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UNITED STATES
SECURITIES AND EXCHANGE COMMISSION
Washington, D.C. 20549
FORM 8-K
CURRENT REPORT
Pursuant to Section 13 or 15(d) of the Securities
Exchange Act of 1934
Date of Report (Date of earliest event reported):
February 22, 2024
INNODATA
INC.
(Exact name of registrant as specified in its charter)
Delaware |
001-35774 |
13-3475943 |
(State or other jurisdiction of |
(Commission File Number) |
(I.R.S. Employer |
incorporation) |
|
Identification No.) |
|
|
|
55 Challenger Road |
|
|
Ridgefield Park, NJ |
|
07660 |
(Address of principal executive offices) |
|
(Zip Code) |
Registrant's telephone number, including area code (201) 371-8000
(Former
name or former address, if changed since last report)
Check the appropriate box below if the Form 8-K filing is intended
to simultaneously satisfy the filing obligation of the registrant under any of the following provisions:
¨ | Written communications pursuant
to Rule 425 under the Securities Act (17 CFR 230.425) |
¨ | Soliciting material pursuant to
Rule 14a-12 under the Exchange Act (17 CFR 240.14a-12) |
¨ | Pre-commencement communications
pursuant to Rule 14d-2(b) under the Exchange Act (17 CFR 240.14d-2(b)) |
¨ | Pre-commencement communications
pursuant to Rule 13e-4(c) under the Exchange Act (17 CFR 240.13e-4(c)) |
Securities registered pursuant to Section 12(b)
of the Act:
Title of each class |
Trading Symbol(s) |
Name of each exchange on which registered |
Common Stock |
INOD |
The Nasdaq Stock Market LLC |
Indicate by check mark whether the registrant is an emerging growth
company as defined in Rule 405 of the Securities Act of 1933 (§230.405 of this chapter) or Rule 12b-2 of the Securities Exchange
Act of 1934 (§240.12b-2 of this chapter).
Emerging growth company ¨
If an emerging growth company, indicate by check
mark if the registrant has elected not to use the extended transition period for complying with any new or revised financial accounting
standards provided pursuant to Section 13(a) of the Exchange Act. ¨
Item 2.02 Results of Operations and Financial Condition.
On February 22, 2024, Innodata Inc. issued a press
release announcing its fourth quarter and fiscal year 2023 financial results. A copy of the press release is furnished with this Current
Report on Form 8-K as Exhibit 99.1.
In accordance with General
Instruction B.2 of Form 8-K, the information in this Current Report on Form 8-K, including Exhibit 99.1, shall not be deemed to be “filed”
for purposes of Section 18 of the Securities Exchange Act of 1934, as amended (the “Exchange Act”), or otherwise subject to
the liabilities of that section, and shall not be incorporated by reference into any registration statement or other document filed under
the Securities Act of 1933, as amended, or the Exchange Act, except as shall be expressly set forth by specific reference in such filing.
Item 9.01 Financial
Statements and Exhibits.
(d) Exhibits
See Exhibit Index below.
Exhibit Index
SIGNATURES
Pursuant to the requirements
of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto
duly authorized.
|
INNODATA INC. |
|
|
Date: February 22, 2024 |
By: |
/s/ Marissa B. Espineli |
|
|
Marissa B. Espineli |
|
|
Interim Chief Financial Officer |
Exhibit 99.1
Innodata Reports Fourth Quarter and
Fiscal Year 2023 Results
Fourth Quarter Revenue Up 35% Year-Over-Year
NEW YORK – February 22, 2024 –
INNODATA INC. (NASDAQ: INOD) today reported results for the fourth quarter and the year ended December 31, 2023.
