Innodata Inc (INOD) 2024 Q4 法說會逐字稿

Good afternoon, ladies and gentlemen, and welcome to the Innodata to report fourth quarter and fiscal year 2024 results conference call. (Operator Instructions)

女士們、先生們，下午好，歡迎參加Innodata報告2024年第四季及2024財年業績電話會議。（操作員指令）

This call is being recorded on Thursday, February 20, 2025.

該通話於 2025 年 2 月 20 日星期四錄製。

I would now like to turn the conference over to Amy Agress, General Counsel at Innodata, Inc. Please go ahead.

現在，我想將會議交給 Innodata, Inc. 的總法律顧問 Amy Agress。請繼續。

Thank you, Inay. 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 fourth quarter and fiscal year 2024. We'll then take questions from analysts.

謝謝你，Inay。大家下午好。感謝您今天加入我們。今天的演講者是 Innodata 執行長 Jack Abuhoff 和臨時財務長 Marissa Espineli。參加今天電話會議的還有財務和企業發展資深副總裁 Aneesh Pendharkar。我們首先聽取傑克的發言，他將提供有關業務的觀點，然後瑪麗莎將回顧我們 2024 年第四季和財年的業績。然後我們將回答分析師的問題。

Before I 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.

在我開始之前，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、預期或其他陳述。這些聲明是基於目前的預期、假設和估計，並受風險和不確定性的影響。

Actual results could differ materially from those contemplated by these forward-looking statements. 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.

實際結果可能與這些前瞻性陳述所預期的結果有重大差異。可能導致這些結果出現重大差異的因素已在今天的收益新聞稿、我們的 10-K 表、10-Q 表以及向美國證券交易委員會提交的其他報告和文件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 reconciliations of those measures with comparable GAAP measures. Thank you.

此外，在本次電話會議中，我們可能會討論某些非公認會計準則財務指標。在我們網站上發布的美國證券交易委員會 (SEC) 文件中，您可以找到有關這些非 GAAP 財務指標的更多揭露，包括這些指標與可比較 GAAP 指標的對帳。謝謝。

I will now turn the call over to Jack.

現在我將電話轉給傑克。

Thank you, Amy, and hello, everyone. Our Q4 '24 revenue totaled $59.2 million, a year-over-year increase of 127% for the quarter. This exceeded our projected Q4 revenue guidance of $52 million to $55 million for Q4 '24. And our adjusted EBITDA for the quarter was $14.1 million, or 23.9% of revenue, a 231% year-over-year increase.

謝謝你，艾米，大家好。我們的 24 年第四季營收總計 5,920 萬美元，年增 127%。這超過了我們預計的24年第四季5200萬至5500萬美元的收入預期。本季調整後的 EBITDA 為 1,410 萬美元，佔營收的 23.9%，較去年同期成長 231%。

For the full year 2024, we delivered $170.5 million of revenue, up 96% over 2023. And our full year adjusted EBITDA was $34.6 million, or 20.3% of revenue, a 250% year-over-year increase. We finished the year with $46.9 million of cash, up from $13.8 million of cash at the end of 2023. Our $30 million credit facility remains undrawn. We are very pleased with these results.

2024 年全年，我們營收 1.705 億美元，比 2023 年成長 96%。我們全年調整後的 EBITDA 為 3,460 萬美元，佔營收的 20.3%，較去年同期成長 250%。我們今年的現金餘額為 4,690 萬美元，高於 2023 年底的 1,380 萬美元。我們的3000萬美元信貸額度仍未動用。我們對這些結果非常滿意。

In the fourth quarter, we experienced accelerating business momentum across key strategic imperatives that we believe will serve our medium and long-term growth plans. The momentum we're achieving gives us confidence to forecast 2025 as another year of strong growth.

第四季度，我們在關鍵策略要務方面的業務發展勢頭不斷加速，我們相信這將有助於我們的中長期成長計畫。我們所取得的勢頭使我們有信心預測 2025 年將是另一個強勁成長的一年。

In terms of guidance, in 2025, we will be taking the same approach we took in 2024. We'll start the year with an initial growth forecast based primarily on one and near-in forecastable business. And in succeeding quarters, if we win new business, we'll update the guidance.

在指導方面，到 2025 年，我們將採取與 2024 年相同的方法。我們將以初步的成長預測來開始新的一年，該預測主要基於一項及近期可預測的業務。在接下來的幾個季度裡，如果我們贏得新業務，我們將更新指引。

Last year at this time, we forecasted 20% growth for 2024. But then we revised this initial guidance upward multiple times through the course of the year as we won more business, ultimately delivering 96% revenue growth. We are now forecasting 40% or more revenue growth for 2025, and we will update this initial guidance through the course of the year.

去年此時，我們預測 2024 年的成長率為 20%。但隨著我們贏得更多業務，我們在一年中多次上調這一初步預期，最終實現了 96% 的收入成長。我們目前預測 2025 年的營收將成長 40% 或更多，並且我們將在今年內更新這項初步指引。

Our strong business momentum is reflected in revenue growth, margin expansion, broadening customer relationships, and continued progress on our strategic roadmap. We are laser-focused on providing big tech companies with the data engineering they require to develop generative AI frontier models. We believe our efforts are paying off.

我們強勁的業務動能體現在營收成長、利潤率擴大、客戶關係擴大以及策略路線圖的持續進展。我們專注於為大型科技公司提供開發生成式 AI 前沿模型所需的資料工程。我們相信我們的努力將會獲得回報。

In Q4 in January, we were awarded additional programs and expansions with our largest customer, valued at approximately $24 million of annualized run rate revenue. These newest awards expand our total annualized run rate revenue with this customer to approximately $135 million.

今年 1 月第四季度，我們獲得了最大客戶的額外項目和擴展合同，價值約為 2400 萬美元的年化運行收入。這些最新的合約使我們與該客戶之間的年度總運行收入擴大至約 1.35 億美元。

With our other big tech customers, we're also seeing accelerated demand for our services. Sequentially, from Q3 2024 to Q4 2024, our revenues from our largest big tech customer grew by 8%, while our aggregate revenues from our other seven big tech customers grew by 159%.

