Innodata Inc (INOD) 2024 Q1 法說會逐字稿

Greetings. Welcome to the Innodata first-quarter 2024 results conference call. (Operator instructions) Please note this conference is being recorded.

問候。歡迎參加 Innodata 2024 年第一季業績電話會議。（操作員說明）請注意，本次會議正在錄製中。

I will now turn the conference over to your host, Amy Agress, General Counsel at Innodata. You may begin.

我現在將會議交給主持人 Innodata 總法律顧問 Amy Agress。你可以開始了。

Thank you, Paul. Good afternoon, everyone. Thank you for joining us today. Our speakers today are Jack Abuhoff, CEO of Innodata; and Marissa Espineli, Interim CFO. Also on the call today is Aneesh Pendharkar, Senior Vice President, Finance and Corporate Development. We'll hear from Jack first, who will provide perspective about the business, and then Marissa will follow with a review of our results for the first quarter. We'll then take your questions.

謝謝你，保羅。大家下午好。感謝您今天加入我們。今天我們的演講者是 Innodata 執行長 Jack Abuhoff；臨時財務長瑪麗莎‧埃斯皮內利 (Marissa Espineli)。今天參加電話會議的還有財務和企業發展資深副總裁 Aneesh Pendharkar。我們將首先聽取傑克的意見，他將提供有關業務的觀點，然後瑪麗莎將回顧我們第一季的業績。然後我們將回答您的問題。

Before we get started, I'd like to remind everyone that during this call, we will be making forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, assumptions, and estimates and are subject to risks and uncertainties. Actual results could differ materially from those contemplated by these forward-looking statements, and factors that could cause these results to differ materially are set forth in today's earnings press release in the Risk Factors section of our Form 10-K, Form 10-Q, and other reports and filings with the Securities and Exchange Commission. We undertake no obligation to update forward-looking information.

在開始之前，我想提醒大家，在這次電話會議中，我們將做出前瞻性陳述，即對未來事件的預測、預測或其他陳述。這些陳述是基於目前的預期、假設和估計，並受到風險和不確定性的影響。實際結果可能與這些前瞻性陳述預期的結果有重大差異，並可能導致這些結果存在重大差異的因素在今天的收益新聞稿中的表格10-K、表格10-Q、表格10-Q 的風險因素部分中列出。我們不承擔更新前瞻性資訊的義務。

In addition, during this call, we may discuss certain non-GAAP financial measures in our SEC filings, which are posted on our website. You will find additional disclosures regarding these non-GAAP financial measures, including reconciliation of these measures with comparable GAAP measures.

此外，在本次電話會議期間，我們可能會討論我們向 SEC 提交的文件中的某些非 GAAP 財務措施，這些文件發佈在我們的網站上。您將找到有關這些非 GAAP 財務指標的其他揭露信息，包括這些指標與可比較 GAAP 指標的調整表。

Thank you. I will now turn the call over to Jack.

謝謝。我現在會把電話轉給傑克。

Good afternoon. We are very excited to be here with you today. We have lots of updates to share regarding the accelerated momentum we are experiencing across our business. First and foremost, we are pleased to announce record revenues for the quarter of $26.5 million, representing 41% year-over-year growth. Our growth in the quarter was driven by the value we are bringing to help the world's largest tech companies build AI large language models, or LLMs. As a result of accelerated business momentum, we are raising our 2024 revenue guidance to an expected organic revenue growth of at least 40% year over year. This is double the growth rate we guided to last quarter.

午安.我們很高興今天能和你們在一起。關於我們整個業務的加速發展勢頭，我們有許多最新消息可以分享。首先，我們很高興地宣布本季營收達到創紀錄的 2,650 萬美元，年增 41%。我們本季的成長是由我們為幫助世界上最大的科技公司建立人工智慧大語言模式（LLM）帶來的價值所推動的。由於業務動能加速，我們將 2024 年營收指引上調至預計有機收入年增至少 40%。這是我們上季指導成長率的兩倍。

We are executing a multipronged strategy to deliver -- designed to deliver extraordinary levels of growth over the next several years as we extend what we believe is our early leadership in generative AI solutions. We're focused on providing solutions at three levels of the Gen AI stack at the bottom layer, helping some of the world's largest tech companies and independent software vendors, or ISVs, develop generative AI foundation models. In the middle layer, helping enterprises that prefer not to build models from scratch, but rather to leverage existing LLMs and other AI customized for them with their own data. And at the top layer, building generative AI-enabled platforms that are useful for niche industry requirements.

我們正在執行多管齊下的策略，旨在在未來幾年內實現非凡的成長水平，同時我們將擴大我們在生成人工智慧解決方案方面的早期領導地位。我們專注於在底層的 Gen AI 堆疊的三個層面提供解決方案，幫助一些全球最大的科技公司和獨立軟體供應商 (ISV) 開發生成式 AI 基礎模型。在中間層，幫助那些不喜歡從頭開始建立模型，而是利用現有的法學碩士和其他為他們量身定制的人工智慧和自己的數據的企業。在頂層，建立可滿足利基產業需求的生成式人工智慧平台。

Our primary focus this year is on that first layer of the stack, partnering with some of the world's largest tech companies to develop generative AI foundation models. We are pleased with the success we are having thus far. We entered the year with agreements in place with five of the so-called Magnificent Seven companies, which are our group of well-known, high-performing Big Tech companies, we believe will spend billions of dollars on generative AI data engineering over the next several years.

我們今年的主要重點是堆疊的第一層，與一些世界上最大的科技公司合作開發生成式人工智慧基礎模型。我們對迄今為止所取得的成功感到高興。進入這一年，我們與所謂的七大公司中的五家公司簽訂了協議，這些公司是我們的知名、高性能的大型科技公司集團，我們相信接下來將在生成人工智能數據工程上花費數十億美元幾年。

We announced today that we rewarded yet another program expansion from one of our Big Tech customers. We're valuing this expansion at approximately $23.5 million of annualized run rate revenue once implemented. This is on top of the $20 million in new programs with this customer we announced less than two weeks ago on April 24. We expect that these programs will ramp up over the next two months.

我們今天宣布，我們獎勵了我們的一個大型科技客戶的另一個計劃擴展。我們對此次擴張的估值約為 2,350 萬美元的年化營運收入。這是我們在不到兩週前的 4 月 24 日宣布的針對該客戶的 2000 萬美元新計劃的基礎上的。我們預計這些計劃將在未來兩個月內逐步增加。

While our customer agreements typically contain early termination upon notice provisions, we believe this customer is committed to a significant multiyear LLM strategy from which we stand to benefit. In fact, we are in discussions with this customer regarding potential new programs and expansions beyond what we have announced so far.

