程，包括網路安全檢測和補救工作流程，他們也正在嘗試對 SRE 工作流程進行相同的自動化，以提高其可吸收性。因此，應用場景的種類正在不斷增加。隨著這一趨勢的發展，我們不僅在核心搜尋業務中看到了機遇，而且在安全性和可觀測性方面也看到了機會。

Miller Jump, Truist Securities.

Miller Jump，Truist Securities。

Congrats on the sales led momentum. Ash, you mentioned a MongoDB competitive win in the prepared remarks. We haven't heard as much about this head-to-head between the two of you until fairly recently.

恭喜你們取得銷售成長動能。Ash，你在準備好的演講稿中提到了MongoDB在比賽中獲勝。直到最近，我們才開始聽到一些關於你們兩人之間正面交鋒的消息。

So are you seeing MongoDB increasingly in bake-offs as customers look to build AI apps? Or is that more of a one-off?

所以，隨著客戶尋求建立人工智慧應用程序，您是否越來越多地看到 MongoDB 在競標中被採用？還是這只是個特例？

No, this was a situation where the customer had started to use that technology for a basic search application. They had some issues scaling it and as they were trying to build a more scalable solution, especially for hybrid search, they realized that they needed something that could perform and that was the customer win that I talked about.

不，這種情況是客戶開始將該技術用於基本的搜尋應用程式。他們在擴展規模方面遇到了一些問題，當他們試圖建立一個更具可擴展性的解決方案時，特別是對於混合搜索，他們意識到他們需要一些能夠有效運行的東西，這就是我所說的客戶成功案例。

At the end of the day, where we tend to typically play is in the area of unstructured data. We don't tend to see them as much. But from time to time, you do see these kinds of situations.

歸根究底，我們通常從事的領域是非結構化資料。我們不太常見到他們。但偶爾還是會看到這類情況。

And if I could just ask a quick follow-up for Navam. As large deals are becoming more of a contributor in your go-to-market strategy, moving upmarket, can you just remind us how you're handling those large deals in your guidance process? And any considerations around seasonality there?

我可否再問一下關於納瓦姆的一個小問題？隨著大宗交易在您的市場推廣策略中扮演越來越重要的角色，並逐步向高端市場邁進，您能否提醒我們一下，在您的指導過程中，您是如何處理這些大宗交易的？那麼，這方面是否需要考慮季節性因素呢？

Yes. Seasonality wise, I think it just follows the normal typical enterprise seasonality pattern where they end up being more tail end weighted in Q3 and Q4. But we talked about large deals in the last quarter. They happen every quarter. It's just the volume of bookings are bigger and towards the tail end of the year.

是的。從季節性角度來看，我認為這只是遵循正常的典型企業季節性模式，即第三季和第四季的業績會更加突出。但我們上個季度談的是大宗交易。這種情況每季都會發生。只是預訂量更大，而且都集中在年底。

In terms of how we handle it, I think that this is a natural byproduct of just being successful with our customers, particularly the larger customers within the [G2K]. So we welcome it. When we look at our guidance and what we expect the full year to be, we naturally take a haircut on specific deals that could move from one quarter to another. So that's how we incorporate it into our guidance, a risk-adjusted number on not actually counting on everything going our way.

至於我們如何處理這個問題，我認為這只是我們在服務客戶方面取得成功，特別是服務大型客戶方面取得成功的自然結果。[G2K]所以我們表示歡迎。當我們審視我們的業績指引和對全年的預期時，我們自然會對可能從一個季度轉移到另一個季度的特定交易做出相應的調整。所以，這就是我們將其納入指導原則的方式，即一個經過風險調整的數字，而不是指望所有事情都如我們所願。

Koji Ikeda, Bank of America.

池田浩二，美國銀行。

This is [George Marian] on for Koji. I appreciate you guys taking our questions today. I wanted to ask just in the conversations that you guys have with customers and their strategy around adopting AI. How would you say that the tone and the conversations differ versus a year ago? And what kind of inning are they in today versus maybe a year ago in the adoption journey with Elastic?

這是喬治·馬里安對上小次郎。感謝各位今天回答我們的問題。我想問的是，你們與客戶的對話以及你們在採用人工智慧方面的策略。您認為現在的語氣和對話與一年前有何不同？與一年前相比，他們目前在採用 Elastic 的過程中處於什麼階段？

The general tone is definitely one of greater enthusiasm for AI. I think there's been enough proof points now for AI helping in all kinds of use cases, whether it be around code development, whether it be around customer support, in legally discovery, like lots and lots of use cases across all functions. And so we are seeing the conversations be less evangelism and more about helping them put together these kinds of sophisticated agentic application. So there's definitely been maturity.