對於我們其他大型科技客戶來說，我們也看到對我們服務的需求正在加速成長。從 2024 年第三季到 2024 年第四季度，我們從最大的大型科技客戶獲得的收入成長了 8%，而我們從其他七家大型科技客戶獲得的總收入成長了 159%。

This increased growth by our other big tech customers, which we hope will continue in 2025, serves as validation of our land and expand strategy, and we expect it will continue to diversify our revenue base. Our confidence that these seven other big tech customers will collectively become a significant part of our revenue makeup in 2025 is bolstered by the progress we made in Q4 in building relationships, expanding work, securing new wins, gaining traction, and earning trust.

我們希望其他大型科技客戶的這種成長態勢能夠在 2025 年繼續保持，這證明了我們土地和擴張策略的有效性，並且我們預計它將繼續實現我們的收入基礎多元化。我們相信，到 2025 年，這七家大型科技客戶將成為我們收入的重要組成部分，而我們在第四季度在建立關係、擴大工作、獲得新勝利、獲得關注和贏得信任方面所取得的進展增強了我們的信心。

The number of projects and pilots we have underway with these customers significantly increased in Q4. This includes several pilots running now, which hold the promise, potentially, of seven- or even eight-figure wins.

我們與這些客戶合作的專案和試點數量在第四季度顯著增加。其中包括幾名目前正在參賽的飛行員，預計他們將獲得七位數甚至八位數的獎金。

As we discussed last quarter, our strategy encompasses both services and platforms. On the services side, we intend to be a go-to partner for big techs that are building generative AI frontier models and enterprises that seek to transform their products and operations with generative AI technologies. We believe these are lucrative markets which we are well-suited to serve.

正如我們上個季度所討論的，我們的策略涵蓋服務和平台。在服務方面，我們打算成為正在建立生成式人工智慧前沿模型的大型科技公司以及尋求利用生成式人工智慧技術轉變其產品和營運的企業的首選合作夥伴。我們相信，這些都是利潤豐厚的市場，我們非常適合服務。

The first focus area is big tech, and we believe we are positioned to benefit from big tech's aggressive planned investments in generative AI. Following recent earning reports from the Magnificent Seven, it is estimated that Amazon, Meta, Microsoft, and Google Paradox will spend a cumulative $325 billion in CapEx and investments in 2025, driven by continued commitment to building out their artificial intelligence offerings.

第一個重點領域是大型科技公司，我們相信，我們將從大型科技公司對生成式人工智慧的積極計畫投資中受益。根據七巨頭最近發布的收益報告，據估計，亞馬遜、Meta、微軟和 Google Paradox 將在 2025 年累計花費 3,250 億美元的資本支出和投資，以持續致力於打造人工智慧產品。

Amazon expects CapEx to be over $100 billion, up from $83 billion in 2024, with its CEO reiterating his previous views that AI is a, quote, once-in-a-lifetime type of business opportunity. Meta expects its 2025 CapEx to be between $60 billion and $65 billion, which, even at the bottom end of this guidance, is over 50% higher than its 2024 CapEx of $39.2 billion. Its CEO has termed 2025 as the, quote, fining year for AI.

亞馬遜預計資本支出將超過 1000 億美元，高於 2024 年的 830 億美元，其執行長重申了他先前的觀點，即人工智慧是一種千載難逢的商業機會。Meta 預計其 2025 年資本支出將在 600 億美元至 650 億美元之間，即使按照該指引的底端，也比其 2024 年的 392 億美元資本支出高出 50% 以上。其執行長將 2025 年稱為人工智慧的輝煌之年。

Microsoft, meanwhile, expects to spend $80 billion in its fiscal 2025, which will end in June. And Alphabet has forecast 2025 CapEx of $75 billion, which is almost 50% higher than its 2024 CapEx of $52.5 billion. In recent earnings, press releases have reinforced the commitment by these large tech companies to accelerate their AI investments with the goal of approaching AGI, artificial general intelligence.

同時，微軟預計將在 6 月結束的 2025 財年中支出 800 億美元。Alphabet 預測 2025 年的資本支出將達到 750 億美元，比 2024 年的 525 億美元資本支出高出近 50%。在最近的收益報告中，新聞稿強化了這些大型科技公司加速人工智慧投資的承諾，目標是接近AGI，即通用人工智慧。

We believe that the long road to AGI will be paved with data, multilingual and multimodal data, data for safety and alignment, meta learning and reasoning data, computer use, agentic and operator data, industry-specific data, and data for real-world modeling and simulation.

我們相信，通往 AGI 的漫長道路將由數據、多語言和多模態數據、安全和協調數據、元學習和推理數據、計算機使用、代理和操作員數據、行業特定數據以及用於現實世界建模和模擬的數據所鋪就。

Now, we know models perform better when supervised fine-tuning data is high-quality, large-scale, highly consistent, and diverse. An industry analogy to explain where we are in capturing data is to imagine the realm of all useful data to be the size of a football.

現在，我們知道，當監督微調資料高品質、大規模、高度一致且多樣化時，模型的表現會更好。一個產業類比可以解釋我們在捕捉數據方面所處的位置，那就是將所有有用數據的範圍想像為一個足球大小。

By comparison, today's best-performing LLMs have been trained with data sets that are probably the size of a dime. What's even more interesting is that much of this is uncaptured, but useful data does not even exist explicitly today, such as how to execute a multi-step process using a series of websites or how to reason through complex domain-specific problems. We believe this likely means an even greater need for investments in our services that will be necessary to achieve the goal of AGI.

相較之下，當今表現最好的法學碩士 (LLM) 都是用一角硬幣大小的資料集進行訓練的。更有趣的是，其中大部分尚未被捕獲，但有用的數據今天甚至還不存在明確的數據，例如如何使用一系列網站執行多步驟過程或如何推理複雜的特定領域問題。我們相信這可能意味著我們需要對我們的服務進行更大的投資，而這對於實現 AGI 的目標是必要的。

We intend for Innodata to be at the forefront of providing these services. Moreover, we believe that innovation in hardware optimization, such as that lower the costs of compute required to train tomorrow's LLMs on data, will enable big tech to accelerate their investments in data.

我們希望 Innodata 能成為提供這些服務的先鋒。此外，我們相信，硬體優化方面的創新，例如降低未來 LLM 資料訓練所需的運算成本，將使大型科技公司能夠加速對資料的投資。

We saw this kind of innovation recently from DeepSeek, the Chinese AI research lab. Their innovative use of several existing technologies, which enabled more data to be trained with less compute, are in fact part and parcel of the technology revolution previously popularized as Moore's Law for the semiconductor industry. We expect DeepSeek's hardware optimization techniques to be quickly absorbed by our largest customers, much like other recent hardware optimization techniques that received less fanfare and future hardware optimization techniques that are inevitable. We believe that there is no viable substitute for pre-training data and fine-tuning data to progress to AGI.