雖然我們的客戶協議通常包含提前終止通知的條款，但我們相信該客戶致力於實施重要的多年法學碩士策略，我們將從中受益。事實上，我們正​​在與該客戶討論超出我們迄今為止宣布的潛在新計劃和擴展。

We also signed two additional Big Tech companies, a large, prominent generative AI company and a large prominent consumer-facing ISV, investing substantially in generative AI foundation models. As a result of these new wins, we now serve seven Big Tech customers. We believe we will continue to grow with these customer relationships in 2024, and that we may grow some of them, possibly quite substantially. For Big Tech customers, we provide a broad range of services to support their generative AI programs. This includes creating instruction datasets, which you can think of as the programming behind large language models. It also includes human preference data used in reinforcement learning and reward modeling to align models to human preferences and build guardrails against toxic biases and harmful responses.

我們還簽署了另外兩家大型科技公司，一家大型、著名的生成式人工智慧公司和一家面向消費者的大型獨立軟體開發商，對生成式人工智慧基礎模型進行了大量投資。由於這些新的勝利，我們現在為七家大型科技客戶提供服務。我們相信，到 2024 年，我們將繼續發展這些客戶關係，並且我們可能會擴大其中一些客戶關係，並且可能會大幅成長。對於大型科技客戶，我們提供廣泛的服務來支援他們的生成式人工智慧程式。這包括創建指令資料集，您可以將其視為大型語言模型背後的程式設計。它還包括用於強化學習和獎勵建模的人類偏好數據，以使模型與人類偏好保持一致，並針對有毒偏見和有害反應建立防護欄。

In a blog post last month that accompanied a major release, one of our large Big Tech customers stated that the quality of these instruction datasets has an outsized influence on the performance of their models, and that some of their biggest improvements in model quality come from carefully crafted instruction datasets and multiple rounds of quality assurance. This statement crystallizes why we have become the partner of choice for such customers. We believe we are well-positioned to anticipate Big Tech's changing needs and to grow with them.

在上個月伴隨重大版本發布的一篇部落格文章中，我們的一位大型科技客戶表示，這些指令資料集的品質對其模型的性能有著巨大的影響，並且他們在模型品質方面的一些最大改進來自於精心製作的教學資料集和多輪品質保證。這句話明確了為什麼我們成為這類客戶的首選合作夥伴。我們相信，我們有能力預測大型科技公司不斷變化的需求並與他們一起成長。

It is evident that Big Tech's aspirations extend beyond today's predominantly text-to-text English language models. We foresee expansion in terms of multimodal models, domain and task-specific models, models natively built in more than 30 different languages, and models capable of complex reasoning. All of these dimensions will require modeling with the kind of data that we create. We believe we are still in the early innings of this journey.

顯然，大型科技公司的願望超越了當今主要的文本到文本英語語言模型。我們預計多模態模型、特定於領域和任務的模型、以 30 多種不同語言本地構建的模型以及能夠進行複雜推理的模型將擴展。所有這些維度都需要使用我們創建的資料類型進行建模。我們相信我們仍處於這趟旅程的早期階段。

I encourage you to read the latest quarterly earnings transcripts from the Mag Seven. Generative AI is a prevailing theme with promises of more gen AI models, more gen AI and products, and commitments to multiyear investment cycles and CapEx increases to support aggressive AI research and product development. We believe the emerging enterprise market, which we call the middle layer, consisting of companies across verticals that seek to adopt generative AI technologies to be another important growth factor for Innodata, one that will ultimately dwarf the Big Tech market for us.

我鼓勵您閱讀七大雜誌最新的季度收益記錄。生成式人工智慧是一個盛行的主題，承諾提供更多一代人工智慧模型、更多一代人工智慧和產品，並承諾多年投資週期和資本支出增加，以支援積極的人工智慧研究和產品開發。我們認為，新興企業市場（我們稱之為中間層）由尋求採用生成式人工智慧技術的跨行業公司組成，是 Innodata 的另一個重要成長因素，最終將使我們的大型科技市場相形見絀。

In parallel with executing strategies to penetrate Big Tech, we're taking steps to prepare for what we foresee as a likely explosion in the enterprise space. We believe we are very well-positioned due to our intimate knowledge of the gen AI roadmap of large tech companies, which has enabled us to gain exceptional domain expertise and the future product needs of the enterprise market. We believe that enterprise adoption is about to enter a Cambrian period of explosive growth as a result primarily of three technology developments now underway. I'll explain and illustrate each with examples.

在執行滲透大型科技策略的同時，我們正在採取措施，為我們預見的企業領域可能的爆炸性成長做好準備。我們相信，由於我們對大型科技公司的新一代人工智慧路線圖有深入的了解，我們處於非常有利的位置，這使我們能夠獲得卓越的領域專業知識和企業市場的未來產品需求。我們相信，企業採用即將進入爆發性成長的寒武紀時期，這主要是目前正在進行的三項技術發展的結果。我將用例子來解釋和說明每一個。

Today, enterprise users of generative AI are mostly using ChatGPT as a standalone application. We'll call this level zero use case. For example, if I'm an HR Director at Innodata test with revising Innodata's employee handbook, I can prompt ChatGPT to write a first draft of the vacation policy. Companies are now shifting from this level zero to what we think of as level one. We think of level-one systems as those based on retrieval augmented generation, or RAG, which we believe are likely to become better performing for reasons I will explain shortly.

如今，生成式人工智慧的企業用戶大多將 ChatGPT 作為獨立應用程式使用。我們將此稱為零級用例。例如，如果我是 Innodata test 的人力資源總監，正在修改 Innodata 的員工手冊，我可以提示 ChatGPT 編寫休假政策的初稿。公司現在正在從零級轉向我們所認為的一級。我們認為一級系統是基於檢索增強生成（RAG）的系統，我們相信它可能會變得更好，原因我很快就會解釋。

RAG systems couple search technology and prompt engineering with such a level one system and Innodata employee might prompt an Innodata HR chatbot with a request like, please summarize for me Innodata's vacation policy. A search engine working behind the scenes would then retrieve Innodata's vacation policy from a large document repository and insert it into the prompt of context with an instruction to the LLM to answer the question primarily based on the inserted policy.

