Elastic N.V. (ESTC) 2027 Q1 法說會逐字稿

Good afternoon And welcome to the elastic first-quarter fiscal 2027 earnings results conference call. (Operator Instructions) Please note this event is being recorded.

下午好，歡迎參加 Elastic 2027 會計年度第一季財報結果電話會議。(接線員指示) 請注意，本活動將被錄音。

I would now like to turn the conference over to Alex Kurtz, Vice President of Investor Relations. Please go ahead.

現在我想把會議交給投資人關係副總裁 Alex Kurtz。請開始。

Good afternoon, and thank you for joining us on today's conference call to discuss Elastic's first-quarter fiscal 2027 financial results. On the call, we have Ash Karney, Chief Executive Officer; and Navam Welihinda, Chief Financial Officer.

下午好，感謝各位參加今天的電話會議，一同討論 Elastic 2027 會計年度第一季財務結果。今天與會者包括執行長 Ash Karney，以及財務長 Navam Welihinda。

Following the prepared remarks, we will take questions. A press release was issued today after the close of the market and it's posted on our website. Slides which are supplemental to the call can also be found on Elastic Investor Relations website at ir.elastic.com.

在事先準備的發言之後，我們將進行問答。我們已於今日收盤後發布新聞稿，並已張貼於公司網站。作為本次電話會議補充資料的簡報，也可在 Elastic 投資人關係網站 ir.elastic.com 找到。

Our discussion will include forward-looking statements, which may include predictions, estimates, our 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, speaks only as of 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 forward-looking statements, unless required by law. 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 of the Securities and Exchange Commission.

我們的討論將包含前瞻性陳述，可能包括預測、估計、我們對產品與解決方案需求的預期，以及未來營收與其他資訊。這些前瞻性陳述係基於我們目前所知因素，僅截至本次電話會議當日有效，並受各種風險與不確定性影響，可能導致實際結果與前述陳述存在重大差異。除非法律要求，我們不承擔更新任何前瞻性陳述的義務。請參閱我們今日稍早發布之新聞稿所載的風險與不確定性、投資人關係網站所張貼簡報中的相關內容，以及我們向美國證券交易委員會提交文件中更完整的說明。

We'll 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 the slides. Unless specifically noted otherwise, all results and comparisons are on a fiscal year-over-year basis. Webcast replay of this call will be available on our company website under the Investor Relations link.

我們也將討論若干非 GAAP 財務衡量指標。關於非 GAAP 指標的揭露（包括與最可比 GAAP 指標的調節表）可在新聞稿與簡報中找到。除非另有特別註明，所有結果與比較皆以會計年度年對年為基礎。本次電話會議的網路重播將可在公司網站的投資人關係連結下取得。

Our second quarter fiscal 2027 quiet period begins at the close of business on Friday, October 16, 2026. We'll be hosting a virtual public webinar highlighting our improved metrics capability on September 22nd at 8:00 AM, Pacific Coast time, which will be made available on our IR website for viewing. See the Elastic's Investor Relations website for more details.

我們 2027 會計年度第二季的靜默期將於 2026 年 10 月 16 日（星期五）營業結束時開始。我們將於 9 月 22 日太平洋時間上午 8:00 舉辦一場公開的線上虛擬網路研討會，重點介紹我們改良後的 metrics（度量）能力，並將在我們的 IR 網站提供觀看。更多詳情請見 Elastic 投資人關係網站。

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

接下來，我把時間交給 Ash。

Thank you, Alex. Good afternoon, everybody. Thank you for joining us to discuss our first-quarter fiscal 2027 results. We are pleased to report a strong start to the year with continued strength in sales execution. We beat across all guided metrics and demonstrated the constant currency growth acceleration in revenue and sales led subscription revenue that we called out last quarter.

謝謝你，Alex。各位下午好。感謝各位參加本次會議，與我們一同討論 2027 會計年度第一季的業績。我們很高興回報本年度開局強勁，銷售執行力持續展現韌性。我們在所有指引指標上均超越預期，並展現了我們在上季所提到的、以固定匯率計算之營收與銷售主導訂閱營收的成長加速。

Q1 total revenue was $478 million, growing 15%. Sales-led subscription revenue grew 18% to $399 million, and we delivered a non-GAAP operating margin of 16.2%. As we previously noted, we entered fiscal 2027 with a plan to accelerate our sales-led subscription revenue growth on a constant currency basis over the course of the year. And our Q1 results demonstrate that we are off to a good start.

第一季總營收為 4.78 億美元，成長 15%。銷售主導的訂閱營收成長 18% 至 3.99 億美元，我們的非 GAAP 營業利益率為 16.2%。如同先前所述，我們在進入 2027 會計年度時，規劃在全年逐步加速以固定匯率計算的銷售主導訂閱營收成長。而第一季的結果顯示我們已取得良好開端。

Customer demand was strong across all solution areas, especially in search and AI, and Security. We ended Q1 with more than 1,800 customers spending $100,000 or more in ACV. This is the highest quarter-over-quarter net additions to this $100,000 metric that we have ever seen.

客戶需求在所有解決方案領域皆表現強勁，尤其是在搜尋與 AI，以及資安方面。第一季結束時，年度合約價值（ACV）達 10 萬美元或以上的客戶超過 1,800 家。這是我們在「10 萬美元」這項指標上，歷來所見最高的季對季淨新增數。

Our 21% cRPO growth and 27% RPO growth signal that customers are continuing to make multi-year commitments to our platform as long-term AI transformations are taking hold. AI is reshaping the stack that developers build upon.

我們 21% 的 cRPO 成長與 27% 的 RPO 成長，顯示隨著長期 AI 轉型逐步落地，客戶仍持續對我們的平台做出多年期承諾。AI 正在重塑開發者所依賴的技術堆疊。

The focus is no longer on tokenmaxxing. It is on building agentic applications that leverage the reasoning and influencing power of LLMs on a business's proprietary data. This requires the highest possible retrieval accuracy at the lowest possible cost. That shift plays directly to Elastic's strength, and we have invested accordingly in critical areas.

焦點不再是 tokenmaxxing。而是打造代理式（agentic）應用，運用 LLM 在企業專有資料上的推理與影響力。這需要在最低成本下達到最高的檢索準確度。這樣的轉變正好直接呼應 Elastic 的優勢，我們也因此在關鍵領域進行相應投資。

First, we have invested in a highly optimized data store and retrieval for AI. Our goal is for Elasticsearch to be the best store for all data that our customers care about, enabling text, vector, and hybrid search across structured and unstructured data spanning text vectors, images, audio, video, and more.

第一，我們投資於高度最佳化、面向 AI 的資料儲存與檢索能力。我們的目標是讓 Elasticsearch 成為客戶所重視之所有資料的最佳儲存層，支援跨結構化與非結構化資料的文字、向量與混合搜尋，涵蓋文字向量、影像、音訊、影片等更多類型。

We released VectorDB index mode and auto calibration this quarter, giving developers a high-quality vector search experience out of the box, with no manual tuning required. One platform with support for every data-type AI demands.

本季我們發布了 VectorDB 索引模式與自動校準（auto calibration），讓開發者開箱即用即可獲得高品質的向量搜尋體驗，無需手動調校。單一平台即可支援 AI 所需的各種資料型態。

Second, in precisely accurate context, we continue to be one of the world's most powerful context platforms for AI. This quarter, we brought Jina's multimodal and multilingual semantic search capabilities, including first-party embedding and re-rank models to on-premises and air gapped environments. This extends the power of our first party models to the world's most sensitive, regulated, and security conscious deployments.

第二，在精準的上下文（context）方面，我們持續是全球最強大的 AI 上下文平台之一。本季我們將 Jina 的多模態與多語言語意搜尋能力（包含第一方 embedding 與 re-rank 模型）帶到地端（on-premises）與隔離網路（air gapped）環境。這使我們第一方模型的能力得以延伸至全球最敏感、受監管且高度重視資安的部署場景。

Our Agent Builder harness continues to mature as well, enabling developers to build agents directly on top of data and Elasticsearch. Agent Builder now offers advanced agent observability, monitoring and enhanced human in the loop approval workflows, giving enterprises the control and visibility they need to deploy AI agents with confidence at scale.

我們的 Agent Builder 工具組也持續成熟，使開發者能直接在資料與 Elasticsearch 之上建置代理（agents）。Agent Builder 現在提供進階的代理可觀測性（observability）、監控，以及強化的人在迴路（human in the loop）核准工作流程，讓企業具備在大規模部署 AI 代理時所需的控制力與可視性。

Our investments are translated directly into competitive wins. A global 2000 semiconductor company selected Elasticsearch Serverless in a seven-figure new logo win top power a personalized AI-driven knowledge search experience for its customers. Elasticsearch will serve as the context layer, transforming the company's vast product catalog into real-time grounded AI context. When a customer queries a chip specification, compatibility requirement, or part number, Agent Builder returns an accurate answer, with per-user document level security, ensuring each customer sees only what's relevant to them.

我們的投資也直接轉化為競爭勝利。一家全球 2000 大的半導體公司在一筆七位數美元的新客戶（new logo）案中，選擇了 Elasticsearch Serverless，用於為其客戶打造個人化、AI 驅動的知識搜尋體驗。Elasticsearch 將作為上下文層，把該公司龐大的產品目錄轉化為即時、具依據（grounded）的 AI 上下文。當客戶查詢晶片規格、相容性需求或料號時，Agent Builder 會回傳精準答案，並具備每位使用者的文件層級安全控管，確保每位客戶只看到與其相關的內容。

In a competitive RFP against pure-play vector databases and other platform players, our hybrid semantic retriever and natively integrated agentic capabilities were the decisive differentiator.

在與純向量資料庫供應商及其他平台業者競爭的 RFP 中，我們的混合式語意檢索器（hybrid semantic retriever）與原生整合的代理式能力，成為決定性的差異化因素。

AI is also changing the arena of observability. As organizations build and deploy more agents. It requires more scalable monitoring of the entire application stack at a lower cost. And the speed and scale of AI deployments is requiring more automation teams to streamline the process of detecting, investigating, and remediating issues. We are pushing the frontier in these areas through targeted investments.

AI 也正在改變可觀測性的競技場。隨著組織建置並部署更多代理。就需要以更低成本，對整個應用堆疊進行更具擴展性的監控。同時，AI 部署的速度與規模也要求更高程度的自動化，讓團隊能簡化偵測、調查與修復問題的流程。我們正透過聚焦式投資，在這些領域持續推進前沿。

This quarter, we relaunched our metrics offering. We released Columnar Mode in Elasticsearch 9.5, now in technical preview. Columnar Mode is an entirely new index mode, purpose-built for time series data. It delivers extremely efficient compression, storage, and querying of time series in a columnar data structure, pushing storage costs down 20% to approximately 3 bytes per metric sample, while still using the same ESQL query language.

本季我們重新推出了 metrics（度量）產品。我們在 Elasticsearch 9.5 中發布了 Columnar Mode，目前為技術預覽版。Columnar Mode 是全新的索引模式，專為時間序列資料打造。它以柱狀資料結構提供極高效率的壓縮、儲存與查詢，將儲存成本降低 20%，每個度量樣本約降至 3 位元組，同時仍使用相同的 ESQL 查詢語言。

With these innovations we are now an optimized engine for multiple types of data, including documents, vectors, logs, metrics, and more. Columnar Mode makes the Elastic platform a highly competitive solution for metrics and infrastructure monitoring, an area where we historically have not had a major presence.