| · | Revenue for the
quarter ended December 31, 2023 was $26.1 million, up 35% from revenue of $19.4 million in the same period last year. The comparative period included $0.5 million in revenue from the 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 three months ended December 31, 2023. |
| · | Net income for the quarter
ended December 31, 2023 was $1.7 million, or $0.06 per basic share and $0.05 per diluted share, compared to a net loss of $2.0 million,
or $0.07 per basic and diluted share, in the same period last year. |
| · | Total revenue for the
year ended December 31, 2023 was $86.8 million, up 10.0% from revenue of $79.0 million in 2022. The comparative period included $8.5 million in revenue from the large social media company referenced above. There was no revenue from
this company in 2023. |
| · | Net loss for the year
ended December 31, 2023 was $0.9 million, or $0.03 per basic and diluted share, compared to net loss of $12.0 million, or $0.44 per basic
and diluted share in 2022. |
| · | Adjusted EBITDA was $4.3
million in the fourth quarter of 2023, compared to Adjusted EBITDA of $0.2 million in the same period last year.* |
| · | Adjusted EBITDA was $9.9
million for the year ended December 31, 2023, compared to Adjusted EBITDA loss of $3.3 million in 2022.* |
| · | Cash, cash equivalents
and short-term investments were $13.8 million at December 31, 2023 and $10.3 million at December 31, 2022. |
* Adjusted EBITDA is defined below.
Amounts in this press release have been rounded.
All percentages have been calculated using unrounded amounts.
Jack Abuhoff, CEO, said, “We are pleased
to announce fourth quarter 2023 revenues of $26.1 million, representing 35% year-over-year growth and 18% sequential growth. We exceeded
our guidance of $24.5 million by 6.5% as a result of strong customer demand for generative AI services and our ability to ramp up quickly
to meet customer demand. In 2023 overall, we grew revenues 10%.
“It is worth noting that our Q4 2023 year-over-year
revenue growth was 39%, versus 35%, and our year-over-year revenue growth was 23%, versus 10%, if we back out revenue from the large social
media company that went through a highly-publicized take-private in 2022 in conjunction with which it terminated our services (as well
as services from many of its other vendors) and laid off 80% of its staff. This customer contributed $8.5 million in revenue in 2022 and
$0.5 million in revenue in Q4 of 2022. Beginning in Q1 2024, revenue from this customer will no longer provide a drag on year-over-year
comparisons.
“We are also very pleased to announce fourth
quarter Adjusted EBITDA of $4.3 million, exceeding our guidance of $3.7 million by 16%.
“Growth in Q4 was driven primarily
by ramp of generative AI development work for one of the Big Five tech companies we signed mid-2023 and also benefited by the start of
the generative AI development program with another of the Big Tech customers we announced late last summer.
“In late Q4, the first customer I mentioned
signed a three-year deal with us for our current, initial program, with an approximate value of $23 million per year for each of 2024,
2025, and 2026, or $69 million for the three years, based on the not-to-exceed value of the statement of work. We’re very proud
of this achievement. It came with customer kudos for the work we’ve done and expressions of interest in expanding the partnership
further. That said, and as a cautionary note, investors should understand that there are a number of ways under the SOW that the customer
could terminate early or reduce spend if it chose to. We believe the quality of our services will always be the key to enduring customer
relationships, not the stated term or value of a contract.
“We’re off to a strong start to 2024.
We entered the year with master service agreements in place with five of the so-called Magnificent Seven technology companies. With two
of these companies, we are now solidly underway. A third also contributed to Q4 growth, with a more significant ramp-up from this customer
starting this month. We are optimistic we will grow revenues with all three of these customers in 2024.
“With the remaining two of the five Mag
Seven customers, we’ve barely gotten out of the gate, but we are optimistic about making significant inroads this year. We are also
in conversations with several additional companies, including some of the most prominent leaders in generative AI today.
“We believe we have the strategy, business
momentum and customer relationships to deliver significant revenue growth in 2024. We will stick with our annual growth target of 20%
in 2024 with the intention of over-achieving this.”
Abuhoff continued, “In 2024, we will target
two broad markets. The first is Big Tech companies that are building generative AI foundation models and we believe are likely to spend
significantly on generative AI development. For these Big Tech companies, we provide a range of services they require to support their
gen AI programs. One of these services is the creation of instruction data sets. You can think of instruction data sets as the programming
used to fine tune large language models. Fine tuning with instruction data sets is what enables the models to understand prompts, to accept
instruction, to converse, to apparently reason, and to perform the myriad of incredible feats that many of us have now experienced. We
will also be providing reinforcement learning and reward modeling, services which are critical to provide the guardrails against toxic,
bias and harmful responses. In addition, we are also involved in model assessment and benchmarking, helping ensure that models meet performance,
risk and emerging regulatory requirements. Based on my conversations with several of these companies, as well as public remarks they have
made, we believe they are likely to spend hundreds of millions of dollars each year on these services. This spend is separate from and
in addition to their spend on data science and compute, the other essential ingredient of high-performing large language models.