整體基調無疑是對人工智慧更加熱情。我認為現在已經有足夠的證據表明人工智慧可以在各種用例中提供幫助，無論是程式碼​​開發、客戶支援、法律取證，還是其他各種功能中的眾多用例。因此，我們看到對話不再是佈道，而是幫助他們建立這類複雜的代理應用程式。所以，他們確實成熟了。

In terms of the total number of these agents that people have within their organization, that number is still in the early days. Like if you think about the total number of business processes and workflows that can be automated by AI, I think you have to be realistic that we are still in the early days because AI just is a pretty powerful and transformative capability.

就人們組織內部擁有的這類代理人的總數而言，這個數字仍處於早期階段。想想看，人工智慧可以自動化多少業務流程和工作流程，我認為你必須現實一點，我們仍處於早期階段，因為人工智慧確實是一項非常強大且具有變革性的能力。

And what you can do with these LLM in terms of reasoning can be applied to many, many different functions and different work processes. So we believe that the opportunity is still very significant and still ahead of us.

而你運用這些LLM所掌握的推理能力，可以應用在許多不同的職能和不同的工作流程。所以我們相信，機會依然非常寶貴，還在我們面前。

Mike Cikos, Needham.

麥克·西科斯，尼德姆。

This is Matt Calitri on for Mike Cikos over at Needham. With all the advancements you're making to search with things like the Jina Reranker models, are you able to charge customers more? Or is the improved speed and accuracy more of an acquisition vehicle?

這裡是 Matt Calitri，替 Mike Cikos 在 Needham 為您報道。鑑於你們在搜尋方面取得的所有進步，例如 Jina Reranker 模型，你們是否可以向客戶收取更高的費用？或者說，速度和精度的提高更多是作為一種目標獲取手段？

So we do charge in terms of consumption, right? So we have a consumption model, as you know. So pretty much everything that you do on our platform. It's metered and effectively based on compute, based on storage and so on. And for anything that's LLM or model related, it's based on tokens.

所以我們是按消費量收費的，對吧？如你所知，我們有一個消費模式。所以基本上你在我們的平台上做的所有事情。它是按流量計費的，實際上是根據運算能力、儲存空間等因素來計算的。而所有與LLM或模型相關的內容，都是基於代幣的。

And all of our pricing is sort of public on our pricing pages, but yes, with these newer models, we are monetizing everything. And as the usage continues to grow, as customers do more and more on our platform, that is what drives revenue for us.

我們所有的定價都在定價頁面上公開透明，但沒錯，對於這些新型號，我們正在將一切都變得貨幣化。隨著用戶數量的持續成長，客戶在我們平台上進行的操作越來越多，這正是我們收入的來源。

Got it. Very helpful. And then maybe just taking a different slice at the guidance question here. So you beat on the 3Q guide in constant currency, and then you raised the constant currency guide for sales led subscription revenue, but you left constant currency unchanged for the full year guide. And I can appreciate the three fewer days and the risk adjusted, but that would have been baked into the prior guide.

知道了。很有幫助。然後，或許可以從另一個角度來探討這個指導性問題。所以，你提高了以固定匯率計算的第三季業績預期，然後提高了以固定匯率計算的銷售驅動型訂閱收入預期，但全年業績預期（以固定匯率計算）保持不變。我能理解減少三天時間和風險調整，但這在先前的指南中已經考慮到了。

Can you just help walk through the mechanics there of why that wouldn't have increased?

你能幫我解釋為什麼這種情況不會發生嗎？

Yes. I mean it's quite simple. The number that we care about is sales-led subscription revenue. We handily beat that number this quarter. And we raised more than we beat.

是的。我的意思是，這很簡單。我們關注的數字是銷售驅動的訂閱收入。本季我們輕鬆超過了這個數字。我們籌集的資金比我們贏得的資金還要多。

That's a reaction of what we think is happening with the business and the sort of the positive momentum that we're seeing on the sales line. So overall, what we -- we're not thinking about it too much more than we feel good about the forward momentum of sales led subscription revenue, and we beat the number, and we're raising more than we be.

這是我們對公司業務發展現狀以及銷售方面積極勢頭的一種反應。所以總的來說，我們——我們沒有過多考慮這個問題，只是對銷售驅動的訂閱收入的成長勢頭感到滿意，我們超額完成了目標，而且籌集的資金也超過了預期。

Eric Heath, KeyBanc Capital Markets.

Eric Heath，KeyBanc Capital Markets。

Showing no further questions, this concludes our question-and-answer session. I would like to turn the conference back over to Ash Kulkarni for any closing remarks.

由於沒有其他問題，我們的問答環節到此結束。我謹將會議交還給阿什·庫爾卡尼先生，請他作總結發言。

Thank you all for joining us today. We at Elastic are very proud of our business results and excited about the opportunity ahead. Thank you.

感謝各位今天蒞臨。Elastic 的全體員工都為我們所取得的業績感到非常自豪，並對未來的機會感到興奮。謝謝。

The has now concluded. Thank you for attending today's presentation. You may now disconnect.

會議現已結束。感謝各位參加今天的報告會。您現在可以斷開連線了。