透過這些創新，我們如今成為可針對多種類型資料進行最佳化的引擎，包括文件、向量、日誌、指標等。Columnar Mode 使 Elastic 平台成為指標與基礎設施監控領域中極具競爭力的解決方案，而這一領域過去我們並未有顯著的市場存在。

Additionally, we now support native Prometheus ingestion. With PromQL support simplifying the migration from Prometheus into Elastic, no new tooling or retraining is needed. We are giving teams full visibility across metrics, logs, and traces in one unified platform, all at a very compelling price compared to incumbent competitors.

此外，我們現在支援原生 Prometheus 匯入。透過 PromQL 支援簡化從 Prometheus 遷移至 Elastic 的流程，無需新的工具或再訓練。我們讓團隊能在單一整合平台上全面掌握指標、日誌與追蹤，且相較既有競爭對手具備極具吸引力的價格。

We also acquired Deductive AI, a leader in the emerging space of AI SRE. Deductive has built a reinforcement learning, or RL harness that automates the task of complex investigations. It pairs upstream data like code repositories and Elastic alerts, with downstream signals from Slack, PagerDuty, and ServiceNow to dynamically construct decision trees, as it learns from past and ongoing investigations. It then uses these to drive investigations for new incidents based on past learnings.

我們也收購了 Deductive AI，這是新興 AI SRE 領域的領導者。Deductive 建立了一套強化學習（reinforcement learning，RL）框架，用以自動化複雜調查的工作。它將程式碼儲存庫與 Elastic 警示等上游資料，與來自 Slack、PagerDuty 與 ServiceNow 的下游訊號配對，並在從過去與進行中的調查中學習的同時，動態建構決策樹。接著，它會運用這些學習成果，基於過往經驗來推動新事件的調查。

This allows SRE teams to significantly reduce the time to investigate and remediate problems to achieve the goal of an AI-led SRE organization. By integrating deductive reasoning capabilities into our observatory platform, we're building a true agentic SRE, one that can autonomously detect, investigate, and guide remediation across the full signal stack.

這使 SRE 團隊能大幅縮短問題調查與修復所需時間，以達成 AI 主導的 SRE 組織目標。透過將演繹推理能力整合進我們的可觀測性平台，我們正在打造真正的代理式（agentic）SRE——能在完整訊號堆疊上自主偵測、調查並引導修復。

This quarter, Gardner recognized Elastic as a leader for the third consecutive year in the Gartner Magic Quadrant for observability platforms reflecting the strength of where we already stand. Illustrating the power of this unified platform approach, a leading global insurance company added Elastic absurdity to its existing security deployment in a seven-figure expansion. The customer had been running a fragmented environment, with application logs in Elastic, and metrics and traces in another incumbent solution, preventing effective root cause analysis across tens of thousands of annual incidents half attributable to application issues.

本季，Gartner 連續第三年在《Gartner 可觀測性平台魔力象限》中將 Elastic 評為領導者，反映我們既有優勢的實力。為展現此一統一平台方法的威力，一家全球領先的保險公司在既有的安全性部署之上新增 Elastic 可觀測性，並以七位數規模擴大採用。該客戶原先運行的是碎片化環境：應用程式日誌在 Elastic，而指標與追蹤在另一家既有解決方案中，導致無法針對每年數以萬計、其中約一半歸因於應用程式問題的事件進行有效的根因分析。

The deciding factor was Elastic's newly released native Prometheus ingestion and promQL support, which met their heavily metrics-driven environment where it was. And combined with our migration tooling, enabled full consolidation onto a single open telemetry-first platform without any costly rip and replace. Looking ahead, the ability to apply Elastic AI agents across all signal types to intelligently identify root cause was a key driver of the expansion.

決定性因素是 Elastic 新推出的原生 Prometheus 匯入與 PromQL 支援，能在其高度以指標為導向的環境中直接滿足需求。並結合我們的遷移工具，使其得以在不需昂貴「拆除重建」（rip and replace）的情況下，完整整併到單一、以 OpenTelemetry 優先的平台。展望未來，能將 Elastic AI 代理套用於所有訊號類型，以智慧方式識別根因，是推動此次擴張的關鍵動因。

In a post-Mythos world, organizations are facing an increasingly challenging landscape where vulnerabilities are being discovered at an alarming rate and weaponized at machine speed. This requires cyber defenders to detect, investigate, and mitigate at speeds well beyond human capacity alone. To bridge this gap, AI-driven automation has become an absolute necessity for cyber defenders Accordingly, we have invested in several areas to help our customers achieve their end goal of an AI-driven song.

在後 Mythos 時代，組織正面臨日益嚴峻的環境：弱點以驚人的速度被發現，並以機器速度被武器化。這要求資安防禦者以遠超人力單獨所能的速度進行偵測、調查與緩解。為彌補此落差，以 AI 驅動的自動化已成為資安防禦者的絕對必要條件。因此，我們在多個領域投入資源，協助客戶達成其最終目標——AI 驅動的 SOC。

Attack Discovery reached a new milestone this quarter. It now investigates and validates threats autonomously, allowing SOC teams to move at machine speed. Attack Discovery turns a wall of alerts into a prioritized list of real attacks and moving security teams closer to Alert Zero. Alert Zero is the SOC's version of inbox, inbox zero. A queue worked down to the attacks that actually matter with agents and analysts operating together.

Attack Discovery 本季達成新的里程碑。它現在能自主調查並驗證威脅，讓 SOC 團隊以機器速度行動。Attack Discovery 將一整面牆的警示轉化為已排序、優先處理的真實攻擊清單，並讓資安團隊更接近 Alert Zero。Alert Zero 是 SOC 版本的「收件匣清零」（inbox zero）。透過代理與分析師協同運作，將佇列處理到只剩真正重要的攻擊。

This quarter, we were named a leader in the IDC MarketScape for worldwide SIEM, and a strong performer in the Forrester Wave for extended detection and response. Forrester specifically recognized that Elastic's strategy envisions an open agenetic SOC that will automate operations. Elastic XDR integrates seamlessly with our SIEM and attack discovery capabilities, enabling protection and remediation unaffected systems to counter AI scale threats.

本季，我們在 IDC MarketScape 全球 SIEM 評比中被評為領導者，並在 Forrester Wave 的延伸式偵測與回應（XDR）評比中被評為強勁表現者。Forrester 特別指出，Elastic 的策略描繪了一個開放的代理式（agentic）SOC，將自動化營運。Elastic XDR 與我們的 SIEM 與 Attack Discovery 能力無縫整合，使其能保護並修復受影響的系統，以對抗 AI 規模化的威脅。

And on endpoint protection, Elastic Security is the only vendor to achieve 14 consecutive months of 100% detection rates in AV comparatives independent testing. Our strength in Security is also allowing us to rapidly grow our footprint in the US public sector through the CISA SIEM-as-a-Service offering. This relationship continues to serve as a powerful channel across the US government opening new opportunities.

在端點防護方面，Elastic Security 是唯一在 AV-Comparatives 獨立測試中連續 14 個月達成 100% 偵測率的供應商。我們在安全性領域的優勢，也讓我們透過 CISA 的 SIEM-as-a-Service 方案，快速擴大在美國公部門的版圖。這項合作關係持續成為橫跨美國政府的強大通路，開啟新的機會。

A large US public sector agency shows Elastic Security and observability to begin unifying its fragmented data estate onto a single platform, replacing disparate SIEM data. Elastic's newly achieved FedRAMP high authorization, unlocked the opportunity and our ability to monitor both on-premises and multi-cloud environments from one managed deployment made us the strongest candidate.

一家大型美國公部門機構選擇 Elastic Security 與可觀測性，以開始將其碎片化的資料資產整合到單一平台，取代分散的 SIEM 資料。Elastic 新取得的 FedRAMP High 授權解鎖了此機會，而我們能以單一受管部署同時監控地端與多雲環境，使我們成為最有力的候選者。

Where the agency's previous vendor had stalled on innovation, Elastic's space of development and LLM agnostic AI integration gave them a clear path forward for modern threat detection and response. Our efficiency and AI features were key drivers of this win. What is exciting about this customer is that we were able to migrate their very complex data platform from their incumbent solution onto Elastic in under one month, taking advantage of all of the automated migration tooling that we have built for this purpose.

在該機構先前供應商的創新停滯之際，Elastic 的開發速度與對 LLM 不綁定（LLM-agnostic）的 AI 整合，為其提供了現代化威脅偵測與回應的清晰前進路徑。我們的效率與 AI 功能是贏得此案的關鍵驅動因素。這位客戶令人振奮之處在於：我們能在不到一個月內，將其非常複雜的資料平台從既有解決方案遷移到 Elastic，並充分運用我們為此目的打造的自動化遷移工具。

We see the same momentum in the private sector. A global semiconductor manufacturer chose Elastic Security Services as its security analytics platform to protect against insider that and secure its intellectual property using our AI capabilities. The customer intends to move hundreds of dashboards from an incumbent solution into Elastic to leverage our natural language search and analytics capabilities.

我們在私部門也看到同樣的動能。一家全球半導體製造商選擇 Elastic Security Services 作為其安全分析平台，運用我們的 AI 能力防範內部威脅並保護其智慧財產。該客戶計畫將數百個儀表板從既有解決方案移轉至 Elastic，以運用我們的自然語言搜尋與分析能力。

Now moving away from manual workflows. The customer is adopting our agent capabilities across their full data estate. When competitors offered AI as an add-on, Elastic's fully integrated platform gave the customer exactly what they needed, one product built for the age of AI. All of these innovations, combined with the consistent sales execution are driving rapid growth in AI usage within our customer base.

如今正逐步擺脫手動工作流程。該客戶正在其完整資料資產上採用我們的代理能力。當競爭對手將 AI 作為附加功能提供時，Elastic 的全整合平台為客戶提供了其所需的一切——一款為 AI 時代打造的產品。所有這些創新，加上持續一致的銷售執行力，正推動我們客戶群中 AI 使用量的快速成長。

Over 37% in of our $100,000-plus ACV customers are now using Elastic for AI, up from approximately 21% a year ago. That is more than 670 high-value customers now using Elastic for AI use cases with 70 net additions quarter over quarter in Q1. Our ability to deliver all of this with an open platform across both cloud and self-managed deployments is proving to be an enduring advantage, as AI adoption grows across natives, enterprises, regulated industries and government agencies around the world. This includes our support for both proprietary models and open models like GLM from Z.ai, our adherence to standards like open telemetry, our ability to support sovereign deployments through our self-managed offering, and our partnerships with NVIDIA and Dell around their AI factory and with Google Distributed Cloud.

我們年經常性合約價值（ACV）達 10 萬美元以上的客戶中，現已有超過 37% 使用 Elastic 進行 AI，較一年前約 21% 顯著提升。目前已有超過 670 家高價值客戶使用 Elastic 進行 AI 用例，且在第一季（Q1）較前一季淨新增 70 家。我們能以開放平台同時支援雲端與自管部署來交付上述能力，隨著 AI 在全球原生企業、大型企業、受監管產業與政府機構中的採用成長，正被證明是一項長期優勢。這包括我們同時支援專有模型與 Z.ai 的 GLM 等開放模型、遵循 OpenTelemetry 等標準、透過自管方案支援主權部署的能力，以及與 NVIDIA 與 Dell 在其 AI Factory、以及與 Google Distributed Cloud 的合作夥伴關係。

We entered this fiscal year with seven successive quarters of strong sales execution and continuing momentum for our platform. Our pace of growth in search and AI and Security has continued. And with our most recent innovations in the areas of metrics and AI S, we are excited about the prospects of our absorbability business. As AI adoption grows across the enterprise, we expect to continue driving acceleration of our business toward our midterm revenue and profitability targets.