RAG 系統將搜尋技術和提示工程與這樣的一級系統結合起來，Innodata 員工可能會向 Innodata HR 聊天機器人提示類似請求，請為我總結一下 Innodata 的假期政策。然後，在幕後工作的搜尋引擎將從大型文件儲存庫中檢索 Innodata 的休假政策，並將其插入上下文提示中，並指示法學碩士主要根據插入的政策回答問題。

RAG-based systems are about to become more useful as the latest crop of soon-to-be-released LLMs or for significantly expanded context windows. A context window refers to the amount of retrieved information that can be included with a prompt. By including more context, the chatbot can become more consistent, relevant, and useful. One of the Big Tech companies is about to release a new model with a context window that is eight times larger than that of OpenAI's GPT-4 Turbo, enabling you to include, for example, 3,000 pages of documents in a single prompt.

作為即將發布的最新一批法學碩士或顯著擴展的上下文窗口，基於 RAG 的系統將變得更加有用。上下文視窗是指可以包含在提示中的檢索資訊量。透過包含更多上下文，聊天機器人可以變得更加一致、相關和有用。一家大型科技公司即將發布一種新模型，其上下文視窗比 OpenAI 的 GPT-4 Turbo 大八倍，使您能夠在單一提示中包含例如 3,000 頁的文件。

Today's expert or advanced expert augmentation systems are, for the most part RAG-based systems, that combine generative AI with humans in the loop to deliver improved productivity. In a few minutes, I'll give you an example of such a system we started working on for a customer in the quarter.

當今的專家或高級專家增強系統大部分都是基於 RAG 的系統，它將生成式 AI 與人類結合起來，以提高生產力。幾分鐘後，我將為您提供一個我們在本季開始為客戶開發的系統的範例。

We believe a second technology development called agentic workflows will enable what we'll call level two systems. With an agentic system, rather than asking a question to a chatbot, you present a goal to a virtual agent. Your virtual agent then accesses multiple back-end systems, and LLMs talk to each other to accomplish your goal. Agentic workflows really open up the kinds of things you can ask computers to do with LLMs. With an agentic system, an Innodata employee might ask a virtual Innodata agent, please look up how many days off Innodata employees get, check how many days off I have left, and request a week off around my son's graduation, so long as there are still available hotels in Boston. Imagine that. Now, while the full realization of agentic workflows may be years away, we believe incremental progress is being achieved and will likely accelerate.

我們相信，稱為代理工作流程的第二種技術開發將實現我們所謂的二級系統。使用代理系統，您無需向聊天機器人提出問題，而是向虛擬代理提出目標。然後，您的虛擬代理訪問多個後端系統，法學碩士相互交談以實現您的目標。代理工作流程確實開啟了您可以要求計算機與法學碩士一起完成的各種事情。使用代理系統，Innodata 員工可能會詢問虛擬 Innodata 代理，請查看 Innodata 員工獲得了多少天休假，檢查我還剩下多少天休假，並在我兒子畢業前後請求一周的休假，只要有波士頓仍有空房。想像一下。現在，雖然代理工作流程的完全實現可能還需要數年時間，但我們相信漸進式的進展正在取得，並且可能會加速。

The third development that we believe will accelerate enterprise adoption is that the cost of training and serving models is likely to go down dramatically, making it possible for enterprises to train and serve models at scale. Once this happens, we believe that companies are likely to want to fine tune their own models rather than relying on RAG-based architectures. We'll call these level three systems.

我們認為將加速企業採用的第三個發展是培訓和服務模式的成本可能會大幅下降，使企業能夠大規模培訓和服務模式。一旦發生這種情況，我們相信公司可能希望微調自己的模型，而不是依賴基於 RAG 的架構。我們將這些稱為三級系統。

Level three systems will support more complex use cases and enable sensitive information to be processed in private clouds or on premises rather than being served up as context to third-party foundation models. We intend Innodata to offer enterprise all of the services they require to navigate the journey from level-zero to level three and beyond. This will include custom development, integration, and fine-tuning services, as well as managed services around data readiness and data governance and industry-specific workflow platforms. We are not alone in our thinking that the enterprise market for generative AI is about to explode.

三級系統將支援更複雜的用例，並使敏感資訊能夠在私有雲或本地進行處理，而不是作為第三方基礎模型的上下文。我們希望 Innodata 為企業提供從零級到三級甚至更高級別的旅程所需的所有服務。這將包括客製化開發、整合和微調服務，以及圍繞資料準備和資料治理以及行業特定工作流程平台的託管服務。我們並不是唯一一個認為生成式人工智慧企業市場即將爆發的人。

In a report last year, Bloomberg estimated the market for generative AI focused IT services will grow to nearly $22 billion by 2027 and to nearly $86 billion by 2032, representing a 100% compounded annual growth rate for the 10-year period from 2022 to 2032. To position ourselves to drive enterprise growth, we are expanding our talent base, creating new accelerators, and winning new reference engagements.

彭博社在去年的一份報告中估計，到2027 年，以產生人工智慧為中心的IT 服務市場將成長到近220 億美元，到2032 年將成長到近860 億美元，即2022 年至2032 年10年間的複合年增長率為100% 。為了推動企業發展，我們正在擴大人才基礎，創造新的加速器，並贏得新的參考項目。

This quarter, one of the largest legal information companies in the world engaged us to develop a new LLM-based workflow system for their complex operational processes spanning legal and regulatory law in multiple European countries and multiple languages. This is an example of what I referred to a few minutes ago as an advanced level one system. Our implementation uses GPT and a combination of several techniques, including chain of density, prompt engineering, and a vector database with similarity matching. Our generative AI-enabled workflow system is expected to enable the customer to drive significant operational savings across high-cost processes that previously relied entirely on humans with language and legal expertise.

本季度，世界上最大的法律資訊公司之一聘請我們為其複雜的操作流程開發一個基於法學碩士的工作流程系統，涵蓋多個歐洲國家和多種語言的法律和監管法。這是我幾分鐘前提到的高階一級系統的一個例子。我們的實作使用 GPT 和多種技術的組合，包括密度鏈、提示工程和具有相似性匹配的向量資料庫。我們的生成式人工智慧工作流程系統預計將使客戶能夠在高成本流程中顯著節省營運成本，而這些流程以前完全依賴具有語言和法律專業知識的人類。

This quarter, we also delivered a generative AI powered tool that gathers on-the-fly insights from large-scale textual data, contextually analyzes the data for specific areas of interest, and performs language translations. The technology aims to increase organizations efficiency by ensuring knowledge workers are equipped with the intelligence needed to make informed decisions.