我們最近從中國人工智慧研究實驗室 DeepSeek 看到了這種創新。他們創新地使用了幾種現有技術，從而能夠用更少的計算來訓練更多的數據，這實際上是之前被稱為半導體行業摩爾定律的技術革命的重要組成部分。我們預計 DeepSeek 的硬體優化技術能夠被我們最大的客戶迅速吸收，就像其他近期不太受關注的硬體優化技術和不可避免的未來硬體優化技術一樣。我們相信，沒有什麼可以取代預訓練資料和微調資料來實現 AGI 的發展。

Techniques such as data distillation, using output of existing models to train new models, may result in high performance on benchmarks because benchmarks are inherently biased toward the past. But limiting data diversity in this way actually results in a more limited performance and ultimately causes what's referred to as model collapse.

資料提煉等技術，利用現有模型的輸出來訓練新模型，可能會在基準測試中取得較高的效能，因為基準測試本質上偏向過去。但以這種方式限制資料多樣性實際上會導致效能更加有限，並最終導致所謂的模型崩潰。

DeepSeek relied heavily on data distillation. That's why in the last few weeks we're seeing more and more of the limits of what their model can do. We're also seeing big tech companies putting in place the technologies to effectively shut the back door to future data distillation. In addition to supplying supervised fine-tuning data, we are increasingly identifying opportunities to source and transform pre-training data to solve the issues around IP infringement.

DeepSeek 嚴重依賴資料提煉。這就是為什麼在過去的幾周里我們越來越多地看到他們的模型的局限性。我們也看到大型科技公司正在採用這些技術，有效地關閉未來數據提煉的後門。除了提供監督微調資料外，我們還在不斷尋找機會取得和轉換預訓練資料來解決智慧財產權侵權問題。

One of the big tech companies that we signed in 2024 engaged us on pre-training data in Q4, which resulted in $3 million of Q4 revenue. We're also finding expanded opportunities with big tech companies in LLM safety and evaluation. Just last month we won two LLM trust and safety engagements with a big tech company that we valued approximately $3.6 million of annualized revenue run rate.

我們在 2024 年簽約的一家大型科技公司在第四季度與我們合作提供預訓練數據，並在第四季度帶來了 300 萬美元的收入。我們還發現，在法學碩士 (LLM) 安全和評估領域，與大型科技公司合作的機會越來越多。就在上個月，我們與一家大型科技公司贏得了兩項 LLM 信託與安全業務，我們對其年收入運行率的估值約為 360 萬美元。

Let's talk a bit about the enterprise market. The DeepSeek hardware optimization that we just spoke of, that makes both training and inferencing less expensive, will, we believe, significantly catalyze enterprise-gen AI adoption. This has recently been talked about as an example of the Jevons Paradox, the simple idea that when technological progress makes a resource cheaper or more efficient to use, it often leads to an increase in demand for that resource.

讓我們來談談企業市場。我們剛才提到的 DeepSeek 硬體優化可以降低訓練和推理的成本，我們相信這將大大促進企業級 AI 的採用。最近，人們將此作為傑文斯悖論的一個例子進行討論，該悖論的簡單思想是，當技術進步使某種資源變得更便宜或使用效率更高時，通常會導致對該資源的需求增加。

We believe we are on the precipice of a rapid acceleration in enterprise adoption of generative AI. This, we believe, will result from hardware optimization that lowers the cost of building gen AI solutions and managing gen AI infrastructure, as well as advancements in high-quality open-source models that can be fine-tuned as expert agents, innovations in orchestrating agentic AI ecosystems, and frontier models capable of performing deep research, utilizing both websites and tomorrow's agents.

我們相信，我們正處於企業採用生成式人工智慧的快速加速階段。我們相信，這將源於硬體優化，從而降低構建新一代人工智慧解決方案和管理新一代人工智慧基礎設施的成本，以及可作為專家代理進行微調的高品質開源模型的進步、協調代理人工智慧生態系統的創新，以及能夠利用網站和未來代理進行深入研究的前沿模型。

We're seeing that enterprise customers struggle with access to gen AI talent. We're building technical roadmaps to capture both operational enhancement and product innovation, and we’re building prototypes that move into development. And as their ecosystems become more densely populated with AI agents, we anticipate that they will struggle with issues around safety and trust as well.

我們發現企業客戶​​在取得新一代人工智慧人才方面面臨困難。我們正在建立技術路線圖以捕捉營運增強和產品創新，並且正在建立進入開發階段的原型。而且隨著它們的生態系統中人工智慧代理的密度越來越高，我們預期它們也將面臨安全和信任的難題。

We believe our enterprise gen AI focus presents opportunities for us to continue delivering strong revenue growth in 2026 and beyond. The strong relationships we have with leading information companies, financial services companies, and other businesses have been and are expected to be a right proving ground for enterprise AI solutions and services.

我們相信，我們對企業級人工智慧的關注為我們在 2026 年及以後繼續實現強勁的收入成長提供了機會。我們與領先的資訊公司、金融服務公司和其他企業建立的牢固關係已經成為並有望成為企業 AI 解決方案和服務的正確試驗場。

We believe we already have a line of sight to double-digit growth with a number of these customers in 2025, based on forecasted gen AI-related spend. Moreover, our gen AI focus creates a clear path for reinvesting in our business with what we anticipate to be near-term payback. Our 2025 budget calls for us to reinvest a portion of our cash from operations back into the business, while at the same time exceeding our 2024 adjusted EBITDA.

根據對人工智慧相關支出的預測，我們相信到 2025 年，這些客戶中的許多客戶已經有望實現兩位數的成長。此外，我們對人工智慧的關注為我們的業務再投資創造了一條清晰的道路，我們預計短期內將獲得回報。我們的 2025 年預算要求我們將部分營運現金重新投資到業務中，同時超過 2024 年調整後的 EBITDA。

Our scheduled investments are largely in people, spanning technology, product development, operations, and sales. We are pleased with how successful we have been recently at recruiting select top talent from prominent technology companies and leading competitors. They find our business momentum attractive, as well as the opportunity to build practices that align to the industry and technology trends that I just described.