我們以連續七個季度強勁的銷售執行力與平台持續動能進入本會計年度。我們在搜尋與 AI 以及安全性方面的成長速度持續。隨著我們近期在指標與 AI S 領域的創新，我們對可觀測性業務的前景感到振奮。隨著 AI 在企業中的採用成長，我們預期將持續推動業務加速，朝向我們的中期營收與獲利目標邁進。

I also want to take a moment to recognize a board transition.I want to thank Karen Moroney, who will be stepping off our Board after a long tenure. We are grateful for her partnership and she will continue to be a friend to Elastic. I am pleased to announce that Julia Liuson has been nominated to join our Board. Julia has seen Elastic Grow as a leader in the areas of Search AI, Absorbability, and Security in her prior role as President of developer tools at Microsoft. She brings a unique perspective around AI and at-scale infrastructure development that will be invaluable as we continue to execute on our strategy.

我也想花點時間提及董事會的人事交接。我想感謝 Karen Moroney，在長期任職後即將卸任本公司董事會職務。我們感謝她的合作夥伴關係，她也將持續作為 Elastic 的朋友。我很高興宣布，Julia Liuson 已獲提名加入我們的董事會。Julia 在先前擔任微軟開發者工具總裁期間，見證 Elastic 成長為搜尋 AI、可觀測性與資安領域的領導者。她在 AI 與大規模基礎設施開發方面帶來獨特觀點，這將在我們持續推進策略執行時成為無可估量的助力。

I want to thank our customers and partners for their trust, our shareholders for their continued partnership, and our employees for their focus and execution.

我要感謝我們的客戶與合作夥伴對我們的信任，感謝股東持續的合作夥伴關係，也感謝員工的專注與執行力。

With that, I will turn the call over to Navam.

接下來，我把電話會議交給 Navam。

Thank you, Ash. On our last earnings call in May, we expressed confidence that our commitments we secured in fiscal '26, combined with our continued sales execution, will drive revenue acceleration over the course of fiscal '27 on a constant currency basis. While it's still early in the fiscal year, our Q1 results put us on track to achieve this goal.

謝謝你，Ash。在我們 5 月的上一場財報電話會議上，我們表達了信心：我們在 2026 會計年度所取得的承諾，加上持續的銷售執行，將在固定匯率基礎上推動 2027 會計年度期間的營收加速成長。雖然本會計年度仍在初期，但我們第一季的結果讓我們有望達成此目標。

Our total revenue in the first quarter was $478 million. We grew approximately 15% as reported and on a constant currency basis. On a constant currency basis, Q1 growth accelerated quarter over quarter, up from 14% in Q4. Sales with subscription revenue in the first quarter was $399 million. We grew 18% as reported and 17% on a constant currency basis.

第一季總營收為 4.78 億美元。按報告口徑與固定匯率口徑計算，我們約成長 15%。以固定匯率計算，第一季成長率較前一季加速，從第四季的 14% 提升。第一季以銷售帶動的訂閱營收為 3.99 億美元。按報告口徑成長 18%，以固定匯率計算成長 17%。

Similar to total revenue, sales-led subscription revenue accelerated quarter over quarter in constant currency, up from 16% in Q4. Our cRPO in the first quarter was $1.2 billion, representing 21% growth as reported and 20% on a constant currency basis. Our constant currency cRPO growth sustained 20% growth for the second consecutive quarter. Our RPO for the first quarter was $1.9 billion, representing 27% growth, both as reported and on a constant currency basis.

與總營收類似，以固定匯率計算的銷售帶動訂閱營收亦較前一季加速，從第四季的 16% 提升。第一季 cRPO 為 12 億美元，按報告口徑成長 21%，以固定匯率計算成長 20%。以固定匯率計算的 cRPO 成長率已連續第二季維持 20% 成長。第一季 RPO 為 19 億美元，按報告口徑與固定匯率口徑皆成長 27%。

As Ash mentioned, the continued strength in RPO reflects customers deepening their long-term commitments to Elastic as a core part of their AI infrastructure. Our Q1 revenue acceleration on a constant currency basis, both for total and for sales-led subscription revenue, as well as our second straight quarter of 20% constant currency cRPO growth provides validation for our acceleration trajectory.

如 Ash 所提到，RPO 的持續強勁反映客戶正加深對 Elastic 的長期承諾，將其視為其 AI 基礎設施的核心一環。我們第一季在固定匯率基礎上的營收加速（無論是總營收或銷售帶動訂閱營收），以及連續第二季 20% 的固定匯率 cRPO 成長，為我們的加速成長軌跡提供了驗證。

Three core dynamics are powering our fiscal 2017 sales-led subscription revenue growth. First, our strategic investments in sales capacity over the past year are driving the pipeline improvements we expected. Building on seven quarters of go-to-market improvement, we continue to see year-over-year gains in both ramp sales head count and productivity this quarter. Additionally, the strength in our second quarter pipeline and buildup of out quarter pipeline reinforce our confidence in securing new and expanded commitments, as well as achieving our planned renewals.

三項核心動能正在推動我們 2017 會計年度的銷售帶動訂閱營收成長。第一，過去一年我們在銷售產能上的策略性投資，正帶來我們預期的管線改善。在連續七季的市場進入策略改善基礎上，本季我們持續看到已上線（ramp）的銷售人力與生產力皆呈現年增。此外，第二季管線的強勁，以及未來季度管線的累積，進一步強化我們對取得新增與擴大承諾、以及達成既定續約目標的信心。

Second, as we discussed last quarter, a portion of our fiscal '27 revenue is made up of commitments from fiscal '26, now being consumed and converted into revenue. We are pleased with the healthy consumption activity we saw this quarter. The net expansion rate, or NER, remained strong, though it moved from 112% to 111% this quarter. As a reminder, our NER is a four-quarter trailing metric impacted by historical growth. The NER we reported in Q1 reflects the lower constant currency growth rate in the trailing four quarters, as compared to the 4 quarters preceding. We expect NER to improve within four quarters as constant currency revenue acceleration builds through fiscal '27.

第二，如同我們上季所討論，我們 2027 會計年度的一部分營收由 2026 會計年度取得的承諾所構成，這些承諾目前正被消耗並轉換為營收。我們對本季看到的健康使用（consumption）活動感到滿意。淨擴張率（NER）仍維持強勁，但本季從 112% 小幅降至 111%。提醒一下，我們的 NER 是一項過去四季滾動的指標，會受到歷史成長的影響。我們在第一季所報告的 NER，反映了過去四季的固定匯率成長率相較於再往前四季較低。隨著 2027 會計年度固定匯率營收加速逐步建立，我們預期 NER 將在四季內改善。

Third, we saw continued improvements in our new and expansion commitments as seen in our greater than $100,000 customer count, that segment now contributing 90% of sales-led subscription revenue, up from 87% a year ago. This quarter, we added more than 80 net new customers to this tier, our largest increase to date. This reflects the effectiveness of our sales team in both winning new logos and expanding within our existing base.

第三，我們在新增與擴張承諾方面持續改善，這可從年化合約金額超過 10 萬美元的客戶數看出；該客群目前貢獻銷售帶動訂閱營收的 90%，高於一年前的 87%。本季我們在此級距新增超過 80 家淨新客戶，創下迄今最大增幅。這反映我們銷售團隊在贏得新客戶（new logos）以及在既有客戶基礎內擴張方面的成效。

Now turning to Q1 margins and profitability. I will discuss all measures on a non-GAAP basis. We delivered subscription gross margins of 81%, total gross margins of 77% and an operating margin of 16.2%, exceeding our guidance from last quarter. The improvement in margins reflect the operating leverage in our model as revenue scales.

接著談第一季的毛利率與獲利能力。我將以非 GAAP 基礎說明所有指標。我們實現訂閱毛利率 81%、總毛利率 77%，以及營業利益率 16.2%，優於上季給出的指引。毛利率的改善反映隨著營收規模擴大，我們商業模式所展現的營運槓桿。

We achieved an adjusted free cash flow margin of 30% despite onetime charges related to organizational changes we announced in June. These amounted to $13 million of cash paid for restructuring and other charges. As a reminder, adjusted free cash flow fluctuates quarter to quarter, due to booking seasonality, and we manage free cash flow on a full-year basis.

儘管我們在 6 月宣布的組織調整帶來一次性費用，我們仍達成 30% 的調整後自由現金流利潤率。其中包含 1,300 萬美元的現金支出，用於重組及其他費用。提醒一下，調整後自由現金流會因訂單入帳的季節性而在各季間波動，我們以全年為基礎管理自由現金流。

During the first quarter, we returned approximately $40 million to shareholders, representing purchases of approximately 800,000 shares. Since the $500 million share repurchase program launched in October 2025, we used $380 million and repurchased 5.2 million shares cumulatively as of the end of last quarter.

第一季期間，我們向股東返還約 4,000 萬美元，約買回 80 萬股。自 2025 年 10 月啟動 5 億美元庫藏股回購計畫以來，截至上季末我們累計已使用 3.8 億美元並回購 520 萬股。

Now turning to our outlook for the second quarter and for the fiscal 2027. Building from the momentum we experienced in Q1, we are raising our previous guidance for the full year.

接著談我們對第二季與 2027 會計年度的展望。在第一季動能的基礎上，我們上調先前對全年的指引。

For the second quarter of fiscal '27, we expect total revenue in the range of $486 million to $487 million representing 14.9% growth at the midpoint or 15% constant currency growth at the midpoint. We expect sales-led subscription revenue in the range of $407.5 million to $408.5 million, representing 16.9% growth at the midpoint or 17.1% in constant currency growth at the midpoint.

就 2027 會計年度第二季而言，我們預期總營收介於 4.86 億至 4.87 億美元，中位數代表 14.9% 成長，或以固定匯率計算中位數為 15% 成長。我們預期銷售帶動訂閱營收介於 4.075 億至 4.085 億美元，中位數代表 16.9% 成長，或以固定匯率計算中位數為 17.1% 成長。

We expect non-GAAP operating margin for the second quarter to be approximately 19%. We expect non-GAAP diluted earnings per share in the range of $0.80 to $0.82, using between $108 million and $109 million diluted weighted average ordinary shares outstanding.

我們預期第二季非 GAAP 營業利益率約為 19%。我們預期第二季非 GAAP 稀釋後每股盈餘介於 0.80 至 0.82 美元，稀釋後加權平均流通普通股數介於 1.08 億至 1.09 億股。

For fiscal '27, given our strong Q1 results, we are raising our outlook for the year. We expect total revenue in the range of $1.998 billion to $2.010 billion, representing approximately 15.2% growth at the midpoint or 15.3% constant currency growth at the midpoint. We expect sales-led subscription revenue in the range of $1.682 billion to $1.694 billion, representing 17.4% growth at the midpoint or 17.5% in constant currency growth at the midpoint.

