• Winning streak continues with latest deal, expected to be signed tomorrow
• Company has landed all three potentially transformative opportunities disclosed in Q2 report, plus fourth deal originally anticipated for later in year
• Company now poised to support four of Big Five global tech companies for generative AI development

NEW YORK, NY / ACCESSWIRE / August 10, 2023 / INNODATA INC. (NASDAQ:INOD) today reported results for the second quarter ended June 30, 2023.

• Revenue for the quarter ended June 30, 2023 was $19.7 million, compared to revenue of $20.0 million in the same period last year. The comparative period included $2.5 million in revenue from a large social media company that underwent a significant management change in the second half of last year, as a result of which it dramatically pulled back spending across the board. There was no revenue from this company in the quarter ended June 30, 2023.
• Net loss for the quarter ended June 30, 2023 was $0.8 million, or $0.03 per basic and diluted share, compared to a net loss of $3.8 million, or $0.14 per basic and diluted share, in the same period last year.
• Revenue for the six months ended June 30, 2023 was $38.5 million, compared to revenue of $41.2 million in the same period last year. The comparative period included $6.9 million in revenue from the large social media company referenced above. There was no revenue from this company in the six months ended June 30, 2023.
• Net loss for the six months ended June 30, 2023 was $2.9 million, or $0.11 per basic and diluted share, compared to a net loss of $6.6 million, or $0.24 per basic and diluted share, in the same period last year.
• Adjusted EBITDA was $1.6 million in the second quarter of 2023, compared to Adjusted EBITDA loss of $1.3 million in the same period last year.*
• Adjusted EBITDA was $2.4 million for the six months ended June 30, 2023, compared to Adjusted EBITDA loss of $2.3 million in the same period last year.*
• Cash, cash equivalents and short-term investments were $13.7 million at June 30, 2023, as compared to $10.3 million at December 31, 2022.

* Adjusted EBITDA is defined below.

The amounts in this press release have been rounded. All percentages have been calculated using unrounded amounts.

Jack Abuhoff, CEO, said, "Today we are announcing yet another highly anticipated win, which we expect gets signed tomorrow. We have now landed all of the deals we presented last quarter as potentially transformative. In the last eight weeks we have made four deal announcements. Two are with new customers, including the deal we are announcing today, and two are with an existing customer. All of these customers are among the top five global technology companies in the world. These engagements support AI and large language model development. Since these wins have all come in just the last eight weeks, they are not yet reflected in our financial results. We believe that these wins are potentially transformative for our company. Moreover, we believe that we are in the very early stages of exploiting a market opportunity which itself is in its early stages and for which - as our last eight weeks of wins demonstrate - we believe we are particularly well-suited. To give you a sense of the magnitude of our addressable market, an industry analyst recently estimated that AI-focused IT services are among the four hottest market opportunities in generative AI, all with 10-year CAGRs of 100% or more, with the market likely to grow from $83 million in 2022, to $21.7 billion by 2027 and to $85.9 billion by 2032.^[1]

"Further details on the deals we have announced, in reverse chronological order, are as follows:

• For the deal we announced today, we expect the customer to authorize $3.5 million in spend to get us started, and the customer has stated that it intends to supplement this authorization as we move forward. We expect to begin ramping up the engagement early in the fourth quarter. This customer has shared with us its vision for the initial program, which, if fully realized, we believe could potentially result in approximately $12 million dollars of new quarterly revenues at maturity. That said, at this point we do not know when or if the initial program will reach this level of spend. In addition, while the customer has told us we will be signing tomorrow, it is possible that this could slip as it is outside our control. Importantly, the agreement we expect to sign tomorrow with this new customer is a framework agreement that enables the customer's business units to easily add additional programs and allocate additional scope and spend to us. The customer has told us it will be potentially requesting us to participate in additional programs, which may include supporting the customer's own customer base with model fine tuning and integration.
• On July 18 we announced our engagement with another new Big Five tech customer. We kicked off an initial program over the last couple of weeks and based on discussions with this customer believe we may potentially get to an annualized run rate of $15 million dollars with this customer by end of the year solely on this initial program. We have begun discussions with this customer about additional programs.
• On June 27 we announced a white-labeled service, under which we will be performing AI data annotation and LLM fine-tuning for a hyperscaler's customers. While we stated in our June 27 press release that we expected to kick off the program with three end-customers in July, I'm pleased to report that we already have nine end-customers signed on for pilots - and we are not even halfway through August. We believe three of these pilots are highly likely to turn into booked business near-term, with one having an anticipated booking value of over $1 million. Beyond these nine white label enterprise pilots, we presently have a direct pipeline of enterprises with which we are now or soon plan to be engaged in discussions about LLM fine-tuning and integration. Our direct pipeline includes a large legal information company, one of the largest life insurance companies in the world, a leading investment bank, and a leading commercial bank. In the near-term, through this program with our customer, we anticipate a cadence of one to two new pilots each week. It is difficult to forecast the revenue opportunity this program represents because it is so new. However, if we can continue to onboard from this potential pool of tens of thousands of our customers' end-customers at the pace we are executing currently, we believe that this opportunity could dwarf any single initiative we are pursuing.
• On June 14 we announced that an existing Big 5 customer had engaged us for its LLM build program. In that announcement, we stated that we anticipated potentially exceeding $8 million in revenue this year with this customer. This is up from approximately $3 million last year. We believe there could potentially be considerable opportunity to expand existing programs with this customer and to land new programs. The white label program mentioned above was one of the additional programs we contemplated in that release. We thought it would come later in the year, and we are pleased that it has accelerated."

Innodata will host an investor conference call later today (details below), during which CEO Jack Abuhoff is expected to share the company's strategy, including its focus on the Big Five tech companies' generative AI initiatives; its white label services; and its enterprise LLM strategy. Abuhoff will discuss that, having secured the mega tech companies as customers, Innodata believes that it is well positioned to penetrate to other, potentially even larger market opportunities, including, (a) 50 to 100 technology companies that Innodata estimates are now building or are likely soon to be building LLMs; and (b) thousands of enterprises across verticals that Innodata believes are likely to invest in generative AI to obtain productivity benefits and otherwise remain competitive. During the call, Abuhoff is also expected to elaborate on and discuss the following:

• Under its white label services programs with hyperscalers, Innodata will perform LLM training and fine-tuning services on their behalf. These hyperscalers have positioned themselves to offer their customers compute, storage, foundation models, machine learning, database and data services - basically everything required to train and serve generative AI - all under one roof and at attractive price points;
• Innodata believes these white label programs could enable Innodata to rapidly deploy its services to a large number of enterprises, independent of its own sales and marketing, leveraging both the hyperscalers' brands and their customer reach;
• Through the white label program, Innodata believes it is likely to gain early exposure to a wide range of early-adopter generative AI use cases, having recently piloted use cases ranging from call center summarization, legal and medical question-answering, and ecommerce. Innodata believes this exposure will set it up well for what it believes will be our largest and most significant opportunity - LLMs for the enterprise. Innodata believes the pace of generative AI adoption among enterprises will rapidly accelerate as early adopters demonstrate dramatically enhanced productivity and significantly more compelling customer experiences. Innodata believes the hyperscalers will make it possible for companies of all sizes to customize their own large language models and build generative AI applications in a secure and enterprise-grade fashion. Innodata believes this will be further accelerated by high-performing, commercially-useable Open Source generative AI models that are becoming increasingly available as well as the best-performing closed source models that will likely soon support fine-tuning on proprietary data.
• Innodata's plans to exploit the enterprise opportunity with what it believes are five distinct competitive advantages:
  • First, the skills and referenceability it will have acquired helping the Big Five build the very foundation models with which enterprises will then be seeking to integrate;
  • Second, the experience it will have gained across a wide range of use cases working with early-adopter enterprises through its white-label engagements with the hyperscalers;
  • Third, the real-world experience it continues to gain in integrating both classical and generative AI into its own operations and products;
  • Fourth, its technology platforms for transforming enterprise data into LLM-ready context for both model fine-tuning and prompt injection; and
  • Fifth, its technology platforms (both existing and road mapped for development) that help enterprises generate reliable fact-based responses and insights from foundation models using techniques such as retrieval augmented generation, or RAG for short, that combine the reasoning and language engines of pre-trained LLMs with business' proprietary context data - unstructured data like technical documentation, images, videos, and reports, as well as structured content from enterprise systems and sensors.