“Our second target market is enterprises
across a wide range of verticals that seek to integrate and fine-tune generative AI models. These are still early days in terms of enterprise
adoption of generative AI, but we believe that a decade from now virtually all successful businesses will have adopted generative AI technologies
into their products and operations. For enterprises, our offerings including business process management, in which we re-engineer workflows
with AI and LLMs and perform the work as ongoing managed services. We also offer strategic technology consulting, where we work with customers
to define roadmaps for AI and LLM integration into both operations and products and build prototypes and proofs-of-concept. We also fine-tune
models, both in isolation and as part of larger systems that incorporate other technologies. For enterprises, we are capable of going
soup-to-nuts, everything from initial consulting to model selection to finetuning, deployment, and integration, as well as testing and
evaluations to ensure that the LLMs are helpful, honest, and harmless.
“Also for enterprises, we offer subscription-based
platforms and industry solutions that encapsulate AI - both our own models and leading 3rd party models. Much the way data
is at the heart of the programming-like work we do for Big Tech, data is similarly critical to enterprise deployments. Enterprise use
cases tend to be highly specific and targeted, requiring models that are trained with industry-specific or domain-specific data or that
require significant prompt engineering efforts and in-context learning utilizing carefully curated and organized company data.
“The bottom line here is that data engineering
is important for the big tech companies building generative AI foundation models and the enterprises adopting these technologies. Data
engineering has been our focus for the past two decades, and we believe we are quite good at it.”
Abuhoff concluded, “In response to some
questions we’ve recently been asked by investors:
| · | Several investors have asked whether we currently
anticipate needing to raise additional equity. |
| o | The answer is no, we do not currently anticipate needing to raise additional equity. We ended Q4 with
$13.8 million in cash and short-term investments, slightly down from $14.8 million last quarter, but that was largely due to timing, as
we had $2.4 million in cash receipts from major customers collected right after the New Year, and we generated over $4 million of Adjusted
EBITDA in Q4 alone. Nonetheless, to support our growth and future working capital requirements, we have a revolving line of credit with
Wells Fargo that provides up to $10 million of financing, 100% of which was available under our borrowing base as of the end of Q4. We
have not yet drawn down on the Wells Fargo line. We anticipate generating enough cash from operations in 2024 to fund our capital needs
without having to draw down on the Wells Fargo facility. |
| · | Several investors have asked why we have no
Chief Technology Officer. |
| o | In a sense we actually have four chief technology officers, or at least their equivalents, each
of which manage a specific technology area: we have a PhD in computer science and AI who heads our AI labs research team and data science
teams; we have an SVP of engineering overseeing product and platform engineering; we have another VP focused on software development and
product evolution for our Agility product; and we have a Chief Information Security Officer who heads security and infrastructure. Under
these leaders, we have close to 300 developers, architects, infrastructure managers and data scientists. We have found that this structure
best supports the breadth and scale of our business. |
| · | Investors have asked us to share our recent
spending on software and product development, and why do we not separately disclose it, and to comment on whether we have a significant
spend on cloud infrastructure. |
| o | In terms of our spending across software and product development, over the last five years, we spent about
$26 million. This peaked in 2022 at $8.9 million and came down to $6.4 million in 2023. However,
since roughly 80% percent of our business is managed services, we do not view the aggregate spending across these areas as a focal point
for investors. In terms of cloud, we spend a couple of million dollars per year, mostly for software, infrastructure and data hosting.