我們計劃的投資主要用於人才，涵蓋技術、產品開發、營運和銷售。我們很高興看到我們最近成功地從知名科技公司和主要競爭對手中招募頂尖人才。他們發現我們的業務發展勢頭頗具吸引力，有機會建立符合我剛才所描述的產業和技術趨勢的實踐。

The work we're doing with our big tech customers on trust and safety is helping to inform our development of our automated trust and safety platform. We believe that our automated trust and safety platform will be useful to enterprises to measure how their models and agents are working, to surface vulnerabilities and misalignments, and to identify specific training required for continuous improvement. We're building this for the agentic era, in which we anticipate companies will depend on a rich ecosystem of agents to power their operations and products.

我們與大型科技客戶在信任和安全方面進行的合作有助於我們開發自動化信任和安全平台。我們相信，我們的自動化信任和安全平台將有助於企業衡量其模型和代理商的工作情況、發現漏洞和錯位，並確定持續改進所需的特定培訓。我們正在為代理時代建立這個系統，我們預計，屆時公司將依賴豐富的代理生態系統來支援他們的營運和產品。

In the last few months, we have worked hand-in-hand with prospective customers and partners, designing functions and features. We demoed the platform for the big tech company that I spoke about earlier as having just engaged us at a 3.6 million trust and safety program. And I believe what they saw helped us seal the deal. We expect to beta release the product to select charter customers in Q2.

在過去的幾個月裡，我們與潛在客戶和合作夥伴攜手設計功能和功能。我們為一家大型科技公司展示了這個平台，我之前提到過，該公司剛剛與我們合作開展一項涉及 360 萬的信任與安全計畫。我相信他們所看到的情況幫助我們達成了這筆交易。我們預計將在第二季向選定的特許客戶發布該產品的測試版。

I'll now turn the call over to Marissa to go over the financial results, after which Marissa, Aneesh, and I will be available to take questions from our analysts. Marissa?

現在，我將把電話轉給瑪麗莎，讓她討論財務結果，之後，瑪麗莎、阿尼什和我將回答我們分析師的問題。瑪麗莎？

Thank you, Jack, and good afternoon, everyone. Revenue for Q4 2024 reached $59.2 million, reflecting a year-over-year increase of 127%. This exceeded our expectations, benefiting from a project we delivered in the quarter for one of our new big tech customers. For 2024 as a whole, we grew 96%.

謝謝你，傑克，大家下午好。2024 年第四季的營收達到 5,920 萬美元，年增 127%。這超出了我們的預期，得益於我們本季為一位新的大型科技客戶交付的一個專案。就 2024 年全年而言，我們成長了 96%。

For the quarter, adjusted gross margin was 48%, representing a 4% sequential increase from the 44% we achieved in Q3 of 2024. This was a strong result, driven by a project for one of our new big tech customers in the fourth quarter that yielded strong margin, as well as automation efforts and management initiatives that reduced headcount and optimized costs in our Synodex business.

本季度，調整後的毛利率為 48%，較 2024 年第三季的 44% 較上季成長 4%。這是一項強勁的業績，得益於我們在第四季度為一家新的大型科技客戶開展的項目，該項目產生了強勁的利潤，同時自動化工作和管理舉措減少了員工數量並優化了 Synodex 業務的成本。

For the year, adjusted gross margin climbed slightly from 42% to 43%, which would have been 45% without the $3.6 million of recruiting costs we incurred in Q2 to scale the business.

今年，調整後的毛利率從 42% 小幅上升至 43%，而如果我們不計第二季為擴大業務而產生的 360 萬美元招聘成本，毛利率將達到 45%。

Adjusted EBITDA for the fourth quarter was $14.1 million, or 23.9% of revenue up from $4.3 million year over year. For the year, adjusted EBITDA was $34.6 million, or 20.3% of revenue, up from $9.9 million from 2023. Our result in both quarters and the year demonstrated strong operating leverage characteristics of our business.

第四季調整後 EBITDA 為 1,410 萬美元，佔營收的 23.9%，高於去年同期的 430 萬美元。全年調整後的 EBITDA 為 3,460 萬美元，佔營收的 20.3%，高於 2023 年的 990 萬美元。我們的兩個季度和全年業績都體現了我們業務強大的經營槓桿特徵。

Net income was $10.3 million in the fourth quarter, up from $1.7 million in the same period last year. For the year, net income was $28.7 million, which was 3,256% higher than 2023. We were able to utilize the benefit of accumulated net operating losses, or NOLCO, in Q3 and in Q4 to partially offset our tax provision. As a result, our effective tax rate for 2024 was approximately a negative 17.1%. Without the benefit of NOLCO, our effective tax rate would have been approximately 20%.

第四季淨收入為1,030萬美元，高於去年同期的170萬美元。全年淨收入為 2,870 萬美元，比 2023 年高出 3,256%。我們能夠利用第三季和第四季的累計淨營業虧損（NOLCO）來部分抵銷我們的稅款準備金。因此，我們 2024 年的有效稅率約為負 17.1%。如果沒有 NOLCO 的幫助，我們的實際稅率將約為 20%。

Absent any changes to our tax environment and variables, we expect our 2025 tax rate to be in the range of 28% to 31.5%. Our cash position at the end of Q4 was $46.9 million, up $26.4 million at the end of Q3, and up from $13.8 million at the year-end 2023.

如果我們的稅收環境和變數沒有任何變化，我們預計 2025 年的稅率將在 28% 至 31.5% 之間。我們第四季末的現金狀況為 4,690 萬美元，比第三季末增加了 2,640 萬美元，比 2023 年底的 1,380 萬美元有所增加。

We still have not drawn on our $30 million Wells Fargo Credit Facility that we increased in Q2 of 2024. The amount drawable under this facility at any point in time is determined based on borrowing-based formula. Jack also mentioned that in 2025, we plan on investing in extending our capabilities.

我們仍未動用 2024 年第二季增加的 3,000 萬美元富國銀行信貸額度。此項服務在任何時間點可提取的金額是根據借款公式決定的。傑克也提到，2025 年，我們計劃投資擴展我們的能力。

Our internal budget has us dialing up strategic hires and product development expenditure as we saw the seed for long-term growth. From a budget and forecasting perspective, we believe we can dial up reinvestment of operating cash flow while at the same time aim to exceed 2024's adjusted EBITDA. That's all on my side.