就 2027 會計年度而言，鑑於第一季的強勁表現，我們上調全年展望。我們預期總營收介於 19.98 億至 20.10 億美元，中位數約代表 15.2% 成長，或以固定匯率計算中位數為 15.3% 成長。我們預期銷售帶動訂閱營收介於 16.82 億至 16.94 億美元，中位數代表 17.4% 成長，或以固定匯率計算中位數為 17.5% 成長。

We expect non-GAAP operating margin to be approximately 19.4%. We expect non-GAAP diluted earnings per share in the range of $3.29 to $3.37, using between $108.5 million and $109.5 million diluted weighted average ordinary shares outstanding. We continue to expect our fiscal 2027 adjusted free cash flow margin to be 21.5%. We are growing revenue efficiently, while maintaining disciplined investments and are making progress towards rural fort.

我們預期非 GAAP 營業利益率約為 19.4%。我們預期非 GAAP 稀釋後每股盈餘介於 3.29 美元至 3.37 美元之間，係以稀釋後加權平均流通普通股數介於 1.085 億股至 1.095 億股計算。我們仍預期 2027 會計年度調整後自由現金流利潤率為 21.5%。我們在維持嚴謹投資紀律的同時，以高效率推動營收成長，並正朝向 rural fort 取得進展。

Before I close, a few more financial items worth highlighting related to this year. We incurred approximately $20 million of restructuring-related charges during the first quarter, and we expect to incur an additional $2 million to $5 million of restructuring charges for the remainder of the fiscal year. We expect our GAAP operating margin to be positive in the second quarter and for the full year. We also expect to maintain GAAP operating margin profitability going forward. And last, as we said last quarter, we expect total revenue and sales-led subscription revenue growth to accelerate in the second half with Q4 having the highest year-over-year growth for the year.

在我結束之前，還有幾項與今年相關、值得強調的財務事項。我們在第一季認列約 2,000 萬美元的重組相關費用，並預期在本會計年度剩餘期間將再認列 200 萬至 500 萬美元的重組費用。我們預期第二季以及全年 GAAP 營業利益率將為正值。我們也預期未來將持續維持 GAAP 營業利益率的獲利能力。最後，如同我們上季所說，我們預期總營收與銷售主導（sales-led）的訂閱營收成長將在下半年加速，其中第四季將是全年年增率最高的一季。

To summarize, we are executing well across our fiscal year priorities and are firmly on track to meet our medium-term financial targets of both accelerating our sales-led subscription revenue growth to 20% plus and improving our rule of 40 as measured as a sum of revenue growth and adjusted free cash flow. The sustained progress we see in cRPO, sales productivity pipeline and operating leverage reinforce our confidence in our revenue growth and margin expansion plans.

總結來說，我們正順利執行本會計年度的各項優先事項，並穩健朝向達成中期財務目標前進：一方面將銷售主導的訂閱營收成長加速至 20% 以上，另一方面提升我們的「40 法則」（rule of 40），其衡量方式為營收成長率與調整後自由現金流之加總。我們在 cRPO、銷售生產力管線以及營運槓桿方面所見到的持續進展，進一步強化我們對營收成長與利潤率擴張計畫的信心。

Elastic continues to be the essential platform for enterprises looking to derive value from their data, and we look forward to the opportunities ahead. Thank you for your continued support thanks for joining us today. With that, I'll open it up for Q&A.

Elastic 仍是企業從其資料中萃取價值所不可或缺的平台，我們也期待未來的各項機會。感謝各位持續的支持，也謝謝今天加入我們。接下來我將開放問答。

(Operator Instructions) Matt Hedberg, RBC Capital Markets.

（接線員指示）RBC Capital Markets 的 Matt Hedberg。

Great. Thanks for taking my question, guys. First of all, congrats on the quarter, the acceleration, especially after a 4Q was impressive. Ash, there's a lot of things that stood out to me, the strength in $1,000 -- or $100,000 customers, I think you said the largest sequential ad you've ever seen was impressive.

太好了。謝謝你們回答我的問題，各位。首先，恭喜本季表現與成長加速，尤其是在第四季之後仍能加速，令人印象深刻。Ash，有很多點讓我注意到，像是 1,000 美元——或 100,000 美元客戶的強勁表現；我記得你說過，史上最大的單季淨新增（sequential add）非常亮眼。

And I guess you talked about a lot of things on the call about execution and and product traction and just better sales capacity. But I wonder if you can put a finer point on the success there, why now? And just kind of the sustainability of that large customer growth would be great.

我想你們在電話會議中談到很多，包括執行力、產品動能，以及更好的銷售產能。但我想請你更精準地說明這項成功：為什麼是現在？另外，也希望你談談這種大型客戶成長的可持續性。

Matt, thank you very much for the question. And like you said, it was a great quarter in terms of the net ads. We added 80 customers to that cohort, the highest ever number of additions that we've had. Fundamentally, the way I think about it is that our new and expand motion, especially in our enterprise and mid-market high propensity customers is working really well.

Matt，非常感謝你的提問。如你所說，就淨新增而言，這是一個很棒的季度。我們在該客群新增了 80 位客戶，創下我們歷來最高的新增數。從根本來看，我的理解是，我們的新客開發與擴張（new and expand）動能，特別是在企業與中型市場中高傾向（high propensity）客戶方面，運作得非常好。

If you remember, about two years ago, a little over two years ago, we made a change to the way that segmentation within the organization, within the sales organization. And since then, you have seen us continue to improve in this area. And what you're seeing is customers are making bigger commitments. Customers are making longer-term commitments. And that's resulting in this cohort really growing very nicely.

如果你還記得，大約兩年前、略多於兩年前，我們調整了組織內部、尤其是銷售組織的分群方式。自那之後，你們看到我們在這方面持續改善。而你現在看到的是，客戶正在做出更大的承諾。客戶也在做出更長期的承諾。這使得這個客群成長得非常漂亮。

By the way, this $100,000 cohort now represents 90% of our sales-led subscription revenue, so it just gives you a sense both of how important this cohort is, but also how well they're doing. And the thing that excites me the most is the AI penetration in this cohort. So 37% of this $100,000 cohort is now using our AI features. That number was about 21% in the past. And like we explained even at our Financial Analyst Day, the more this high value customer cohort uses our AI capabilities, the more they use more and more solutions within our platform. That really becomes the enduring road driver for us.

順帶一提，這個 100,000 美元客群目前占我們銷售主導訂閱營收的 90%，這讓你能理解這個客群的重要性，以及他們表現得有多好。而最讓我興奮的是這個客群中的 AI 滲透率。因此，這個 100,000 美元客群中已有 37% 正在使用我們的 AI 功能。過去這個數字大約是 21%。正如我們在財務分析師日所說，這個高價值客群越多使用我們的 AI 能力，他們就越會在我們的平台內使用更多解決方案。這確實會成為我們長期且持久的成長驅動力。

So very excited about it. And it just shows that the go-to-market motion is working and the platform strength and differentiation is holding very well.

所以我們非常興奮。這也顯示我們的市場進入（go-to-market）動能正在奏效，而平台的強度與差異化也維持得非常好。

Well, if I could as a follow-up, the 37% of those customers using AI, it was another thing that stood out to me. Is there any way to think about what that means from an NRR perspective? I'd have to imagine it, it's obviously additive and maybe it's part of the NRR reacceleration. Just any way to think about what that means from a like a customer ACV or NRR perspective?

那我追問一下，這些客戶中有 37% 在使用 AI，這也是另一個讓我注意到的點。有沒有什麼方式可以從 NRR 的角度來理解這代表什麼？我想這顯然是加分項，或許也是 NRR 重新加速的一部分。能否分享一下，從客戶 ACV 或 NRR 的角度，該如何看待這件事？

Good question. So net -- the NRR is obviously a strong metric across the board for all our $100,000 customers. But when you think about the cohort of customers that are that are using AI, the dynamics that we talked about during the financial analyst, they still stand, which is they have a higher growth propensity compared to customers not using AI. So that dynamic exists today among that AI cohort group at the same way it existed when we talked about in the Financial Analyst Day.

好問題。所以，對我們所有 100,000 美元客戶而言，NRR 顯然是一項整體都很強的指標。但當你看使用 AI 的那群客戶時，我們在財務分析師日談到的動態仍然成立：相較於未使用 AI 的客戶，他們具有更高的成長傾向。因此，這個動態今天在 AI 客群中依然存在，與我們在財務分析師日所談到的情況一致。

All right, thanks, Matt.

好的，謝謝你，Matt。

Next question please.

請下一個問題。

Tyler Radke, Citi.

Citi 的 Tyler Radke。

Can you guys hear me okay?

你們聽得到我嗎？

We can now.

現在聽得到。

Sorry about that, was on mute there. Can you just talk a little bit -- obviously, really strong cloud performance. And I know you alluded to the strength in the cloud bookings last quarter, but any one-offs dynamics we should be mindful of? And can you just comment on sort of the the bookings mix this quarter, how that cloud sort of looked, relative to historicals? And you know, just any any color on how we should be thinking about the growth of cloud from here?

抱歉，剛剛我在靜音。能否談談——顯然雲端表現非常強勁。我知道你們上季提到雲端訂單（bookings）的強勢，但這季是否有任何一次性因素（one-offs）需要我們留意？另外也請評論一下本季的訂單組合（bookings mix），雲端相較於過往歷史水準看起來如何？以及，對於接下來雲端成長，我們應該如何思考？

Yes. Thanks, Tyler. It's Navam here. So look, we're very pleased with the way cloud has been performing in the quarter, both in terms of the commitment volume. And also, more importantly, the consumption against the annual commitments we have, the aggregate annual commitments we have. And as a reminder, cloud is not a guided metric and there's always going to be quarter-over-quarter variability because it's consumption. But our annual cloud growth improved to 27% this quarter, up from 26% last quarter.

是的。謝謝你，Tyler。我是 Navam。我們對本季雲端的表現非常滿意，無論是在承諾量（commitment volume）方面。更重要的是，在我們所擁有的年度承諾（annual commitments）、也就是整體年度承諾之下的實際使用量（consumption）。提醒一下，雲端並不是我們提供指引的指標，而且由於它是以使用量計算，季度之間一定會有波動。不過，我們本季雲端年度成長率提升至 27%，高於上季的 26%。

On the monthly cloud side, that number, we expected it to remain flat and it remained roughly flat for the quarter. So the dynamics are roughly the same in terms of the growth on the sales-led cloud side and the SMB smaller customers remaining flat. At the end of the day though, we win because we have flexibility in our deployment model, right? And we meet the customers where they are and where they want to deploy our software. And we are one of the very few players that can actually do that. And that's the reason we continue to focus on sales led subscription revenue.

就每月雲端那一塊而言，那個數字，我們原本預期會維持持平，而本季也大致維持持平。因此，在銷售主導的雲端端成長，以及 SMB 較小客戶維持持平方面，其動態大致相同。不過歸根結底，我們之所以能勝出，是因為我們的部署模型具備彈性，對吧？我們在客戶所在之處與他們會合，也在他們希望部署我們軟體的地方提供服務。而我們是少數真正能做到這點的業者之一。這也是我們持續聚焦於銷售主導訂閱營收的原因。

In terms of bookings dynamics, we expect to, like I said, meet customers where they are. There isn't much to call out this quarter in terms of one-offs. So we talked about the mix in Q4 being a good cloud quarter. Q1 remained a solid quarter with no unusual activity one way or the other.