Relative to Q2 performance and 2023 outlook, Abuhoff added, "In Q2, revenue was $19.7 million, a 4% increase from Q1, and Adjusted EBITDA was $1.6 million, a 100% increase from Q1, which we believe was made possible by the work we did late last year and into Q1 in sharpening our focus and finding opportunities to operate more cost effectively. There was no revenue in the quarter from the wins we discussed earlier. There was also no revenue in the quarter from the large social media company which contributed $2.5 million in revenue in Q2 of last year but dramatically pulled back spending in the second half of last year as it underwent a significant management change. If we back out revenue from this large social media company, our revenue growth in Q2 2023 over Q2 2022 would have been 13%.

"In terms of the second half of the year and going into 2024, we expect revenue and Adjusted EBITDA growth to accelerate in the ensuing quarters, both sequentially and year-over-year, as the wins we discussed today ramp up."

Abuhoff concluded, "We ended the quarter with $13.7 million in cash and short-term investments, up from $10.8 million at the end of Q1. We continue to have no appreciable debt. In order to support our growth and future working capital requirements, in the quarter we put in place a secured revolving line of credit with Wells Fargo that provides up to $10 million subject to a borrowing base limitation."

[1] https://www.bloomberg.com/company/press/generative-ai-to-become-a-1-3-trillion-market-by-2032-research-finds/

Timing of Conference Call with Q&A

Innodata will conduct an earnings conference call, including a question-and-answer period, at 5:00 PM eastern time today. You can participate in this call by dialing the following call-in numbers:

The call-in numbers for the conference call are:

1-877-545-0523 (Domestic)
+1 973-528-0016 (International)
Participant Access Code 219146

1-877-481-4010 (Domestic Replay)
+1 919-882-2331 (International Replay)
Replay Passcode 48772

It is recommended that participants dial in approximately 10 minutes prior to the start of the call. Investors are also invited to access a live Webcast of the conference call at the Investor Relations section of www.innodata.com. Please note that the Webcast feature will be in listen-only mode.

Call-in or Webcast replay will be available for 30 days following the conference call.

About Innodata

Innodata (NASDAQ:INOD) is a global data engineering company delivering the promise of AI to many of the world's most prestigious companies. We provide AI-enabled software platforms and managed services for AI data collection/annotation, AI digital transformation, and industry-specific business processes. Our low-code Innodata AI technology platform is at the core of our offerings. In every relationship, we honor our 30+ year legacy delivering the highest quality data and outstanding service to our customers. Visit www.innodata.com to learn more.

Forward Looking Statements

This press release may contain forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended, and Section 27A of the Securities Act of 1933, as amended. Words such as "project," "believe," "expect," "can," "continue," "could," "intend," "may," "should," "will," "anticipate," "indicate," "forecast," "predict," "likely," "goals," "estimate," "plan," "potential," "promises," "possible," or the negatives thereof and other similar expressions generally identify forward-looking statements, which speak only as of the date hereof.

These forward-looking statements are based on management's current expectations, assumptions and estimates and are subject to a number of risks and uncertainties, including without limitation, the expected or potential effects of the novel coronavirus ("COVID-19") pandemic and the responses of governments, the general global population, our customers, and the Company thereto; impacts resulting from the rapidly evolving conflict between Russia and the Ukraine; investments in large language models; that contracts may be terminated by customers; projected or committed volumes of work may not materialize; pipeline opportunities and customer discussions which may not materialize into work or expected volumes of work; continuing reliance on project-based work in the Digital Data Solutions ("DDS") segment and the primarily at-will nature of such contracts and the ability of these customers to reduce, delay or cancel projects; the likelihood of continued development of the markets, particularly new and emerging markets, that our services support; continuing DDS segment revenue concentration in a limited number of customers; potential inability to replace projects that are completed, canceled or reduced; our dependency on content providers in our Agility segment; difficulty in integrating and deriving synergies from acquisitions, joint venture and strategic investments; potential undiscovered liabilities of companies and businesses that we may acquire; potential impairment of the carrying value of goodwill and other acquired intangible assets of companies and businesses that we acquire; a continued downturn in or depressed market conditions; changes in external market factors; the ability and willingness of our customers and prospective customers to execute business plans that give rise to requirements for our services; changes in our business or growth strategy; the emergence of new, or growth in existing competitors; various other competitive and technological factors; our use of and reliance on information technology systems, including potential security breaches, cyber-attacks, privacy breaches or data breaches that result in the unauthorized disclosure of consumer, customer, employee or Company information, or service interruptions; and other risks and uncertainties indicated from time to time in our filings with the Securities and Exchange Commission.