我們的內部預算讓我們增加了策略性招募和產品開發支出，因為我們看到了長期成長的種子。從預算和預測的角度來看，我們相信我們可以增加營運現金流的再投資，同時力求超過 2024 年的調整後 EBITDA。這些都是我的看法。

Thank you, everyone, for joining today. Operator, please open the line for questions.

感謝大家今天的參加。接線員，請打開電話線以回答問題。

(Operator Instructions)

（操作員指令）

George Sutton, Craig-Hallum.

喬治·薩頓、克雷格·哈勒姆。

Thank you. Fabulous job, guys. So I was particularly excited to see the 159% sequential growth from your seven other big tech customers. I wondered if you could just lay out the future for that group, if you would. And how does it dovetail with the number of pilots that you're seeing? You mentioned seven to eight-figure opportunities. Are those coming from those seven or those additional customers?

謝謝。你們幹得太棒了。因此，我特別高興看到您的其他七家大型科技客戶的環比增長達到 159%。我想知道您是否可以簡單描述一下該團體的未來。這和您見到的飛行員數量有關係嗎？您提到了七到八位數的機會。這些是來自那七家還是來自額外的客戶？

Hi, George. Well, thank you very much for that. Great question. So the pilots that we're talking about are coming from a combination of those additional big techs. And I can think of one enterprise that we also have, a very large-scale deal that's in what we would refer to as a pilot stage right now. So we're focused this year on big techs in order to achieve our growth plans.

你好，喬治。好吧，非常感謝。好問題。因此，我們所談論的試點項目均來自這些額外大型科技公司的共同開發。我還想到了我們擁有的一家企業，這是一項非常大規模的交易，目前處於我們所說的試點階段。因此，為了實現我們的成長計劃，我們今年將專注於大型技術。

But we're working hard on the enterprise side as well. We're putting in place some key partnerships, some key wins, some key capabilities. And we're seeing that start to bubble up a bit in the pipeline.

但我們也在企業方面努力工作。我們正在建立一些重要的合作關係、取得一些重要的成果並實現一些重要的能力。我們看到這現像在管道中開始有所顯現。

So I want to go back to the football-dime analogy that you used in terms of where the current models are and talk about your largest customer by example. And this is really a duration question, because I think one of the challenges people have is how long will this customer be this size or larger? Can you just address it from that football-dime analogy perspective?

因此，我想回到您使用的足球一角硬幣類比，就當前模型而言，並舉例談談您最大的客戶。這其實是一個持續時間的問題，因為我認為人們面臨的一個挑戰就是這個客戶的規模能維持多久或更大？你能從足球一角硬幣類比的角度來解決這個問題嗎？

Yes. So the analogy that we're using, and I think I can credit one of our internal data scientists with this. I don't know if he got it from somewhere else, but I find it very useful. So we think about the bounds of the containerization of all human knowledge as expressed or expressible potentially as data as being the size of a football. And if we hold that visual image in mind, we can think by comparison as the data that's been used to train today's LLMs as being the size of a dime.

是的。所以，我們正在使用這個類比，我認為我可以將此歸功於我們的一位內部資料科學家。我不知道他是否從其他地方得到它，但我發現它非常有用。因此，我們認為所有人類知識的容器化的界限，就像以數據形式表達或可能表達的那樣，是足球大小。如果我們記住這個視覺圖像，我們可以透過比較來想像，用於訓練今天的法學碩士的數據就像一角硬幣那麼大。

Now, what does that mean? That means that there's a whole lot of additional data that the models of the future are going to need to learn from to be able to function at something that begins to resemble over time as AGI, the ability to closely mimic the capabilities of a human. And when we peel that back a bit, we see lots of different things. We see expert data, reasoning data, multilingual data, multimodal data, meta-learning.

那麼，這是什麼意思呢？這意味著未來的模型需要學習大量額外的數據，才能逐漸發揮類似 AGI 的功能，即緊密模仿人類的能力。當我們稍微回顧一下，就會發現很多不同的東西。我們看到專家資料、推理資料、多語言資料、多模式資料、元學習。

So learning and expressing as data, how do human beings think when they take apart a problem, when they assign components of that problem out, when they order their operations around solving a particular problem? And the problem doesn't even have to be a particularly sophisticated one, although it can be. So there's a ton of data that needs to be captured and that needs to be addressable in order for the models to learn from it.

因此，透過學習和表達數據，當人類分解問題、分配問題的各個組成部分、安排操作以解決特定問題時，他們是如何思考的？儘管這個問題可能非常複雜，但它甚至不必非常複雜。因此，需要捕獲大量資料並且需要對其進行尋址，以便模型可以從中學習。

And that, we believe, is our opportunity, or one of our opportunities. It's not even our only opportunity, but it's a very exciting opportunity. And given the -- what you were all and we were all reading about in their recent earnings reports in terms of the uptick in capital spending principally for these technologies and these capabilities, we believe that we're still in the early innings.

我們相信，這是我們的機會，或說我們的機會之一。這甚至不是我們唯一的機會，但這是一個非常令人興奮的機會。考慮到大家和我們都在他們最近的收益報告中讀到的關於這些技術和這些能力的資本支出增加的情況，我們認為我們仍處於早期階段。

Got you. And then one other question. A lot of discussion relative to models being either open or closed. Can you talk about your opportunity as it may differ from one versus the other?

明白了。還有一個問題。關於模型是開放還是封閉的討論很多。您能談談您的機會嗎？因為它可能彼此不同？

Yes, sure. So I think that we've got opportunities very clearly on both sides of the fence. We're working on open source models with customers for whom open source is a primary strategy, and we're working with customers who are building closed source models.

是的，當然。因此我認為我們在雙方都有非常明顯的機會。我們正在與以開源為主要策略的客戶合作開發開源模型，我們也正在與那些正在建立閉源模型的客戶合作。

I think open source is particularly interesting because in combination with the likely declines in cost of inferencing and costs of computing cycles necessary to train models, the world of opportunity is going to open up well past today's integration strategies for an enterprise. They're going to open up in terms of training, you know, very specific agents. You can call it small language models for building on top of open source models, doing complete supervised SFT models based on that.