就訂單（bookings）動態而言，我們預期會如我所說，去到客戶所在之處。本季就一次性因素而言，沒有太多需要特別指出的。我們談到 Q4 的組合是一個不錯的雲端季度。Q1 仍是一個穩健的季度，沒有任何異常活動，不論是正向或負向。

And by the way, Tyler, just to put a finer point on what Navam said. The fact that we can deliver all the capabilities that we provide through the platform, whether it's for AI, whether it's for Security, whether it's for observability in environments ranging from commercial cloud to people running it in their own data centers to air gap environments, we mentioned last quarter that Google Distributed Cloud has OEMed our capability as well.

順帶一提，Tyler，為了更精準地補充 Navam 所說的。我們能透過平台交付我們提供的所有能力，不論是 AI、不論是資安、不論是可觀測性，且可在從商用雲端、到客戶在自有資料中心運行、再到空氣隔離（air gap）環境等各種環境中提供；我們上季也提到 Google Distributed Cloud 也以 OEM 方式採用了我們的能力。

So that flexibility, that range is a significant enduring moat. Because if you think about the markets that we play in, there are very few vendors that have that ability to deliver across all of those form factors, and that is a big advantage for us. And that's the reason why Navam said sales-led subscription revenue is a very important metric. And by the way, cloud self-managed, all of those are things that we look at, and we are very happy about the performance overall.

因此，這種彈性與覆蓋範圍是一道重要且持久的護城河。因為如果你想想我們所參與的市場，能夠跨所有這些形態（form factors）交付的供應商非常少，這對我們而言是很大的優勢。這也是 Navam 說銷售主導訂閱營收是一個非常重要指標的原因。另外，雲端自管（cloud self-managed）等這些也都是我們會觀察的項目，而我們對整體表現非常滿意。

Great. And Ash, maybe just get a follow-up for you. Obviously, some pretty remarkable events going on in Security as it relates to some of the new attack vectors and agents going rogue. Like, can you just talk to us about the Elastic Security business? How do you see it participating in some of these new Agentic Security fronts?

很好。Ash，或許我再追問一下。顯然，資安領域正在發生一些相當引人注目的事件，涉及新的攻擊向量以及代理（agents）失控。你能否談談 Elastic Security 這塊業務？你如何看待它在這些新的 Agentic Security 前線中的參與方式？

Yeah. Our Security business is something that we are very, very excited about. Even in my prepared remarks, Tyler, I talked about several customers, right, that are using us in Security. I talked about the semiconductor company. I talked about the government did the very large government agency. We've talked to you in the past about a SIEM as a service. I just mentioned Google disconnected cloud. And all of these are already driving our SIEM business and our XDR business.

是的。我們對資安業務感到非常、非常興奮。即便在我事先準備的發言中，Tyler，我也提到好幾個客戶，對吧，他們在資安方面使用我們。我提到了那家半導體公司。我提到了政府、那個非常大型的政府機構。我們過去也跟你談過 SIEM as a service（SIEM 服務化）。我剛才也提到 Google 斷線雲（disconnected cloud）。而這些都已經在推動我們的 SIEM 業務與 XDR 業務。

And what's great about this is we are able to help our customers because it's never been harder to be a CISO. Threats are -- vulnerabilities are being discovered faster. Threats are being activated faster. So sort of working at human speed is just not sufficient. You have to figure out how to use AI on the Defender side, to be able to detect, investigate, and remediate machine speed, and you know how early we invested in sort of the AI-led capabilities like attack discovery and so on.

而這很棒的一點是，我們能夠協助客戶，因為當 CISO 從未如此艱難。威脅——漏洞被發現的速度更快。威脅被啟動的速度也更快。所以以人類速度來運作已經不夠了。你必須想辦法在防禦端使用 AI，才能以機器速度進行偵測、調查與修復；而你也知道我們很早就投資於以 AI 驅動的能力，例如攻擊發現等。

And all of that, the maturity, the continuous innovation that we are driving there, we are already seeing all of this turn into strong commitments. And you're seeing now the consumption against those commitments. So I expect the momentum to continue for us in Security.

而所有這些成熟度、我們在那裡推動的持續創新，我們已經看到這些正在轉化為強勁的承諾（commitments）。而你現在也看到針對這些承諾的使用量（consumption）。因此我預期我們在資安方面的動能將會持續。

Okay, thanks, Tyler. Next question, please.

好的，謝謝，Tyler。請下一題。

Miller Jump, Truist Securities.

Miller Jump，Truist Securities。

Hey, great. Thank you for taking my question and congrats on the strong results here. You mentioned customers choosing you for flexibility and highlighted some of the enhancements to Jina on-prem capabilities this quarter. I'm wondering if you can give any more color on how you're seeing the distribution of customer AI deployments developing specifically across cloud, on-prem, and hybrid and if there's any difference versus your other use cases?

嗨，很好。謝謝讓我提問，也恭喜你們交出強勁的成果。你提到客戶因為彈性而選擇你們，並強調本季對 Jina on-prem（地端）能力的一些強化。我想請問你能否再多提供一些背景：你們如何看待客戶 AI 部署在雲端、地端與混合式之間的分布發展？以及這是否與你們其他使用情境有所不同？

Yeah. It's -- so what we are seeing is that there is still the majority of customer deployments tend to be first and foremost in cloud, that's where they typically start because that's the fastest way for customers to get started but enterprise customers and government agencies. And I say enterprise customers I'm specifically referring to customers in regulated industries, whether it's banking, whether it's telco, especially in international markets for us outside of the Americas, what we are seeing there is a greater desire to, not just have data sovereignty, but also to have operational sovereignty.

是的。我們看到的是——目前大多數客戶部署仍然傾向首先在雲端，因為那通常是客戶最快開始的方式；但對於企業客戶與政府機構而言。我說的企業客戶特別是指受監管產業的客戶，不論是銀行、不論是電信，尤其是對我們在美洲以外的國際市場，我們看到他們更希望不只是資料主權（data sovereignty），也希望有營運主權（operational sovereignty）。

And in those environments, they want solutions where they can run these capabilities within their own enclaves, within their own control. And again, like that's where we have such a great strength because there aren't too many companies that are able to provide that kind of functionality. And in the past, our Jina models, you had availability of those of the commercial Jina models through our inference service, which was cloud only, but there was no way if you're an air gap customer or a customer running things within your own enclave to take advantage of the Jina models, we didn't have a pricing model in place for sort of the commercial capabilities there. So that's what we launched.

在那些環境中，他們想要能在自有隔離區（enclaves）、在自有控制之下運行這些能力的解決方案。而同樣地，這正是我們的強項，因為能提供那種功能的公司並不多。過去，我們的 Jina 模型，你可以透過我們的推論服務取得商用 Jina 模型的可用性，而那是僅限雲端；但如果你是空氣隔離客戶或是在自有隔離區內運行的客戶，就沒有辦法利用 Jina 模型，因為我們當時沒有針對那類商用能力提供定價模型。所以這就是我們推出的內容。

And there's a lot of interest. We launched it because we're seeing a lot of interest. So going forward, what I would expect is AI deployments are going to be based on factors like the criticality of the data, the sensitivity of the data, the kind of customer in their geo location. So those will be bigger factors, but you're going to see AI adoption both in cloud and in self-managed.

而且有很大的興趣。我們之所以推出，是因為我們看到很大的興趣。因此往前看，我預期 AI 部署將取決於資料的重要性、資料的敏感度、客戶類型以及其地理位置等因素。所以這些會是更大的因素，但你會看到 AI 在雲端與自管（self-managed）兩邊都會被採用。

Really exciting. If I could just squeeze in a follow-up for Navam. You all highlighted the strength in the SSA deal but just given that we're coming off on the anniversary, I'm wondering if you can give any more color on how the Fed vertical is being treated in the Q2 guide and if there's any headwinds or tailwinds we should consider this year?

非常令人振奮。如果可以的話，我想再擠一個追問給 Navam。你們強調了 SSA 交易的強勁表現，但考量我們正好剛過周年，我想請問你能否再多提供一些背景：在 Q2 指引中，聯邦政府（Fed）垂直領域是如何被納入考量的？以及今年是否有任何我們應該留意的逆風或順風？

Nothing specific at this point in terms of guidance for the Fed vertical Miller the global public sector remains an important sector for us. When we think about our guidance, we obviously look at a prudent risk-adjusted view as to forward numbers. Very pleased with how the CSA contract is performing and the continued activity there. So we expect that to continue to gain momentum as more agencies come on board. But nothing specific to call out in terms of a big tailwind coming in or a big headwind coming in from the Federal segment.

就目前而言，關於聯邦政府垂直領域在指引中的部分，沒有特別要指出的，Miller；全球公共部門仍然是我們的重要領域。當我們思考指引時，我們顯然會以審慎、風險調整後的觀點來看待未來數字。我們對 CSA 合約的執行情況以及那裡持續的活動感到非常滿意。因此我們預期，隨著更多機構加入，這將持續累積動能。但就聯邦政府部門而言，沒有特別需要指出會帶來重大順風或重大逆風的因素。

Awesome, thank you.

太棒了，謝謝。

Thanks, Miller. Next question, please.

謝謝你，Miller。請下一題。

Brian Essex, JPMorgan.

JPMorgan 的 Brian Essex。

Hey, good afternoon. Thank you for taking the question. And congrats from me as well on the results. It's great to see that acceleration. Maybe ask for me, I'd love to get your view on how you see your customers deploying AI and coding around AI, specifically around leveraging your platform to build their own harness in context windows to get more control around the ability to protect that context and proprietary data, as opposed to using OEM harnesses and coding platforms? And how that -- how you're positioned for or your view on how that portion of the market is going to evolve over the next few years?

嗨，午安。謝謝讓我提問。我也要恭喜你們的業績表現。很高興看到這樣的加速成長。我想請教你們如何看待客戶在部署 AI、以及圍繞 AI 進行開發與寫程式，特別是客戶如何運用你們的平台，在情境視窗（context windows）中打造自有的 harness，以便更能掌控情境保護與專有資料的保護，相較於使用 OEM 的 harness 與程式開發平台？以及你們如何定位、或你們怎麼看這一塊市場在未來幾年會如何演進？

Yeah. Thanks for the question. And yeah, the first thing to appreciate is, at the end of the day, when you're building any kind of a genetic solution the most important element in that is going to always be the large language model, the model that does reasoning, that does inferencing and so on and so forth. But that model, unless what the agent that you're trying to build only depends on external data, only depends on like publicly available information, is going to need to somehow be coupled with your proprietary information.

是的。謝謝你的問題。首先要理解的是，歸根究柢，當你在打造任何類型的生成式解決方案時，其中最重要的元素永遠會是大型語言模型，也就是負責推理、負責推斷（inferencing）等等的模型。但除非你要打造的代理（agent）只依賴外部資料、只依賴例如公開可得的資訊，否則這個模型就必須以某種方式與你的專有資訊結合。

Now if you think about any enterprise, you think about any large agency, the biggest challenge is now you're talking about many, many perabytes, if not exabytes of information, information that's constantly being created, information that's constantly changing. And so this really ends up being a situation where you have to bring the model to the data. The data is just too much to take to the model. And more importantly, that data is your secret sauce. So you never want to have it completely exit your organization anyways.