It is our Big Tech customers, not us, that spend massively on GPUs for training foundation models. |
| · | Other investors have asked us how they should
think about our comps. Specifically, they asked whether our comps are the largest technology and software companies in the world and whether
they should compare our R&D spend and Cloud compute spend to these companies. |
| o | These companies are absolutely not our comps. Rather many of these companies constitute part of our target
market. We are not in their business and, to state the obvious, we are not of similar scale. Players in this market are building foundation
models, and we are providing services to this market that help them on their journey. Therefore, we do not believe that comparing our
R&D spend and Cloud compute spend to theirs is especially useful. We view our competition as companies focused on AI data engineering
services to this market. |
| · | Another question we’ve gotten is how
did we manage to pivot to AI without having to raise substantial capital? |
| o | There are essentially three reasons we were able to pivot to AI without having to raise capital. The first
reason, which we believe is by far the most important, is that the massive spend we read about being required to build foundation models
is incurred by our large tech customers, not by us. Our customers are deploying extensive amounts of capital for cloud compute, for data
science, and for data engineering – three crucial ingredients to an LLM, if you will. We provide the kinds of data engineering services
they need, and providing data engineering does not require that we separately incur compute costs. The second reason we were able to transition
to AI data engineering without incurring massive upfront costs is that we have been a data engineering company for over 20 years, and
we were able to repurpose a lot of what we already had in place, including management, resources, facilities,
and technologies, to serve the AI use cases. The third reason is that when we began exploring AI back in 2016 and developing our
Goldengate infrastructure we incurred manageable investment. From a data perspective, because we were already employing large teams of
resources doing customer work, we did not have to incur incremental additional costs for humans-in-the-loop. We simply had to rearchitect
our operator workbenches and to create the right data lakes. The objectives we initially set for the models we built were to enable us
to reduce costs associated with maintaining rules-based data processing technologies. We were not seeking to automate the work of humans,
but to augment it. Over the years, Goldengate, one of our proprietary platforms, became, we believe, state-of-the-art at things like entity
extraction, data categorization and document zoning – all important aspects of what we do. We use the technology in customer deployments
and within our own platforms with great results. That said, Goldengate is not ChatGPT - you can’t converse with it or ask it to
perform magical feats like writing poetry. Goldengate has 50 million parameters, while ChatGPT is reputed to have 1.7 trillion parameters.
Nevertheless, Goldengate demonstrates that AI can be trained to perform specific tasks very well without incurring massive spending; that
AI deployments leveraging open source algorithms and models can be within reach for many enterprises for industry-specific datasets; and
that for business implementations especially, data engineering is more important than sheer model size as a predictor of performance. |
| · | A question we got recently is “How does
revenue per employee compare in your different lines of business”? |
| o | The answer is that revenue per employee is lowest in our managed services business, while it is multiple
times higher in our AI data engineering scaled services. Regardless, we target an adjusted gross margin of 35 to 37% across these business
lines, so we believe adjusted gross margin is the better metric to track. In our software business, our targeted gross margin is anticipated
to be about 73% this year, and we intend to target a consolidated adjusted gross margin of between 40 and 43%. |
| · | Another question we’ve gotten several
times recently is “Is Agility now profitable?” |
| o | The answer is yes. In this quarter, Agility posted Adjusted EBITDA of $1.2 million. This was a 69% sequential
increase over Q3. We think we executed the Agility business very well in 2023, growing it 15% in a difficult macro environment. It had
a strong adjusted gross margin of 69% over 2023 as a whole and 74% in Q4. We also love what we’ve done with the product –
we believe we’ve taken a leadership position as the first end-to-end public relations and media intelligence platform to integrate
generative AI.” |
Marissa Espineli, Interim CFO, added, “Other
questions we’ve gotten recently from investors have been:
| · | We’ve been asked about why we keep cash
overseas. |