我認為開源特別有趣，因為結合推理成本和訓練模型所需的運算週期成本可能下降，機會世界將會遠遠超越當今企業的整合策略。他們將會開放培訓，你知道，非常具體的特工。你可以稱之為在開源模型之上建立的小型語言模型，並在此基礎上建立完整的監督式 SFT 模型。

That's a huge opportunity for us. There's a lot that enterprise struggle with in terms of even where is their data? What's their policies around data? How do they access it? Where's a federated golden source for the latest data?

這對我們來說是一個巨大的機會。企業面臨很多困難，例如他們的數據在哪裡？他們針對數據制定了什麼政策？他們如何訪問它？最新數據的聯合黃金來源在哪裡？

Well, all of that is data engineering that's going to get worked out with our help, we hope. And on top of that, building the models that form up their complex future agentic ecosystems. So we see opportunity all over the place right now.

好吧，我們希望所有這些都是數據工程，可以在我們的幫助下解決。在此基礎上，建構構成未來複雜的代理生態系的模型。所以我們現在看到到處都有機遇。

All right. Good stuff. Thank you very much.

好的。好東西。非常感謝。

Allen Klee, Maxim Group.

艾倫·克萊（Allen Klee），馬克西姆集團（Maxim Group）。

Great. Congrats. One business question, then a couple of financials. he business one is, there's been a lot of questions in the market with DeepSeek and some thinking of like that maybe through inferencing, whether using other AI models to kind of figure out the answers instead of training.

偉大的。恭喜。一個業務問題，然後幾個財務問題。第一點是，市場上對 DeepSeek 有很多疑問，有人在思考是否可以透過推理，或使用其他 AI 模型來找出答案，而不是進行訓練。

And does that mean that there could potentially be less training done? And I think you did address it, but could you just kind of go into that a little more? Because I think there's some questions in the market.

這是否意味著訓練量可能會減少？我認為您確實提到了這一點，但您能否再進一步詳細闡述呢？因為我認為市場上存在一些問題。

Yes, sure. Happy to. So it's well respected and well recognized among data scientists, that distillation of data. So using data from existing models to train new models creates model collapse. What happens is model diversity drops and that compromises certainly the upper limit of performance.

是的，當然。很開心。因此，數據提煉受到數據科學家的廣泛尊重和認可。因此，使用現有模型的資料來訓練新模型會導致模型崩潰。所發生的情況是模型多樣性下降，這肯定會損害性能的上限。

What you observe is memorization versus true cognition. Now, you can do that cleverly in a way that maximizes how you perform on benchmarks. We call that benchmaxing. And I think clearly the DeepSeek team did an amazing job at benchmaxing across a diversity of benchmarks. So hats off to them for that.

你觀察到的是記憶與真正的認知。現在，您可以巧妙地做到這一點，以最大限度地提高您的基準測試表現。我們稱之為基準測試。我認為 DeepSeek 團隊在多種基準測試中表現出色。我向他們表示敬意。

But the fact remains that when you do distillation, you're hugely compressing the data. You're introducing a huge amount of bias into the model. You're inviting model collapse. And that's why even if you read the technical report from DeepSeek, much less the notes and transcripts that are available of some closed door discussions they had in China with their researchers, they clearly recognize the limitations of what they've done. They clearly talk about how going forward they're going to need to do a lot more work and a lot more investment in terms of data in order to catch up with true performance.

但事實是，當你進行蒸餾時，你會大量壓縮數據。你在模型中引入了大量偏見。你正在導致模型崩潰。這就是為什麼即使你讀過 DeepSeek 的技術報告，更不用說他們在中國與研究人員進行的一些閉門討論的筆記和記錄，他們也清楚地認識到他們所做工作的局限性。他們清楚地談到了未來他們需要做更多的工作，在數據方面投入更多的資金才能達到真正的表現。

So data distillation is a technique; it's a known technique. That wasn't an innovation. Data distillation creates model collapse. And that's why I don't think you're going to see the people that are really driving toward AGI in a serious way and creating the frontier models embracing that as a viable technique.

所以數據提煉是一種技術；這是一種已知技術。那不算什麼創新。數據提煉導致模型崩潰。這就是為什麼我認為你不會看到人們真正認真地推動 AGI 的發展，並創建前沿模型將其作為可行的技術。

Very good. Thank you. And a couple of financial questions. I'll try to be quick. Your gross margins were 45.2% versus 40.8% in the third quarter and 34.8% in the prior year, fourth quarter. You mentioned that of the reasons why one of them, I heard you guys say that it was a new tech customer, something you were working on, but also automation and less headcount and Synodex.

非常好。謝謝。還有幾個財務問題。我會盡量快一點。您的毛利率為 45.2%，而第三季為 40.8%，去年第四季為 34.8%。您提到其中一個原因，我聽你們說這是一個新的技術客戶，是你們正在研究的東西，但同時也包括自動化和更少的員工和 Synodex。

What I'm trying to understand is, do you think there's potential from where it's at now to potentially expand as we go through '25? Or is there any reason why it was unusually a little high in the fourth quarter?

我想了解的是，您是否認為，從現在的情況來看，隨著我們進入 25 年，它還有進一步擴大的潛力？或者說為什麼第四季的漲幅異常高呢？有什麼原因嗎？

Aneesh, do you want to take that?

Aneesh，你想拿走那個嗎？

Yes, of course, Jack. So Alan, I guess just in terms of Q4 specifically, with that set customer, there were certain projects which we were working on where we had pretty healthy margins. And then just the mixed effect with some of our other customers, we were able to generate, as you said, 45% in Q4.

是的，當然，傑克。所以艾倫，我想僅就第四季而言，對於那批固定客戶，我們正在進行某些項目，並且獲得了相當可觀的利潤。然後，加上我們與其他一些客戶的混合效應，正如您所說，我們在第四季度實現了 45% 的收益。

As we think about 2025, holistically, there's always going to be some puts and takes as it relates to gross margin, as it relates to specific programs with specific customers. We, on a fully loaded basis, will generally be targeting around the 40% adjusted gross margin for net new opportunities, which we think is a pretty healthy level of margin for a services company.

當我們展望 2025 年時，從整體來看，總是會存在一些與毛利率、與特定客戶的特定項目相關的利弊。在滿載的情況下，我們通常會將淨新機會的調整後毛利率定為 40% 左右，我們認為對於一家服務公司來說，這是一個相當健康的利潤水準。

Of course, all the opportunities, as we continue to win new customers, we'd be hoping to get more than that. But that's kind of how we're thinking about net new opportunities on the margin front. I hope that makes sense, Allen.