現在如果你想想任何企業、任何大型機構，最大的挑戰在於你面對的是數以百萬億位元組（petabytes），甚至是艾位元組（exabytes）等級的資訊；而且資訊不斷被產生、也不斷在變動。因此這最後會變成一種情況：你必須把模型帶到資料那裡。資料量太大，無法把資料搬到模型那裡。更重要的是，那些資料是你的獨門秘方。所以你無論如何都不希望它完全離開你的組織。

And so that's really why as you think about what people are building with harnesses and so on, the most important element in that is sort of the data retrieval or the context layer and when you are trying to get that context for your LLM, for your agent, you have to worry about accuracy, you have to worry about speed, and you have to worry about cost.

因此，當你思考人們用 harness 等在打造什麼時，其中最重要的元素其實是資料擷取或情境層（context layer）。而當你要為你的 LLM、為你的代理取得那個情境時，你必須顧慮準確性、顧慮速度，也必須顧慮成本。

And what that means is you really want to try and precompute as much of that context ahead of time as possible. So your model isn't just constantly trying to sift through all of the data every single time, which is a very expensive, very inefficient, very slow approach. And that's what we do. That's where we fit in.

這代表你真的會希望盡可能在事前預先計算（precompute）那些情境。如此一來，你的模型就不需要每一次都不斷在所有資料中篩選，因為那是一種非常昂貴、非常低效率、非常慢的方法。而這正是我們在做的事。這就是我們的切入點。

That's the reason why customers turn to us, because we're able to make their agents perform better, we are able to make their agents more secure in how they operate, we are able to provide just the right context to their agents, and we are able to reduce cost and give them that balance of both using proprietary models where it makes sense using open models where that's the best approach.

這也是客戶選擇我們的原因：我們能讓他們的代理表現更好；我們能讓他們的代理在運作方式上更安全；我們能為他們的代理提供恰到好處的情境；同時我們也能降低成本，並在「在合理之處使用專有模型」與「在最佳情境下使用開放模型」之間，替他們取得平衡。

So that flexibility, that deployment choice, all of this is how people are using us today. And that's why we believe that this is something that's an enduring motion for us. It's an enduring area for us to grow on.

所以，這種彈性、這種部署選擇，這些都是人們今天使用我們的方式。也因此我們相信，這會是我們長期持續的動能。這會是我們可以長期成長的領域。

Got it. Maybe that's super helpful color. And maybe just for a follow-up. Security as a percentage of total revenue and in a post-Mythos world, how do we think about contribution from that business relative to the rest of the Elastic platform? Thank you.

了解。這些補充非常有幫助。我再追問一題。在 Mythos 併購之後的情況下，安全（Security）占總營收的比重，以及我們該如何看待該業務相對於 Elastic 平台其他部分的貢獻？謝謝。

As a percentage of revenue, we don't disclose that, Brian. But in terms of growth, Security remains a very strong growth vector for us. And we've highlighted this in the press earnings call as well, as to the contracts and the customers that we have on the Security side. So very pleased with how that's performing, and it remains to be a high-performing, high-growth segment for us.

就營收占比而言，我們不揭露這個數字，Brian。但就成長而言，Security 仍然是我們非常強勁的成長向量。我們也在新聞稿與財報電話會議中強調過這點，包括我們在 Security 方面的合約與客戶。因此我們對它的表現非常滿意，而且它仍然是我們高表現、高成長的業務區塊。

Even this quarter, if I may just add to what Navam said, we had -- Security was -- grew incredibly well. The order roughly was Security, AI, search AI, and then observability. And with observabiliity, with what we're doing around metrics, the deductive acquisition, like that's the third pillar of the stool, if you will. That's what gives us a lot of optimism in the future. So really, like we feel really good about the way our platform story is evolving here.

如果我可以補充 Navam 的說法，即便在本季，我們的 Security —— 成長非常亮眼。大致的排序是：Security、AI、Search AI，然後是可觀測性（observability）。而在可觀測性方面，包含我們在指標（metrics）上的作為、Deductive 的收購等，那可以說是三腳凳的第三支腳。這也是讓我們對未來非常樂觀的原因。所以整體而言，我們對平台故事在這裡的演進方式感到非常好。

Thank you.

謝謝。

All right, thanks, Brian. Next question, please.

好的，謝謝你，Brian。請下一題。

Rob Owens, Piper Sandler.

Piper Sandler 的 Rob Owens。

Thanks for the question, Alex. And good afternoon, everybody. In your prepared remarks, early on, you talked about success in the quarter. You talked about Search and AI and Security. And I know you've got new capabilities in observability, Ash, and you just mentioned some them. But maybe you can drill down relative to the metrics opportunities, some of the new pricing dynamics that you offer and just what customer feedback or acceptance has been at this point?

謝謝你的提問，Alex。各位午安。在你們事先準備的講稿中，一開始你談到本季的成功。你提到了 Search、AI 與 Security。我知道你們在可觀測性方面也有新的能力，Ash，你剛剛也提到其中一些。但也許你可以更深入談談相對於指標（metrics）的機會、你們提供的一些新的定價動態，以及到目前為止客戶的回饋或接受度如何？

Yeah. Thanks for the question. And Rob, the way we have built our absorbability business over the years is starting with logs. As you know, log analytics was where we started, because the messier the logs, the more capable our solution has been in giving you the ability to do full tech search through those logs, to do analytics on those logs. And so our strength in log analytics continues. It's been a huge area for us.

好的。謝謝你的問題。Rob，我們多年來建立可觀測性業務的方式，是從日誌（logs）開始。如你所知，我們是從日誌分析起家，因為日誌越雜亂，我們的解決方案就越能展現能力，讓你能在那些日誌中做完整的文字搜尋，也能對那些日誌做分析。因此我們在日誌分析上的優勢仍然持續。這一直是我們非常重要的領域。

And over the years, we've continually made our platform more efficient for log analytics, which is another reason why we continue to do well in that area. But sort of expanding from there has been an area where, as we've looked at the market, what we realized was metrics. Because of AI and what's been going on in terms of people building these agents, that's an area where we didn't have that same kind of strength, we didn't have that same kind of performance.

而且多年來，我們持續讓平台在日誌分析上更有效率，這也是我們在該領域持續表現良好的另一個原因。但從那裡往外擴展的部分，當我們觀察市場時，我們意識到的是指標（metrics）。由於 AI 以及人們在打造這些代理方面的發展，這是一個我們當時沒有同樣優勢、也沒有同樣效能的領域。

And so about 1.5 years ago or so, we started working on a completely novel back-end to Elasticsearch that allowed us to have not just the regular document store model that we had in Elasticsearch, but also a column or store back end and all accessible through the same API, because again, we want to make it easy for people to adopt this column in our back end. And this column or back end has been really tuned for basically all kinds of time series data, so metrics and even simple logs.

因此大約在 1.5 年前左右，我們開始為 Elasticsearch 打造一個全新的後端，讓我們不僅擁有原本在 Elasticsearch 中的常規文件儲存（document store）模型，也同時擁有一個欄式儲存（column store）後端，而且都能透過同一套 API 存取；因為我們希望讓大家更容易採用我們後端的這個欄式能力。而這個欄式後端已經被高度調校，基本上適用於各種時間序列資料（time series data），例如指標，甚至是簡單的日誌。

And this column or approach makes it possible for us to store the data in a much more efficient way. So the storage efficiency is massively higher. The ingest performance is better. The query performance is better. So we get a ton of benefits and it's going to show up most in metrics.

而這種欄式設計或方法，讓我們能以更高效率的方式儲存資料。因此儲存效率大幅提升。資料匯入（ingest）效能更好。查詢效能也更好。所以我們獲得大量好處，而這些最明顯會反映在各項指標（metrics）上。

And in the past, it used to take us double-digit bites to store metrics. We are now able to store a single metric in around 3 bites, which is a huge difference. And now, we are incredibly competitive in the market. This is going to allow us to really take on this area head on.

過去，我們儲存指標通常需要兩位數的位元組（bytes）。現在我們大約用 3 個位元組就能儲存單一指標，差異非常巨大。而且現在，我們在市場上具備極強的競爭力。這將讓我們能真正正面迎戰這個領域。

And we are early, like I have to say. But the early feedback that we've gotten from customers, because we are going to our existing log analytics customers and upselling there, has been very good. So we are excited about the feedback that we are getting. But the way I see it is if we do this right over the next year, multiple years, this is going to be a pretty significant and meaningful area of growth for us.

而且我們還在早期階段，我必須這麼說。但我們從客戶那裡收到的早期回饋非常好，因為我們正向既有的日誌分析（log analytics）客戶推進並進行加值銷售（upsell）。所以我們對目前收到的回饋感到振奮。但我看法是，如果我們在接下來一年、甚至數年把這件事做對，這將成為我們相當顯著且有意義的成長領域。

Great. And speaking of early, you mentioned a number of autonomous innovations this quarter across both security and observability. So curious, just early feedback from customers. Obviously, the Security landscape is changing rapidly. So for those on the bleeding edge, how are they consuming what does overall consumption look like? Or what's that relative state of change for those that are moving to some of these autonomous capabilities?

很好。說到早期，你提到本季在資安與可觀測性兩方面都有多項自主式創新。所以我想了解一下客戶的早期回饋。顯然，資安態勢正在快速變化。那麼對於走在最前沿的客戶，他們如何使用？整體使用量（consumption）看起來如何？或者對於正在轉向這些自主能力的客戶而言，變化的相對狀態是什麼？

Our AI SOC capabilities on the Security end have been a big reason for our success in Security. So you've been seeing us do very well in Security for the last many quarters. And I attribute a lot of that to the investments that we made and the differentiation that we have in our agentic capabilities when it comes to Security.

在資安端，我們的 AI SOC 能力一直是我們在資安領域成功的重要原因。因此你看到我們在過去許多個季度於資安表現非常好。我把其中很大一部分歸功於我們在資安的代理式（agentic）能力上的投入與差異化。

And you know, the biggest differentiation that I still hear from our customers is not only do we have a very, very complete set of capabilities out of the box. But unlike others who have a black box approach to AI, we have more of an approach where we allow you to see what's under the covers. You can see the skills. You can see the tools inside the harness inside the Security harness that we built.

而且你知道，我仍然從客戶那裡聽到的最大差異化在於：我們不僅提供非常、非常完整的開箱即用能力組合。而且不同於其他採用 AI 黑盒子作法的廠商，我們更偏向讓你看見「引擎蓋底下」的內容。你可以看到各種技能（skills）。你可以看到我們所打造的資安框架（Security harness）中，那個框架裡的工具。

So you can complement it, you can enhance it, you can do more with it. That is a big differentiator. Because at the end of the day, we believe that models are going to keep getting better and for different tasks, some tasks, you're going to prefer to use cloud, others you're going to prefer to use Gemini. For something else, you might use an open source model.

因此你可以補強它、強化它，並用它做更多事情。這是一個很大的差異化。因為歸根結底，我們相信模型會持續變得更好；而針對不同任務，有些任務你會偏好使用雲端模型，另一些你會偏好使用 Gemini。至於其他情境，你可能會使用開源模型。

Also, skills will continue to evolve. Harnesses will continue to get better and we believe that giving that openness and choice to our customers will be an enduring differentiator. And that's what we are seeing so far.