本季度，我們還推出了一款生成式人工智慧驅動的工具，該工具可以從大規模文字資料中收集即時見解，根據上下文分析特定感興趣領域的數據，並執行語言翻譯。該技術旨在透過確保知識工作者俱備做出明智決策所需的情報來提高組織效率。

We built it into our agility public relations platform where we call it Intelligent Insights. We made Intelligent Insights generally available to agility customers in the quarter, and it has been well received. To build the solution, we utilize RAG-based prompt engineering. We recently demonstrated it as an accelerator to one of our large banking customers and it inspired a POC that we are now executing.

我們將其建置到我們的敏捷公共關係平台中，我們稱之為「智慧洞察」。我們在本季向敏捷客戶普遍提供了智慧洞察，並且受到了好評。為了建構該解決方案，我們利用基於 RAG 的提示工程。我們最近向我們的一家大型銀行客戶展示了它作為加速器的作用，它啟發了我們現在正在執行的 POC。

Agility revenue in the quarter increased 16.5% year over year. We have over 1,400 direct customers, and we're generating cash. We've been a leader in the industry, rolling out cutting edge generative AI functionality that is bending the productivity curve for PR and communications professionals. We started early last year with the release of PR CoPilot, the generative AI implementation that helps people write press releases and media pitches.

該季度敏捷收入年增 16.5%。我們擁有超過 1,400 名直接客戶，並且正在產生現金。我們一直是業界的領導者，推出了尖端的生成人工智慧功能，正在改變公關和傳播專業人員的生產力曲線。我們從去年初開始發布 PR CoPilot，這是一種生成式人工智慧實現，可以幫助人們撰寫新聞稿和媒體宣傳。

In Q1, we announced the general availability of Intelligent Insights. We are planning another five significant generative AI feature releases over the course of the second half of this year and into the first quarter next year. As a result of what we believe is our generative AI leadership in the PR space, in the first quarter, we converted over 35% of demos to wins, up from less than 20% prior to implementation of our generative AI roadmap. Our customers told us that one of their biggest challenges was that they needed more hours in the day. With our generative AI innovations, we're making tactical PR a less labor intensive process, giving our customers the time back they need for strategic thinking.

在第一季度，我們宣布全面推出智慧洞察。我們計劃在今年下半年和明年第一季發布另外五個重要的生成式人工智慧功能。由於我們相信我們的生成式人工智慧在公關領域的領導地位，在第一季度，我們將超過35% 的演示轉化為成功，而在實施生成式人工智慧路線圖之前，這一比例還不到20 %。我們的客戶告訴我們，他們最大的挑戰之一是他們一天需要更多的時間。借助我們的生成式人工智慧創新，我們正在使戰術公關成為一個勞動力密集程度較低的過程，為我們的客戶提供進行策略思考所需的時間。

For both the Big Tech market as well as the enterprise market, we see additional opportunities in model safety evaluation and responsible and ethical AI. We began working on trust and safety for one of our Big Tech customers in Q4 2023, providing model assessment and benchmarking services, which help ensure that models meet performance, risk, and emerging regulatory requirements. We learned a lot from the work and development we've been doing on this engagement, so we decided to share our learnings, tools, and innovation with the market more broadly.

對於大型科技市場和企業市場，我們在模型安全評估以及負責任和道德的人工智慧方面看到了更多機會。我們於 2023 年第四季開始為我們的一位大型科技客戶提供信任和安全方面的工作，提供模型評估和基準測試服務，這有助於確保模型滿足效能、風險和新興監管要求。我們從這次合作中所做的工作和開發中學到了很多東西，因此我們決定更廣泛地與市場分享我們的經驗、工具和創新。

Just a couple of weeks ago, we announced our release of an open-source LLM evaluation toolkit, together with a repository of 14 semi-synthetic and human-crafted evaluation datasets that enterprises can utilize for evaluating the safety of their large language models in the context of enterprise tasks. Using the toolkit and the datasets, data scientists can automatically test the safety of underlying LLMs across multiple harm categories simultaneously. Developers can understand how their AI systems respond to a variety of prompts and can identify remedial fine-tuning required to align the systems to the desired outcomes. We expect to release a commercial version of the toolkit and more extensive continually updated benchmarking datasets later this year.

就在幾週前，我們宣布發布開源 LLM 評估工具包，以及包含 14 個半合成和人工製作的評估資料集的儲存庫，企業可以利用這些資料集來評估大型語言模型的安全性。背景。使用該工具包和資料集，資料科學家可以同時自動測試跨多個危害類別的基礎法學碩士的安全性。開發人員可以了解他們的人工智慧系統如何回應各種提示，並可以確定使系統達到預期結果所需的補救微調。我們預計將在今年稍後發布該工具包的商業版本以及更廣泛的持續更新的基準測試資料集。

In Q1, we won two additional engagements for LLM safety and evaluation; one for a hyperscaler's own foundation models and one for an enterprise customer of the hyperscaler through the white label program we have in place with the hyperscaler. In addition, in Q1 2024, we started pilots for a new customer and an existing customer around LLM trust and safety.

在第一季度，我們贏得了兩個額外的法學碩士安全和評估課程；一種用於超大規模企業自己的基礎模型，另一種針對超大規模企業客戶，透過我們與超大規模企業一起實施的白標計畫。此外，在 2024 年第一季度，我們圍繞法學碩士信任和安全為新客戶和現有客戶啟動了試點。

I'll conclude with this. We believe we have an incredible opportunity in front of us. We believe we have the talent, capabilities, and scalability to support the world's leading company's efforts to build AI models and services and to help enterprises advanced AI and generative AI technologies. We believe we can drive best-in-class growth over the next several years and maintain our early leadership position in generative AI services.

我將以此結束。我們相信我們面前有一個難以置信的機會。我們相信我們擁有人才、能力和可擴展性來支持世界領先公司建立人工智慧模型和服務的努力，並幫助企業先進的人工智慧和生成式人工智慧技術。我們相信，我們能夠在未來幾年推動一流的成長，並保持我們在生成人工智慧服務領域的早期領導地位。

Moreover, we believe we can accomplish this without the need to raise equity, to incur debt, or to burn cash. This year, based on our current growth forecast, we intend to invest approximately $3.5 million in recruiting costs to scale our business and approximately another $3 million in new sales, marketing, and product development talent. The recruiting costs relate to the significant increase in revenues we expect this year and will not be incurred next year to support that revenue going forward. The investment in sales, marketing and product development are encouraged to continue our growth momentum and we anticipate that they will yield revenue and profitability benefits primarily next year and beyond.