當然，隨著我們不斷贏得新客戶，我們希望獲得更多的機會。但這正是我們對利潤方面的淨新機會的看法。我希望這是有道理的，艾倫。

Yes, that's very helpful. Thank you. The last question, and I know you may not answer this because you didn't do it yet, but can you help us in any way, you say, you're going to be reinvesting, which I believe is the right thing to do for long term, medium term, long term growth. EBITDA will be up year over year. Is there anything you can help us with in terms of qualitatively what that is, of being up year over year and how to think about that?

是的，這很有幫助。謝謝。最後一個問題，我知道你可能不會回答，因為你還沒有回答，但是你能以任何方式幫助我們嗎，你說你將進行再投資，我相信這對於長期、中期、長期增長來說是正確的做法。EBITDA 將逐年上升。您能從品質上幫助我們了解這到底是什麼，同比增長情況如何，以及如何看待這一情況嗎？

I think what our plan calls for, at least, is to be investing primarily in people across an array of different areas. As you know, I mean, as is evident, we prize operational excellence. We're doing a lot still to tweak and automate and improve and everything else.

我認為我們的計劃至少要求主要對不同領域的人才進行投資。如您所知，我的意思是，顯然，我們重視卓越的營運。我們仍在做大量工作來調整、自動化和改進其他一切。

As we make investments, we're going to be very careful about those. We believe that there's such a rich opportunity landscape that we can make investments and get a very near-term return on those investments. We see that we're able to hire some people who can be very impactful within our business. They love the momentum we've got right now.

當我們進行投資時，我們會非常謹慎。我們相信，這裡有如此豐富的機遇，我們可以進行投資並在短期內獲得回報。我們發現我們能夠聘用一些對我們的業務非常有影響力的人才。他們喜歡我們現在的勢頭。

They love the relationship, or excuse me, the reputation that they hear we're creating in the market when they talk to our customers. They like our plan. They like our vision for what our capabilities are going to be now and into the future.

當他們與我們的客戶交談時，他們聽說我們在市場上建立了這種關係，或者對不起，他們喜歡這種聲譽。他們喜歡我們的計劃。他們喜歡我們對現在和未來能力的願景。

But I think we're reluctant to fix a number in terms of what those investments will be, even though in our plan we have a number. We want to be somewhat flexible. We want to quite possibly dial that up as we dial up forecastable growth. But we're going to be disappointed about it. That's why one of the things we want to measure ourselves against and hopefully hold us to is that as we dial up those investments, we'll also be looking at adjusted EBITDA with our stated goal of beating last year.

但我認為，我們不願意確定這些投資的具體數字，儘管我們的計劃中有一個數字。我們希望有一定的彈性。我們希望在實現可預測成長的同時，也盡可能地實現這一目標。但我們將會對此感到失望。這就是為什麼我們要衡量自己並堅持做到的一件事是，當我們增加這些投資時，我們也將專注於調整後的 EBITDA，我們的目標是超越去年的水平。

Okay, great. Thank you very much.

好的，太好了。非常感謝。

Hamed Khorsand, BWS.

哈米德·霍爾桑德（Hamed Khorsand），BWS。

Hi. Just on the topic of you're looking to invest, are you at capacity now with the client base you have? Do you need it for new projects? Do you need it because you have a sales funnel? Why do you feel like you need to expand your headcount now?

你好。就您想要投資的話題而言，您現在的客戶群是否已經滿載了？您需要它用於新專案嗎？您是否因為有銷售管道而需要它？為什麼您覺得現在需要擴大員工人數？

Sure. So I think it's helpful, Hamed, to distinguish between cost of goods and SG&A. On the cost of goods side, we're able to expand in close proximity to opportunity. We don't need to carry a large bench of capabilities or bench of talent. We don't experience constraint in terms of revenue and revenue opportunity relative to cost of goods.

當然。因此，哈米德，我認為區分商品成本和銷售、一般和行政費用是有幫助的。在商品成本方面，我們能夠在緊鄰機會的情況下進行擴張。我們不需要擁有大量的能力或人才。相對於商品成本，我們在收入和收入機會方面沒有受到限制。

What we do though, in cost of goods is we prepare for the next phases of growth. We want to make sure that we've got the management talent and technical talent and other things required in order to achieve our growth ambitions on that side.

不過，我們在商品成本方面所做的是為下一階段的成長做好準備。我們希望確保我們擁有管理人才、技術人才和其他必要資源，以實現我們在這方面的成長目標。

Now, on the SG&A side, it's a question of ambition. It's a question of, well, how much more do we want to do? How much opportunity do we want to try to seize? What are the things that we think we have justification in potentially winning with the relationships we have and the brand that we have and the capabilities we have? And frankly, there's a lot that we see there. So what you're seeing when we talk about investments is a reflection of the ambition that we have for who we think we can become.

現在，就銷售、一般及行政費用 (SG&A) 方面而言，這是一個雄心壯志的問題。問題是，我們還想做多少？我們想要盡力抓住多少機會？我們認為憑藉我們現有的關係、品牌和能力，我們有可能贏得哪些勝利？坦白說，我們在那裡看到了很多東西。因此，當我們談論投資時，您看到的是我們對自身目標的雄心壯志的體現。

The people we're hiring today, they know how to do things I can hardly even understand. And I love that because we're getting deep into the technology. We're operating in ways that go well beyond anything that we've ever done in the past. And the work that we're doing is well-received by our customers.

我們今天僱用的人知道如何做我幾乎無法理解的事情。我非常喜歡這一點，因為我們正在深入研究這項技術。我們的運作方式遠遠超出了我們過去的任何方式。我們所做的工作受到了客戶的一致好評。

So we're going to keep feeding the beast there. And we'll do so, as I said, in response to the last question, in a way that is disciplined, in a way that enables us to have our cake and eat it too. So to both show, hopefully, year-over-year improvements in key operating metrics, as well as growth levels like what we're showing now and expansion capabilities.