Our actual results could differ materially from the results referred to in forward-looking statements. Factors that could cause or contribute to such differences include, but are not limited to, the risks discussed in Part I, Item 1A. "Risk Factors," Part II, Item 7. "Management's Discussion and Analysis of Financial Condition and Results of Operations," and other parts of our Annual Report on Form 10-K, filed with the Securities and Exchange Commission on February 24, 2023, as updated or amended by our other filings that we may make with the Securities and Exchange Commission. In light of these risks and uncertainties, there can be no assurance that the results referred to in the forward-looking statements will occur, and you should not place undue reliance on these forward-looking statements. These forward-looking statements speak only as of the date hereof.

We undertake no obligation to update or review any guidance or other forward-looking statements, whether as a result of new information, future developments or otherwise, except as may be required by the Federal securities laws.

Company Contact

Marcia Novero
Mnovero@innodata.com
(201) 371-8015

Non-GAAP Financial Measures

In addition to the financial information prepared in conformity with U.S. GAAP ("GAAP"), we provide certain non-GAAP financial information. We believe that these non-GAAP financial measures assist investors in making comparisons of period-to-period operating results. In some respects, management believes non-GAAP financial measures are more indicative of our ongoing core operating performance than their GAAP equivalents by making adjustments that management believes are reflective of the ongoing performance of the business.

We believe that the presentation of this non-GAAP financial information provides investors with greater transparency by providing investors a more complete understanding of our financial performance, competitive position, and prospects for the future, particularly by providing the same information that management and our Board of Directors use to evaluate our performance and manage the business. However, the non-GAAP financial measures presented in this press release have certain limitations in that they do not reflect all of the costs associated with the operations of our business as determined in accordance with GAAP. Therefore, investors should consider non-GAAP financial measures in addition to, and not as a substitute for, or as superior to, measures of financial performance prepared in accordance with GAAP. Further, the non-GAAP financial measures that we present may differ from similar non-GAAP financial measures used by other companies.

Adjusted EBITDA

We define Adjusted EBITDA as net income (loss) attributable to Innodata Inc. and its subsidiaries in accordance with U.S. GAAP before interest expense, income taxes, depreciation and amortization of intangible assets (which derives EBITDA), plus additional adjustments for loss on impairment of intangible assets and goodwill, stock-based compensation, income (loss) attributable to non-controlling interests, non-recurring severance, and other one-time costs.

We use Adjusted EBITDA to evaluate core results of operations and trends between fiscal periods and believe that these measures are important components of our internal performance measurement process.

A reconciliation of Adjusted EBITDA to the most directly comparable GAAP measure is included in the tables that accompany this release.

INNODATA INC. AND SUBSIDIARIES
CONDENSED CONSOLIDATED STATEMENTS OF OPERATIONS
(Unaudited)
(In thousands, except per-share amounts)

INNODATA INC. AND SUBSIDIARIES
CONDENSED CONSOLIDATED BALANCE SHEETS
(Unaudited)
(In thousands)

INNODATA INC. AND SUBSIDIARIES
CONDENSED CONSOLIDATED STATEMENTS OF CASH FLOWS
(Unaudited)
(In thousands)

INNODATA INC. AND SUBSIDIARIES
RECONCILIATION OF GAAP TO NON-GAAP FINANCIAL MEASURES
(Unaudited)
(In thousands)

** Represents non-recurring severance incurred for a reduction in headcount in connection with the re-alignment of the Company's cost structure.

INNODATA INC. AND SUBSIDIARIES
CONSOLIDATED REVENUE BY SEGMENT
(Unaudited)
(In thousands)

SOURCE: Innodata Inc.