此外，我們相信我們可以實現這一目標，而無需籌集股本、負債或燒錢。今年，根據我們目前的成長預測，我們打算投資約 350 萬美元的招募成本來擴大我們的業務，並另外投資約 300 萬美元的新銷售、行銷和產品開發人才。招聘成本與我們預計今年收入的大幅增長有關，明年不會產生招聘成本來支持未來的收入。我們鼓勵對銷售、行銷和產品開發的投資，以繼續我們的成長勢頭，我們預計它們將主要在明年及以後產生收入和盈利能力。

We anticipate approximately 70% of the recurring -- of the recruiting costs to be incurred in Q2 and most of the OpEx investment to be incurred in the second half of the year. We are making these investments while simultaneously driving year-over-year growth in adjusted EBITDA and building cash on our balance sheet. At the end of Q1, our cash balances were $19 million, up from $13.8 million at the end of Q4 2023, driven by positive cash flow from operations and tight working capital management.

我們預計約 70% 的經常性招募成本將在第二季產生，大部分營運支出投資將在今年下半年產生。我們進行這些投資的同時，推動調整後 EBITDA 的年成長，並在資產負債表上累積現金。截至第一季末，我們的現金餘額為 1,900 萬美元，高於 2023 年第四季末的 1,380 萬美元，這得益於營運產生的正現金流和嚴格的營運資本管理。

I'll now turn the call over to Marissa to go over the numbers, and then we'll open the line for some questions.

我現在將把電話轉給瑪麗莎，讓她核對數字，然後我們將開通電話詢問一些問題。

Thank you, Jack, and good afternoon everyone. Let me briefly share with you our 2024 first-quarter financial results. Revenue was $26.5 million, up 41% from $18.8 million in the same period last year. Net income was $1 million, or $0.03 per basic and diluted share, compared to a net loss of $2.1 million, or $0.08 per basic and diluted share in the same period last year.

謝謝你，傑克，大家下午好。我先簡單跟大家分享一下我們2024年第一季的財務表現。營收為 2,650 萬美元，比去年同期的 1,880 萬美元成長 41%。淨利潤為 100 萬美元，即每股基本股和稀釋股 0.03 美元，而去年同期淨虧損為 210 萬美元，即每股基本股和稀釋股 0.08 美元。

The adjusted EBITDA was $3.8 million compared to adjusted EBITDA of $0.8 million in the same period last year. Our cash and cash equivalent and short-term investments were $19 million at March 31, 2024, and $13.8 million at December 31, 2023. We currently have unused line of credit of $10 million with $9.2 million as borrowing days.

調整後 EBITDA 為 380 萬美元，去年同期調整後 EBITDA 為 80 萬美元。截至2024年3月31日，我們的現金及現金等價物以及短期投資為1,900萬美元，截至2023年12月31日為1,380萬美元。我們目前有 1000 萬美元未使用的信用額度，其中藉款天數為 920 萬美元。

So thank you everyone. Paul, we're ready for questions.

所以謝謝大家。保羅，我們準備好提問了。

(Operator instructions) [Aria Cole], Cole Capital.

（操作員說明）【Aria Cole】，科爾資本。

Yes, thank you. Again, congratulations on the good sales results and the good feedback you're getting from customers who are asking, giving you additional business. Jack, one quick question. Clearly, companies can grow organically. They can also grow through acquisition. I was trying to get an update on your thought process or how important acquisitions could be as a part of your growth going forward?

是的，謝謝。再次恭喜您取得了良好的銷售業績，並從提出要求的客戶那裡得到了良好的回饋，為您帶來了額外的業務。傑克，問一個簡單的問題。顯然，公司可以有機成長。他們還可以透過收購來成長。我試圖了解您的思考過程的最新情況，或者收購作為您未來發展的一部分有多重要？

Aria, thank you for the question. So the business plan that we're currently executing successfully is an organic-only plan. We've got a strategy in place that we think we can successfully deliver through organic growth and through the resources that are available to us and that we're able to augment our team with. From time to time, we will kick the tires on potential inorganic opportunities. But I think the important thing is that we're not dependent upon that for growth. We recognize that those come with risks that are not necessarily risks that one incurs with a -- or get primarily organic strategy. And that's the way we're executing right now.

阿麗亞，謝謝你的提問。因此，我們目前成功執行的業務計劃是一個純有機計劃。我們已經制定了一項策略，我們認為我們可以透過有機成長和我們可用的資源以及我們能夠用來增強團隊的資源來成功實現這一戰略。有時，我們會嘗試潛在的無機機會。但我認為重要的是我們的成長並不依賴於此。我們體認到，這些帶來的風險不一定是採用有機策略所帶來的風險，或主要是有機策略所帶來的風險。這就是我們現在正在執行的方式。

Understood. Then the follow-up is looking at organic growth. When you look at the financial employees, what sort of sales per employee can you generate when you're primarily providing services for these large technology companies? And what sort of -- what is the gross margin range you think you can achieve when people's time is being optimally utilized?

明白了。接下來就是關注有機成長。當你觀察財務員工時，當你主要為這些大型科技公司提供服務時，每位員工能產生多少銷售？當人們的時間得到最佳利用時，您認為可以達到什麼樣的毛利率範圍？

Sure. So we target -- at a consolidated level, we target about 40% adjusted gross margin. When you back out the one-time recruiting charges that relate to the revenue that we're scaling up for, and if you back out sales and marketing investments that we plan to have, to be returning on that investment in the following year, from a revenue per employee, we don't track that although it is notable, and it's not lost on us but, our revenue employee has gone or with the large language model work that we're doing is probably four to, even five times in excess of what it's been historically with the business process management services.

當然。因此，我們的目標是——在綜合水平上，我們的目標是調整後毛利率約為 40%。當您取消與我們擴大收入相關的一次性招聘費用，並且如果您取消我們計劃在下一年收回該投資的銷售和營銷投資，每個員工的收入，我們沒有跟踪，雖然它是值得注意的，而且我們並沒有失去它，但是，我們的收入員工已經走了，或者我們正在做的大型語言模型工作可能是四到五倍超出了業務流程管理服務的歷史水平。

Got it. And just finally, in terms of employee retention, you're going to be in a more competitive marketplace for employees in the future. And I'm just wondering what you're putting in place to try and make Innodata a place that people really enjoy working at, where your churn hopefully, our turnover employees will be kept to a minimal level?