因此，我們將繼續在那裡餵養這頭野獸。正如我在回答最後一個問題時所說的那樣，我們將以一種有紀律的方式，以一種能夠讓我們魚與熊掌兼得的方式這樣做。因此，我們希望既能顯示出關鍵營運指標的年成長，又能顯示出我們現在所展現的成長水準和擴張能力。

Okay. And then on the pilot trials you were talking about earlier, is that opportunity as far as taking business away from a competitor or competitors? Or is that brand new projects that you hope to win?

好的。那麼，關於您之前談到的試點試驗，這是否是從競爭對手手中搶走業務的機會？還是您希望贏得的是全新的項目？

I think that there's probably a bit here and there that we've taken from competitors. I know that that is the case here and there. But for the most part, that's not our strategy. This pie is expanding so rapidly that we're focused not on eating someone else's lunch relative to yesterday's -- I'm mixing metaphors terribly, yesterday's pie.

我認為我們可能從競爭對手那裡學到了一些東西。我知道這裡和那裡的情況都是這樣的。但大多數情況下，這不是我們的策略。這個蛋糕擴大得如此之快，以至於我們的注意力不在於吃別人相對於昨天的午餐——我把比喻混淆了，昨天的蛋糕。

But we're focused on, as that pie expands, how do we get a disproportionate share of that expansion? What do we need to be able to do? What do we need to have in place? What do we need to be able to prove that we're seeing as adding disproportionate value relative to our competitors?

但我們關注的是，隨著蛋糕不斷擴大，我們如何獲得不成比例的份額？我們需要具備什麼能力？我們需要做好哪些準備？我們需要怎樣的證據才能證明，與競爭對手相比，我們增加了不成比例的價值？

Okay. And then my final question is, do you feel like you're under less stress because you're cash-positioned now? Or do you think because you're at a higher revenue run rate, you still need a little bit more liquidity than you have now?

好的。我的最後一個問題是，您是否覺得由於您現在有現金，壓力就小了？或者您認為，由於您的收入運行率較高，您仍然需要比現在多一點的流動性？

I think we're very well positioned. We've seen the increase in cash that we've got on our balance sheet now. We haven't tapped our credit facility at all. We're forecasting a very significant level of free cash flow generation.

我認為我們處於非常有利的位置。我們現在看到資產負債表上的現金增加。我們根本沒有動用任何信貸資源。我們預測自由現金流的產生量將非常可觀。

And we're very targeted and very disciplined in terms of the investments we're going to be making. So I think we've got what it takes and we've got what it needs. That said, as I'll repeat again, we're very ambitious. We want to be in a position to seize opportunity. And as that opportunity presents itself to us, we'll, I hope, make the right decisions.

就我們將要進行的投資而言，我們非常有針對性且非常自律。所以我認為我們已經擁有了它所需要的一切。這就是說，我再重複一遍，我們非常有野心。我們希望能夠抓住機會。當這個機會出現在我們面前時，我希望我們能做出正確的決定。

Okay, thank you.

好的，謝謝。

Thank you. There are no further questions at this time. I would now hand the call back to Mr. Jack Abuhoff, for any closing remarks.

謝謝。目前沒有其他問題。現在我將把電話交還給傑克·阿布霍夫先生，請他做最後發言。

Operator, thank you. So, yes, Q4 was a record quarter. 2024 was a record year. We entered 2025 with really strong momentum. We're starting the year with guidance of 40% or more revenue growth, and we'll update that as we go forward, much like we did in 2024. Our confidence is underpinned by the continuing increase we're seeing in customer demand.

接線員，謝謝您。因此，是的，第四季度是一個創紀錄的季度。 2024 年是創紀錄的一年。我們以強勁的勢頭進入 2025 年。我們年初制定的預期是營收成長 40% 或更多，我們會隨著時間推移不斷更新這一預期，就像我們在 2024 年所做的那樣。客戶需求的持續成長增強了我們的信心。

We're announcing today new wins of $24 million in annualized run rate revenue from our largest customer, bringing our total run rate to approximately $135 million with this customer. And at the same time, you know, equally exciting. We grew revenue from our other seven big techs by 159% sequentially. And we think this is a big deal because it shows that our land and expand strategy is working.

我們今天宣布從我們最大的客戶那裡獲得了 2400 萬美元的年化運行率收入，使我們從該客戶獲得的總運行率達到約 1.35 億美元。同時，你知道，也同樣令人興奮。我們來自其他七大科技公司的營收連續成長了 159%。我們認為這是一件大事，因為這表明我們的土地和擴張策略正在發揮作用。

The macro environment is working in our favor as well. We believe the big techs are continuing to dial up their capital commitments to AI. And at the same time, we're anticipating a rapid acceleration in enterprise adoption, thanks in part to DeepSeek and other research labs that are optimizing hardware utilization, which then lowers entry costs for enterprise.

宏觀環境也對我們有利。我們相信，大型科技公司正持續增加對人工智慧的資本投入。同時，我們預期企業採用將會迅速加速，部分得益於 DeepSeek 和其他研究實驗室正在優化硬體利用率，從而降低企業的進入成本。

So the net-net is, we believe, we're in the right place at the right time. And that a potentially massive opportunity exists in front of us to position ourselves for continued strong growth in 2026 and beyond. Our plan calls for reinvesting in the business, while at the same time, hopefully, growing 2025s adjusted to EBITDA over 2024. The balance sheet is strong, $46.9 million in cash at year-end and an undrawn $30 million credit facility. So, we've clearly got the flexibility to execute our strategy.

因此，我們相信，我們在正確的時間處於正確的地點。我們面前存在著一個巨大的機遇，可以幫助我們實現 2026 年及以後的持續強勁成長。我們的計劃要求對業務進行再投資，同時希望 2025 年的 EBITDA 能夠比 2024 年有所成長。資產負債表強勁，年末現金為 4,690 萬美元，尚未提取的信用額度為 3,000 萬美元。因此，我們顯然具有執行我們策略的靈活性。

So, yes, again, thank you all for participating today and for being on this journey with us. We're committed to nothing less than making Innodata one of the greatest AI services companies out there. We'll look forward to updating you on our progress as the year progresses.

所以，是的，再次感謝大家今天的參與並與我們一起踏上這段旅程。我們致力於將 Innodata 打造為最偉大的 AI 服務公司之一。我們期待著隨著時間的推移向您通報我們的進展。

Thank you. And this concludes today's call. Thank you for participating. You may all disconnect.

謝謝。今天的電話會議到此結束。感謝您的參與。你們都可以斷開連線。