同時，技能也會持續演進。框架（harnesses）也會持續變得更好；我們相信，給客戶這種開放性與選擇權，將會是長期且持久的差異化。而這正是我們目前所看到的。

Thanks, Rob, and just reminder about our metrics webinar on September 22nd, that information's going to be posted on the IR website. And with that, let's go to the next question.

謝謝你，Rob，也提醒一下：我們在 9 月 22 日有一場關於指標（metrics）的網路研討會，相關資訊將會公布在投資人關係（IR）網站上。那麼接下來我們進入下一個問題。

Raimo Lenschow, Barclays.

Barclays 的 Raimo Lenschow。

Perfect. Thank you. Congrats from me as well, a great quarter. A couple of weeks ago, you launched Kubernetes capability on the observability side. Can you speak to the importance of that because that seems to be closing a really important gap in the offering and maybe just speak to what's possible now?

太好了。謝謝。我也向你們道賀，這是一個很棒的季度。幾週前，你們在可觀測性方面推出了 Kubernetes 能力。你能談談這件事的重要性嗎？因為看起來這補上了產品供給中一個非常重要的缺口；也請談談現在可以做到哪些事情？

Yeah. A lot of it has to do, Raimo, with our focus on having a great end-to-end experience and the areas that we want to make sure customers adopt us increasingly for is using us for metrics, using us for infrastructure monitoring, and as you know, a lot of agents are being deployed on Kubernetes, environments and getting that right with a great end-to-end experience with dashboards that light up out of the box with sort of native sport, not just for open telemetry-based ingestion and analytics but also support for Prometheus data and PromQL, like these are areas where we've invested a lot.

是的。Raimo，這很大一部分與我們聚焦於提供優秀的端到端體驗有關；而我們希望客戶越來越多採用我們的領域包括：用我們做指標（metrics）、用我們做基礎設施監控（infrastructure monitoring）。而如你所知，很多代理（agents）都部署在 Kubernetes 環境中；把這件事做好、提供優秀的端到端體驗，並讓儀表板能開箱即用地亮起來，提供某種原生支援（native support），不僅支援基於 OpenTelemetry 的資料匯入與分析，也支援 Prometheus 資料與 PromQL——這些都是我們投入很多的領域。

Even in the prepared remarks, the customer that I talked about that chose us for metrics, that customer moved to us because we made it so easy for them to bring their Prometheus data directly into Elastic without having to transform things without having to change things. And that's a big differentiator. So you're absolutely right to look at that and see that, that is a key element. It is one of many investments that we've been making on the observability side. And that's what is quite -- we find that to be quite exciting for the days ahead.

即使在事先準備的講稿中，我提到那位選擇我們來做指標（metrics）的客戶；那位客戶轉向我們，是因為我們讓他們能非常容易地把 Prometheus 資料直接導入 Elastic，而不需要做轉換、不需要改動任何東西。而這是一個很大的差異化。所以你完全有理由這樣看，並認為那是一個關鍵要素。這只是我們在可觀測性方面所做眾多投資之一。而這也讓我們對接下來的日子感到相當興奮。

Perfect. Yeah. No, thank you. Yeah, same view here. And another one for you, like it's -- like you only had your Q1, but you raised the full year by more than the beat in Q1 nowadays and software, everyone is very conservative, et cetera. What gives you the confidence there? What are you seeing in terms of pipeline, et cetera? Thank you.

很好。是的。不，謝謝你。是的，我這邊看法也一樣。另外再問一個：你們才剛有 Q1，但你們把全年展望上調的幅度，甚至超過了 Q1 的超預期幅度；而現在在軟體業，大家都非常保守等等。是什麼讓你們有這樣的信心？你們在管線（pipeline）等方面看到了什麼？謝謝。

Yeah. Thanks, Raimo. I don't think the guidance philosophy has changed much compared to what we've done in the past. We've always taken a prudent and risk-adjusted view to guidance. But like you said, it is only Q1, but it was a good start to fiscal '27. And we got some strong data points from that quarter. Our cRPO, obviously, which was a good number in the RPO number as well as the $100,000 adds.

是的。謝謝你，Raimo。我不認為我們的指引（guidance）哲學相較過去有太大改變。我們一向以審慎、並經風險調整的角度來提供指引。但如你所說，這才只是 Q1，不過這是 27 財年的一個良好開局。而且我們從該季度得到一些強勁的數據點。例如我們的 cRPO，顯然表現不錯；RPO 數字以及 10 萬美元新增客戶（$100,000 adds）也都很好。

Apart from that, there were three specific drivers that we saw internally as well. First is the strong pipeline build, both for the second quarter and the full year, the out quarter pipeline build is looking good. Second is the consumption against the cRPO committed cRPO number performed well. And then third, we expected a certain productivity and capacity increase given the hiring that we did, and we we're seeing that,.

除此之外，我們內部也看到三個具體驅動因素。第一是強勁的管線建立，不論是第二季或全年，遠期季度（out quarter）的管線建立看起來也不錯。第二是相對於 cRPO（已承諾 cRPO）數字的使用量（consumption）表現良好。第三，我們預期因為先前的招募，生產力與產能會有所提升，而我們也確實看到了這點。

And that's allowing us to have the confidence on the go-get number that we need to do for the net new revenue side for the rest of the year. So that's the reason we guided the way we did and we're encouraged about the revenue trajectory for the year. So it hasn't changed -- the philosophy hasn't changed, but we feel good about what we need to go achieve for the rest of the year.

而這讓我們對於今年剩餘期間在淨新增營收（net new revenue）方面需要達成的目標數字更有信心。因此我們才會以這樣的方式給出指引，也對今年的營收走勢感到鼓舞。所以哲學沒有改變——哲學並沒有改變，但我們對於接下來一年其餘時間需要去達成的事情感覺良好。

Thanks, Raimo. Next question, please.

謝謝你，Raimo。請下一題。

Howard Ma, Guggenheim.

Howard Ma，Guggenheim。

Great, thanks for taking the question and I want to add my congratulations, too, on a strong quarter. My question is, is the acceleration that you're seeing, would you say that that's directly attributable to higher multiproduct adoption driven by the realization that Elastic is an attractive solution for both content engineering and managing the agentic-driven proliferation in telemetry data as opposed to point solutions. And does your guidance factor in material acceleration in cross-sell among various use cases?

太好了，謝謝讓我提問，我也想對你們這一季的強勁表現表示祝賀。我的問題是，你們看到的這種加速，你會說這是直接歸因於更高的多產品採用嗎？其背後的驅動因素是客戶意識到 Elastic 對於內容工程以及管理由代理式（agentic）驅動的遙測資料激增而言，都是比點狀解決方案更具吸引力的方案。另外，你們的指引是否已納入在各種使用情境之間交叉銷售出現顯著加速的因素？

Yeah. Maybe let me touch upon that and then Navam might -- let Navam talk about all things related to guidance. But just if you think about our motion, it's always how it's been very similar, right? So we have a platform that allows customers to do multiple things. And what we focus on is making sure that our platform is incredibly good in each of those areas.

是的。也許我先談一下這點，然後再讓 Navam 來談所有與指引相關的內容。不過如果你想想我們的推進方式，一直以來都很類似，對吧？我們有一個平台，讓客戶可以做多種事情。而我們專注的是確保我們的平台在每一個領域都非常出色。

So each of our solutions, our focus is on making sure that those solutions are able to be differentiated and stand on their own and win on their own. And that becomes the tip of the spear for us. It's our land and then expand strategy because once we land with one solution, then the goal becomes how do we get the other solution in there and the third solution in there.

因此，對於我們每一個解決方案，我們的重點是確保這些解決方案具備差異化，能夠獨立成立、獨立取勝。而這就成為我們的尖刀。這就是我們的「先落地、再擴張」策略：一旦我們以某個解決方案落地，接下來的目標就是如何把另一個解決方案導入，然後再導入第三個解決方案。

And obviously, like we had talked even at our Analyst Day, or last Analyst Day, the customers that grow the fastest are the ones that adopt us for all three solutions. So that land and expand motion has continued, and it's not that necessarily that has inflected in any way. But this is what you're seeing here is just the right kind of progression.

而且很明顯，就像我們在分析師日（或上一次分析師日）談到的，成長最快的客戶是那些三個解決方案都採用我們的客戶。所以這種「先落地、再擴張」的推進方式一直持續著，並不一定是在任何方面出現了拐點。但你現在看到的，就是正確的進展節奏。

This is a motion that we've been driving. Probably the biggest thing that has happened is as our focus on our enterprise selling motion, the segmentation change that we did two years ago, as that has matured, we are seeing the benefits of that play out very, very nicely. So our land and expand is working, in all three solution areas we are seeing the right kind of movement.

這是我們一直在推動的模式。可能最大的變化是：隨著我們對企業銷售推進方式的聚焦、以及兩年前做的分眾（segmentation）調整逐漸成熟，我們正非常、非常明顯地看到其效益。因此，我們的「先落地、再擴張」正在奏效，在三個解決方案領域我們都看到正確的動能。

And look, it comes down to making sure that you are positioning your platform, your product in the right way. And then our sales teams know how to position the multiple platform -- the multiple product strategy within that platform. And that's why we feel so good about what this is going to mean for the future.

而且你看，歸根結底在於確保你以正確的方式來定位你的平台、你的產品。接著，我們的銷售團隊也知道如何在該平台內，去定位多平台——多產品策略。這也是為什麼我們對這對未來的意義感到非常樂觀。

In terms of the guidance, Howard, there's nothing different implied in how our land expand motion works. Obviously, there's a lot of -- a lot of our revenue comes from expand more than land. Land is the entry point and then expansion is where the dollars come in over time. And that dynamic comes from both expansion of the existing product that you bought and also cross-sell. So there isn't anything in the guidance that we've taken into account a different behavior from our customers from what we currently see.

至於指引，Howard，我們的「先落地、再擴張」運作方式並沒有暗示任何不同。很明顯，我們的營收有很大一部分來自「擴張」而非「落地」。落地是入口，然後擴張才是隨時間帶來收入的地方。而這種動態同時來自於你已購買產品的既有擴用，也來自交叉銷售。所以在指引中，我們並沒有納入任何與目前所見不同的客戶行為假設。

Okay. Thanks, Howard. Next question, please.

好的。謝謝你，Howard。請下一題。

(Operator Instructions) Radi Sultan, UBS.

（接線員指示）Radi Sultan，UBS。

Awesome, yeah, thanks for taking my question. Ash, in your prepared remarks, you called out a SIEM migration, which I believe you said got done under a month with some of your automated migration tooling. I just wanted to ask, how much of a benefit are you seeing to cloud consumption from AI accelerating migrations on the SIEM side, but also maybe just more broadly?

太棒了，謝謝讓我提問。Ash，在你準備好的發言中，你提到一個 SIEM 遷移案，我記得你說透過你們的一些自動化遷移工具，在不到一個月內就完成了。我想請教的是，你們看到 AI 加速 SIEM 端遷移，對雲端用量（cloud consumption）帶來多大的助益？以及更廣泛來看是否也是如此？

Yes. So the consumption that we saw was -- the strength in consumption that we saw this quarter was broad-based. It was not related to any one customer. But what I talked about there, which is really important to understand is, at the end of the day, SIEM has never been sort of greenfield, right? SIEM as a space has been around for a long time. And our motion has been to displace the incumbents who are not innovating at the same rate.