知道了。最後，就員工留任率而言，未來員工將處於更具競爭力的市場。我只是想知道你們正在採取哪些措施來嘗試讓 Innodata 成為一個人們真正喜歡工作的地方，希望你們的員工流失率能夠保持在最低水平？

So for the most part, over the years, churn has not presented a problem for us that we weren't able to manage. We were able to keep it at a level that was way below that of most of our competitors. Just this past quarter, we were elected as one of the best places to work by, in two different of our locations. So we believe that we will be able to manage it. And we're very excited about the -- obviously, very excited about the growth opportunity in front of us.

因此，多年來，在大多數情況下，客戶流失並沒有為我們帶來我們無法管理的問題。我們能夠將其保持在遠低於大多數競爭對手的水平。就在上個季度，我們在兩個不同的地點被選為最佳工作場所之一。所以我們相信我們能夠管理它。我們對擺在我們面前的成長機會感到非常興奮。

Okay, great. Well, thank you and best of luck.

好的，太好了。嗯，謝謝你，祝你好運。

Thank you.

謝謝。

Tim Clarkson, Van Clemens.

提姆克拉克森、範克萊門斯。

Hey, Jack. Obviously, a great quarter. Just want to go over some of the basics for some of us Luddites here. So when I originally realized that Innodata was getting involved in artificial intelligence. The one thing that was really helpful for me understanding why you guys are successful is just the accuracy, and the top guy from IBM explained it to me that at IBM, they had a 75% failure rate, largely because of inaccuracies. And what I'm hearing is you guys make, like, three mistakes and 20,000 annotations. Can you just talk about how that's, really, it seems simple, but it's a real foundational skill. You're doing more than that, obviously. But that really is what initially separates you from the competition in a big way.

嘿，傑克。顯然，這是一個很棒的季度。只是想為我們這裡的一些勒德分子回顧一些基礎知識。所以當我最初意識到Innodata正在涉足人工智慧領域時。對我理解你們成功的原因真正有幫助的一件事就是準確性，IBM 的高層向我解釋說，在 IBM，他們的失敗率為 75%，很大程度上是因為不準確。我聽到的是你們犯了三個錯誤和 20,000 個註釋。您能否簡單談談這看起來很簡單，但卻是一項真正的基礎技能。顯然，你所做的遠不止這些。但這確實是您最初在競爭中最大的區別所在。

So Tim, thank you for the question. Absolutely. I think data quality has been proven to lead to great model performance. And we have customers that I mentioned a few minutes ago who, with their new releases, are attributing their incremental improvements to their data quality, and we're working for those customers. So we're thrilled that, we're producing those great outcomes for our customers, and we're seeing that those great outcomes are leading to expansions and growth.

提姆，謝謝你的提問。絕對地。我認為數據品質已被證明可以帶來出色的模型性能。我幾分鐘前提到的一些客戶將他們的新版本的增量改進歸因於他們的數據質量，我們正在為這些客戶工作。因此，我們很高興我們正在為客戶創造這些偉大的成果，並且我們看到這些偉大的成果正在帶來擴張和成長。

In terms of LLMs, there are three critical ingredients. There's compute, there's data science, and then there's data engineering work that we do. Given the investments that these companies are making and the kind of risk that they're taking and the strategic emphasis that they're placing on these developments, it's critical to them to have the kind of data that will result in the models that they -- and the accuracy of the models that they're building. So we think we're very well-positioned. We're doing great work, and we think the future is very bright.

就法學碩士而言，有三個關鍵要素。有計算，有數據科學，然後還有我們所做的數據工程工作。考慮到這些公司正在進行的投資、他們所承擔的風險以及他們對這些發展的戰略重點，對他們來說擁有能夠產生模型的數據至關重要： - 以及他們正在建立的模型的準確性。所以我們認為我們處於非常有利的位置。我們正在做出色的工作，我們認為未來非常光明。

Right. Now, just as kind of an extension to that idea. I mean, one of the challenges, obviously, what Innodata historically was do a project and then it ended, and there wasn't a durability of revenues. Can you comment on how durable you think this new business model is going to be into the future?

正確的。現在，就像這個想法的延伸。我的意思是，顯然，挑戰之一是 Innodata 過去做過一個項目，然後項目就結束了，收入沒有持久性。您能否評論一下您認為這種新的商業模式在未來的持久性如何？

So I think it's extremely early days still. We see lots of developments that are taking place. I mentioned several of those. We believe that we're still in the early innings of executing all of these opportunities. We're starting to now talk to our customers about multimodal models, about multiple languages, more complex reasoning tasks that they want the models to be able to take on, domain and task specificity. All of these things are early for them, and we think we're early in our partnerships with them such that we're going to be able to drive multiyear growth as a result of their multiyear investments. At the same time, we're landing more companies and we're getting into the enterprise opportunity. So we think there's a tremendous amount of growth opportunity in front of us.

所以我認為現在還為時過早。我們看到許多正在發生的進展。我提到了其中幾個。我們相信，我們仍處於執行所有這些機會的早期階段。我們現在開始與客戶討論多模式模型、多種語言、他們希望模型能夠承擔的更複雜的推理任務、領域和任務特異性。所有這些事情對他們來說都還為時過早，我們認為我們與他們的合作還處於早期階段，因此我們將能夠透過他們的多年投資來推動多年成長。同時，我們正在吸引更多的公司，我們正在抓住企業機會。因此，我們認為我們面前有巨大的成長機會。

Right. Now historically, back in the, I don't know if you call it the good old days, but the old days when you guys were picking on projects, you're doing $20 million, I remember netting 15%, 20% after tax, and it seems like you got these one-time expenses with sales investments, but separating those out, it seems like there's certainly a potential to have 15% to 20% pretax margins once you guys get onto a solid run rate.

正確的。現在，從歷史上看，回到過去，我不知道你是否稱其為過去的美好時光，但過去你們在挑選項目時，你做了2000萬美元，我記得稅後淨賺15%、20% ，似乎你透過銷售投資獲得了這些一次性費用，但將它們分開，一旦你們獲得穩定的運行率，似乎肯定有可能獲得15% 到20% 的稅前利潤。

So yeah. I think that's, certainly, what we're pursuing. We think the opportunity is there. We also think it's important, as I mentioned, to be investing in our growth. We believe that we have an opportunity in front of us to create a truly great company, and we're very excited about that.

所以是的。我認為這當然是我們所追求的目標。我們認為機會就在那裡。正如我所提到的，我們也認為投資我們的成長也很重要。我們相信我們有機會創造一家真正偉大的公司，我們對此感到非常興奮。

Now, these investments would be directly tied into AI then right, on that part of the business?

現在，這些投資將直接與人工智慧掛鉤，對吧，在這部分業務上？

Exactly right.

完全正確。

Right, great. Well, good luck. It's an exciting future. Thank you.

對了，太好了。好吧，祝你好運。這是一個令人興奮的未來。謝謝。

Thank you, Tim.

謝謝你，提姆。

Dana Buska, Feltl,

達納布斯卡、費爾特爾、

Hi, Jack.

嗨，傑克。

Hey, Dana.

嘿，達納。

Congratulations on a wonderful quarter. I have just a couple of questions for you. You talked a little bit about the demand for training on enterprise data. Can you talk a little bit more about that? And are you seeing more enterprises look to train their own models?

恭喜您度過了一個美好的季度。我只有幾個問題想問你。您談到了企業資料培訓的需求。能多談談嗎？您是否看到越來越多的企業希望訓練自己的模型？

I think we're going to see more enterprises training their own models when the cost of doing so comes down, which we believe is inevitable for the most part. What enterprises are looking to do now is to use their own data as context within RAG implementations. And even with that, we see a lot of opportunities that are now being piloted, and POCs, very early days in terms of getting things into development -- or past development and into implementation. We think we're going to be there in order to help accomplish that. Again, quality of data that feeds those models and the kinds of integrations that become possible, especially with large context, Windows is going to improve the results of those models and what can be achieved with them. We're very well-positioned to help enterprises move things from POCs into development, and we're doing that now today.

我認為，當成本下降時，我們將看到更多的企業訓練自己的模型，我們認為這在很大程度上是不可避免的。企業現在希望做的是使用自己的資料作為 RAG 實施中的上下文。即便如此，我們還是看到了許多正在試點的機會，以及 POC，在將事物投入開發（或過去的開發和實施）方面處於早期階段。我們認為我們將在那裡幫助實現這一目標。同樣，由於為這些模型提供資料的品質以及可能實現的整合類型（尤其是在大型上下文中），Windows 將改進這些模型的結果以及利用它們可以實現的目標。我們處於非常有利的位置，可以幫助企業將概念從概念驗證轉變為開發，而我們今天正在這樣做。

Okay, great. And along those lines, I seem to read, come across articles of how companies are coming up with it tools and software to speed up fine-tuning and doing trust and safety. Can you talk a little bit about how that may affect your business and do you consider that to be a threat?

好的，太好了。沿著這些思路，我似乎讀到了一些文章，介紹公司如何開發 IT 工具和軟體來加速微調並實現信任和安全。您能談談這對您的業務有何影響嗎？

No. We consider that to be an opportunity. The more success we have and the world has moving things from POC into development, the more acceleration we will see in the technology and the opportunities that we have. We are among the companies who is developing capabilities around trust and safety. We're very excited about that. Again, it's a data-driven initiative and a data-driven approach that we're taking that we believe will help companies along in that path.

不。我們認為這是一個機會。我們取得的成功越多，世界將事物從概念驗證轉向開發，我們就會看到技術和機會的加速發展就越快。我們是圍繞信任和安全開發能力的公司之一。我們對此感到非常興奮。同樣，我們正在採取的數據驅動舉措和數據驅動方法，我們相信這將幫助公司沿著這條道路前進。

Okay, excellent. That sounds excited. When you're looking at hiring these new recurring cost, could you talk a little bit about hiring the new people? Could you talk a little bit about what type of positions you're looking to hire?

好的，非常好。聽起來很興奮。當您考慮僱用這些新的經常性成本時，您能談談僱用新員工嗎？您能談談您想要招募什麼類型的職位嗎？

So we're hiring very broadly. We're hiring people who have the ability to help us build the kinds of data sets that we require to train these models. A lot of the people that we're hiring are language experts or they're domain experts, they're linguists, they're people with backgrounds that enable them to appreciate nuance and language. As we think about these models, it's language that is used to program them. And the more fine-tuning we can do around the nuance of those language, the better performing the models are.

所以我們的招募範圍非常廣泛。我們正在招募有能力幫助我們建立訓練這些模型所需的資料集的人員。我們僱用的許多人都是語言專家，或者他們是領域專家，他們是語言學家，他們的背景使他們能夠欣賞細微差別和語言。當我們思考這些模型時，它是用於對它們進行程式設計的語言。我們圍繞這些語言的細微差別進行的微調越多，模型的效能就越好。

Okay, great. And then one question about agility. It looked like it grew about 20% last quarter. Is that a growth rate that you are targeting for this year? Is that growth rate that you think is sustainable?

好的，太好了。然後是一個關於敏捷性的問題。看起來上個季度成長了約 20%。這是您今年的目標成長率嗎？您認為這個成長率是可持續的嗎？

So I think it was about 15%, if I'm not mistaken --

如果我沒記錯的話，我認為大約是 15%--

Dana, it was 17%.

達納，是 17%。

17%, yes. So I think, 15% to 20% is certainly what we would aspire to. We could do a lot more with more reinvestment in it, and that's something that we would probably be considering at some point. But right now, we're very focused on capital allocation relative to the surface opportunities we have with large tech companies.

17%，是的。所以我認為，15%到20%肯定是我們所渴望的。透過更多的再投資，我們可以做更多的事情，這也是我們在某個時候可能會考慮的事情。但目前，我們非常關注與大型科技公司的表面機會相關的資本配置。

Okay, excellent. That sounds very exciting. Thank you for taking my questions.

好的，非常好。聽起來非常令人興奮。感謝您回答我的問題。

Thank you.

謝謝。

Bruce Galloway, Galloway Capital.

布魯斯·加洛韋，加洛韋資本。

Hey, Jack, congratulations. It seems like you're gaining a lot of traction. Just to quantify the size of these contracts and some of the new additions, you mentioned the $23.5 million add-on to the $20 million hyperscaler that you announced in April. I guess that was the one that was doing $23 million a year that extended it for three years. So that alone is a $43.5 million add-on from the $23 million, which on a base of $86 million last year, that's over 50% growth rate just from one customer. Can you give us some quantification on some of these other contracts, how big they could be, and how much they can scale to?