是的。我們本季看到的用量——本季用量的強勁表現——是全面性的。並非與任何單一客戶有關。但我在那裡提到、而且非常重要的一點是：說到底，SIEM 從來就不是所謂的綠地市場（greenfield），對吧？SIEM 這個領域已經存在很久了。而我們的策略一直是取代那些創新速度跟不上的既有領導廠商。

What's really changing there, to be honest, is the environment, people are really worried about what it means to protect your environment, protect your agencies and so on in a post-Mythos world. And it's not just Mythos. There are so many very, very capable models out there, not just commercial models, but open source models that give you the ability to really discover vulnerabilities and then act upon them.

老實說，真正正在改變的是環境：在後 Mythos 時代，人們非常擔心保護你的環境、保護你的代理（agents）等等意味著什麼。而且不只是 Mythos。市面上有非常多、非常有能力的模型，不僅是商用模型，還有開源模型，讓你能夠真正發現弱點，並採取行動。

So you have to assume that people who are trying to do harm now have the ability to access these models. So defenders are having to move faster and so on. So that is driving the momentum for our business and the ability with our tooling with our automated tooling to migrate these customers from their incumbent solution to our product, our platform, we have gotten really, really good at it.

所以你必須假設，現在試圖造成傷害的人也有能力取得這些模型。因此防禦方就必須更快行動，等等。這正在推動我們業務的動能；而且憑藉我們的工具、我們的自動化工具，把這些客戶從既有方案遷移到我們的產品、我們的平台，我們已經做得非常、非常成熟。

This was a very significant sized agency, and we were able to move their massive real estate over in one month -- in under one month. And that is just the thing that gives our field a lot of confidence. It is what gives our customers a lot of confidence, because as they see these things happening over and over again, it gives them confidence that they can safely move to Elastic and that we will be able to make them successful quickly.

這是一個規模非常大的機構，我們能在一個月內——不到一個月——把他們龐大的資產版圖遷移過來。而這正是讓我們前線團隊非常有信心的事情。這也讓客戶非常有信心，因為當他們一次又一次看到這些事情發生，就會相信他們可以安全地轉向 Elastic，而我們也能夠快速讓他們成功。

All right, thank you. Next question, please.

好的，謝謝。請下一題。

Shrenik Qatari, Robert Baird.

Shrenik Qatari，Robert Baird。

Ms. Qatari, your line is open from our end. You have to unmute on yours.

Qatari 女士，我們這邊已為你開線。你那邊需要解除靜音。

All right, I think we need to go to the next question then.

好的，那我想我們需要進到下一題了。

Mike Cikos.

Mike Cikos。

Hey guys, this is Matt Calitri on for Mike Cikos over at Needham. Thank you for taking our questions. And you gave some great color on that 100,000 cohort and some of the AI adoption, which we appreciate. Are there any other clear underlying expansion trends you can share regarding older cohorts versus newer ones or smaller customers versus larger ones? Or is it more so just expansion across the board and you're waiting for that trailing 12 months net expansion number to catch up, as you mentioned in the prepared remarks?

各位好，我是 Needham 的 Matt Calitri，代替 Mike Cikos 提問。謝謝讓我們提問。你們對 100,000 那個客群（cohort）以及一些 AI 採用情況提供了很好的補充說明，我們很感謝。關於較舊客群相較於較新客群，或較小客戶相較於較大客戶，你們是否還能分享任何其他明確的底層擴張趨勢？或者其實更像是全面性的擴張，而你們正如在準備稿中提到的，等待過去 12 個月的淨擴張率（net expansion）指標追上來？

Yes. Thanks, Matt. So the trailing 12-month number on the ER, the NER side is impacted by the trailing 12-month constant currency growth. So that's a separate factor. And as constant currency growth improves alongside guidance that we've provided, it's going to take a lagged effect for the NER to catch up. So that's the comment on the NER side that I was making.

是的。謝謝你，Matt。所以，財報（ER）中 NER 端的過去 12 個月數字，會受到過去 12 個月固定匯率（constant currency）成長的影響。所以那是另一個因素。而隨著固定匯率成長改善、並與我們提供的指引同步提升，NER 需要一段落後時間才會追上。所以這就是我在 NER 端所做的評論。

But on the cohort behavior, the cohort behavior that we talk about is basically a durable land-expand motion, so we get our customers in. And there is a long period of durable expansion that we expect from every one of those cohorts and that's continuing. And we also expect to see and we see the AI cohort show a differential in our growth, meaning the customers who are using our AI features effectively expanding at a slightly higher rate than the ones that aren't.

但就同批客戶（cohort）行為而言，我們所談的 cohort 行為基本上是一種可持續的「先落地、再擴張」（land-and-expand）動能，因此我們先把客戶導入。我們預期每一個 cohort 都會有一段長期且可持續的擴張期，而這個趨勢仍在延續。此外，我們也預期並且確實看到 AI cohort 在成長上呈現差異化，也就是使用我們 AI 功能的客戶，其有效擴張速度略高於未使用者。

So those are the two dynamics that we see in our expansion rates and those trends are continuing. And as I mentioned, NERs, which is trailing picks up alongside the revenue growth rate that we expect to post for the year.

所以，這就是我們在擴張率上看到的兩個動態，而這些趨勢仍在持續。如我先前提到，NER（淨擴張率）屬於落後指標，會隨著我們預期今年將呈現的營收成長率而回升。

Thanks, Matt. Next question, please.

謝謝你，Matt。請下一題。

Sanjit Singh, Morgan Stanley.

Sanjit Singh，摩根士丹利。

Yeah, thank you for taking the questions.Ash, I see a lot of the passion on the SIEM side and obviously throughout the other core parts of the business as well. I wanted to come back to the AI search part of the business. We have a lot of data platform players trying to solve that context, Symantec problem. I think Peppard it in a proprietary way. So from the Elastic perspective, in terms of getting that agent performance and building that map for that agent, why is Elastic able to do that better than some of the other data platform peers that are trying to solve that similar problem?

是的，謝謝讓我提問。Ash，我看到你們在 SIEM 方面充滿熱情，顯然在業務其他核心部分也是如此。我想回到 AI 搜尋這塊業務。我們看到很多資料平台業者都在嘗試解決那個情境、Symantec 的問題。我認為 Peppard 以專有方式把它包裝起來。所以從 Elastic 的角度來看，在取得該代理（agent）的效能並為該代理建立那張地圖方面，為什麼 Elastic 能比其他也在解決類似問題的資料平台同業做得更好？

At the simple answer, Sanjit, is because we've always been optimized for dealing with messy data, for dealing with unstructured data. Most of the data platforms that you're talking about that you might be thinking about were all designed to work with structured information. And fundamentally, although they might have had a sort of no SQL view of the world, it was still sort of designed with strict schemes structure in mind. Elastic has always been different in that sense.

Sanjit，最簡單的答案是，因為我們一直以來都針對處理雜亂資料、處理非結構化資料做最佳化。你提到、你可能想到的大多數資料平台，原本都是為了處理結構化資訊而設計。而且從根本上說，即便它們可能採用了某種 NoSQL 的世界觀，仍然是在嚴格的 schema 結構思維下設計的。Elastic 在這方面一直都不同。

If you think about Elastic, we started as a document store with an inverted index that allows you to put any and all kind of information in it, which is why we were always used for search, which is why we then moved into log analytics because all of these things end up being very unstructured. The schema keeps evolving. And if you think about the kind of information that is being used primarily, a lot of it in AI is this kind of unstructured data.

如果你想想 Elastic，我們一開始是以文件儲存（document store）起家，搭配倒排索引（inverted index），讓你可以把任何各式各樣的資訊放進去；這也是為什麼我們一直被用於搜尋，之後又延伸到日誌分析，因為這些東西最後都非常非結構化。schema 也會不斷演進。而如果你看主要被使用的資訊類型，在 AI 裡面有很大一部分就是這種非結構化資料。

So our strength in terms of being able to bring in this data, being able to then analyze it, search across it the capabilities that we've built, not just with vector search but also around hybrid search, the harnesses that we've built on top of it, all of this Vigia models, our ability to do reranking and so on. We are way ahead of the competition, especially when you look at things from this unstructured lens.

因此，我們在把這些資料導入、再進一步分析、跨資料搜尋方面的能力——不只是向量搜尋（vector search），也包括混合式搜尋（hybrid search），以及我們在其上建立的各種工具與框架、所有這些 Vigia 模型、我們進行重排序（reranking）等能力——特別是從「非結構化」這個視角來看，我們明顯領先競爭對手。

And frankly, Sanjit, we feel that we are still very early in this overall phase of AI adoption. Most organizations are only now starting to really deploy things in a meaningful way. So as that grows, as we have more penetration within our customer base, I think that's going to be what really helps us continue this momentum for a very long time.

坦白說，Sanjit，我們認為整體 AI 採用仍處於非常早期的階段。多數組織現在才剛開始以有意義的方式真正部署。因此，隨著這個趨勢成長、我們在客戶基礎中的滲透率提高，我認為這將真正幫助我們在很長一段時間內持續維持這股動能。

All right. Thanks, Sanjit. Next question please.

好的。謝謝你，Sanjit。請下一題。

Ryan MacWilliams, Wells Fargo.

Ryan MacWilliams，富國銀行。

Hey, thanks for taking the question. One for Navam. How should we think about the gross margins in the quarter? It looks like they were just slightly lower versus previous quarter. I mean perhaps some impact from the mix shift from cloud here. But anything else worth calling out? And maybe how should we think about gross margins for the rest of the year? Thanks.

嗨，謝謝讓我提問。有一題想問 Navam。我們應該如何看待本季的毛利率？看起來相較前一季略低一些。我想可能是雲端組合占比變動帶來一些影響。但還有其他值得特別指出的因素嗎？另外，今年剩餘期間的毛利率應該如何看？謝謝。

Yeah. Look, we're very pleased with how our subscription gross margins are performing. It's remained above 80%. And really, there's nothing specific in terms of a trend that emerged this quarter. But over the longer term, what we expect is that these gross margins are expected to improve as we see benefits from things like serverless as it gets to scale, so there's going to be fluctuations quarter over quarter, but nothing specific this quarter from a trend perspective on margins.

是的。你看，我們對訂閱毛利率的表現非常滿意。它一直維持在 80% 以上。而且就本季而言，並沒有出現任何特定的趨勢變化。但從較長期來看，我們預期隨著無伺服器（serverless）規模化帶來的效益，這些毛利率將會改善；因此季度之間會有波動，但就毛利率趨勢而言，本季沒有任何特別的因素。

Great color. Thank you.

很好的補充說明。謝謝。

This concludes our question-and-answer session. I would like to turn the conference back over to Ash Kulkarni for any closing remarks.

問答環節到此結束。我想把電話會議交回給 Ash Kulkarni，請他做任何結語。

Thank you very much for joining our call today. We are pleased to report a strong start to the year. We're extremely proud of our results and very excited about the opportunity ahead. Lastly, please join us on September 22nd for our public webinar on metrics. Have a great day.

非常感謝各位今天參加我們的電話會議。我們很高興報告今年有一個強勁的開局。我們對成果感到非常自豪，也對未來的機會感到非常興奮。最後，請在 9 月 22 日加入我們的指標公開線上研討會。祝各位有美好的一天。

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

本次電話會議到此結束。感謝各位參加今天的簡報。您現在可以掛線。