嘿，傑克，恭喜你。看來你獲得了很大的吸引力。為了量化這些合約和一些新增合約的規模，您提到了您在 4 月宣布的價值 2000 萬美元的超大規模合約中附加了 2350 萬美元。我猜那家公司每年投入 2,300 萬美元，並將其延長了三年。因此，光是這一項就比 2,300 萬美元增加了 4,350 萬美元，在去年 8,600 萬美元的基礎上，光是一個客戶的成長率就超過 50%。您能否給我們一些其他合約的量化數據，它們可能有多大，以及它們可以擴展到多少？

Sure. So as I mentioned, we're now working with seven Big Tech companies. And we believe when we look across that portfolio, that they are all spending significantly, as significantly as the company that you referred to on these technologies. And we believe we have an opportunity to scale with all of them.

當然。正如我所提到的，我們現在正在與七家大型科技公司合作。我們相信，當我們審視該投資組合時，他們都在這些技術上投入了大量資金，就像您提到的公司一樣。我們相信我們有機會與他們一起擴展。

Now, will all of them become as big as this one? That would be wonderful if it were to happen. I don't know that it will. But we believe we're certainly very well-positioned. We brought in another two customers this quarter, which are very significant players and appear to be very eager to work with us.

現在，它們都會變得跟這個一樣大嗎？如果這真的發生那就太好了。我不知道會這樣。但我們相信我們確實處於有利地位。本季我們又引進了兩家客戶，他們都是非常重要的參與者，似乎非常渴望與我們合作。

And in terms of when you start adding up the numbers and adding up what's possible, we believe that the 40% growth target, which doubles what we provided last quarter, is still a reasonably conservative target. We have lots of opportunity in flight. We're taking conservative view of our pipeline in order to support our growth guidance, and it's a very exciting time in our business right now.

就當你開始累積數字和累加可能性而言，我們認為 40% 的成長目標（是我們上季提供的兩倍）仍然是一個相當保守的目標。我們在飛行中有很多機會。我們對我們的管道採取保守的看法，以支持我們的成長指導，現在是我們業務的一個非常令人興奮的時刻。

So looking at your current infrastructure, your personnel, and your installed base, I mean, do you have the capability, adding $3 million in personnel and $3 million in CapEx seems very modest amount for the scalability and the upside that you have with all these huge contracts coming through?

因此，看看您目前的基礎設施、人員和安裝基礎，我的意思是，您是否有能力增加300 萬美元的人員​​和300 萬美元的資本支出，對於可擴展性和您擁有的所有這些優勢來說，這似乎是非常有限的。

So the investments that I spoke about were investments in the recruiting costs associated with adding the headcount that is required for the near-term contracts to get to that 40% growth. And other investments that we're making in sales, marketing, and product development, I'm not including in those numbers, the costs that we would be incurring to as cost of goods. But again, from a cost of goods perspective, I think you should look at it as an opportunity to drive growth in the services area, probably about 37% adjusted gross margin, and that would subsume the costs of it of producing the revenue.

因此，我所說的投資是與增加近期合約所需的員工人數以實現 40% 的成長相關的招聘成本投資。我們在銷售、行銷和產品開發方面進行的其他投資，我沒有包括在這些數字中，也就是我們將產生的商品成本成本。但同樣，從商品成本的角度來看，我認為你應該將其視為推動服務領域成長的機會，調整後的毛利率可能約為 37％，而這將包含產生收入的成本。

Okay. And also, as far as the cash generation, you generated like $5.2 million in cash, is that mostly from receivables? Or is it pure cash from operations or combination thereof?

好的。另外，就現金產生而言，你們產生了大約 520 萬美元的現金，這大部分來自應收帳款嗎？還是來自營運的純現金或其組合？

Yeah. I mean, it's cash from operations that include receivables. So as we build, we then collect.

是的。我的意思是，這是來自包括應收帳款在內的業務的現金。因此，當我們建造時，我們就會收集。

Okay, great. Thanks. Excellent job. Thanks.

好的，太好了。謝謝。幹得好。謝謝。

Thank you.

謝謝。

Thank you. And that does conclude today's Q&A session. I will now hand the call back to Jack Abuhoff for closing remarks.

謝謝。今天的問答環節到此結束。現在，我將把電話轉回給傑克·阿布霍夫（Jack Abuhoff），讓他發表結束語。

Thank you. So yeah, we're off to an exciting start for 2024. And my team and I are tremendously energized by what we believe we will accomplish in 2024. We grew revenue by 41% year over year in Q1. We anticipate a substantial sequential revenue increase next quarter. And for 2024 overall, we have raised our guidance from 20% to at least 40% year-over-year expected organic-only revenue growth.

謝謝。是的，2024 年我們將迎來一個令人興奮的開端。我和我的團隊對 2024 年將實現的目標感到無比振奮。第一季我們的營收年增 41%。我們預計下個季度營收將大幅成長。就 2024 年整體而言，我們將預期純有機收入年增率從 20% 提高到至少 40%。

Today, we announced yet another substantial customer win this one, worth approximately $23.5 million of annualized revenue. This is on top of the win with the same customer we announced couple of weeks ago valued at approximately $20 million of annualized revenue.

今天，我們宣布又一位重要客戶贏得了這項獎項，年收入約為 2,350 萬美元。這是我們幾週前宣布贏得的同一客戶的年度收入約為 2000 萬美元的勝利。

We also announced the signing of two additional Big Tech customers, both of which we believe will contribute to 2024 revenue growth longer term, in addition to expected, or continued expected growth from our Big Tech customer base. We expect increased market demand from enterprise customers that we hope will continue to accelerate our growth trajectory. We're super excited about the work that's underway. We are laser focused on creating long-term shareholder value.

我們也宣布簽約另外兩家大型科技客戶，我們相信，除了我們大型科技客戶群的預期或持續預期成長之外，這兩位客戶都將為 2024 年的長期收入成長做出貢獻。我們預期企業客戶的市場需求將會增加，我們希望這將繼續加速我們的成長軌跡。我們對正在進行的工作感到非常興奮。我們專注於創造長期股東價值。

And thank you all for attending today's call. We'll be looking forward to our next call.

感謝大家參加今天的電話會議。我們將期待下次通話。

Thank you. This does conclude today's conference. You may disconnect your lines at this time. Thank you for your participation.

謝謝。今天的會議到此結束。此時您可以斷開線路。感謝您的參與。