| o | The reason we keep cash overseas is to cover operating expenses in these locations. We do not plan to
repatriate these funds nor do we foresee the need to. |
| · | We’ve been asked recently about our
cost-plus transfer pricing agreements with our offshore subsidiaries. |
| o | Companies that have revenue in, say, North America or Europe, but have offshore delivery centers in countries
like India and the Philippines, put in place what’s called transfer pricing arrangements to satisfy the arm’s length transaction
principle. Under a transfer pricing arrangement, a percentage of revenue is allocated to the delivery center. The percentage allocated
is often determined by statute or regulation in the foreign country. We understand that the reason the foreign country does this is to
make sure there are profits at the local level for it to tax. When the consolidated enterprise is losing money, and would not otherwise
have to pay taxes, it unfortunately ends up having to pay taxes offshore. Obviously, paying taxes when you are losing money is not a good
thing and is referred to as “tax leakage” - but even in this situation, the tax we pay is insignificant versus the money we
save by operating offshore. |
| · | We’ve been asked whether there is any
structural reason that Innodata would be expected to lose more money as it generates more revenue? |
| o | The answer to this is absolutely not. As Innodata revenue increases, we expect that its Adjusted EBITDA
will increase at an even higher percentage. This is because there is some operating leverage in our direct costs, for things like production
facilities, and significant operating leverage in our general and administrative operating costs. We saw clear evidence of this in both
Q3 and Q4. In Q3, revenue grew sequentially by $2.5 million and Adjusted EBITDA grew sequentially by $1.6 million. Similarly, in Q4, revenue
grew sequentially by $3.9 million and Adjusted EBITDA grew sequentially by $1.1 million. There will however, be quarterly fluctuations
in how much revenue falls to the EBITDA line based on how we flex our operating expenses, particularly our sales and marketing efforts,
based on market dynamics.” |
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:
1-888-506-0062 | |
(Domestic) | |
+1 973-528-0011 | |
(International) | |
Participant Access Code | |
383451 | |
| |
| |
1-877-481-4010 | |
(Domestic Replay) | |
+1 919-882-2331 | |
(International Replay) | |
Replay Passcode | |
49773 | |
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 certain 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. These forward-looking statements include, without limitation, statements
concerning our operations, economic performance, and financial condition. Words such as “project,” “believe,”
“expect,” “can,” “continue,” “could,” “intend,” “may,” “should,”
“will,” “anticipate,” “indicate,” “predict,” “likely,” “estimate,”
“plan,” “potential,” “possible,” “promises,” or the negatives thereof, and other similar
expressions generally identify forward-looking statements.
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, impacts resulting from the continuing conflict between Russia and the Ukraine and Hamas’ attack
against Israel and the ensuing conflict; 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; the likelihood of continued development of the markets, particularly new and emerging markets,
that our services support; the ability and willingness of our customers and prospective customers to execute business plans that give
rise to requirements for our services; 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; potential inability
to replace projects that are completed, canceled or reduced; continuing DDS segment revenue concentration in a limited number of customers;
our dependency on content providers in our Agility segment; difficulty in integrating and deriving synergies from acquisitions, joint
ventures 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; 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
Innodata Inc.
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)
| |
Three Months Ended | | |
Year Ended | |
| |
December 31 | | |
December 31 | |
| |
2023 | | |
2022 | | |
2023 | | |
2022 | |
Revenues | |
$ | 26,112 | | |
$ | 19,375 | | |
$ | 86,775 | | |
$ | 79,001 | |
| |
| | | |
| | | |
| | | |
| | |
Operating costs and expenses: | |
| | | |
| | | |
| | | |
| | |
| |
| | | |
| | | |
| | | |
| | |
Direct operating costs | |
| 15,948 | | |
| 12,740 | | |
| 55,482 | | |
| 51,533 | |
Selling and administrative expenses | |
| 8,203 | | |
| 8,355 | | |
| 30,975 | | |
| 37,940 | |
Interest expense, net | |
| 57 | | |
| 9 | | |
| 179 | | |
| 11 | |
| |
| 24,208 | | |
| 21,104 | | |
| 86,636 | | |
| 89,484 | |
Income (loss) before provision for income taxes | |
| 1,904 | | |
| (1,729 | ) | |
| 139 | | |
| (10,483 | ) |
Provision for income taxes | |
| 248 | | |
| 229 | | |
| 1,028 | | |
| 1,522 | |
Consolidated net income (loss) | |
| 1,656 | | |
| (1,958 | ) | |
| (889 | ) | |
| (12,005 | ) |
Income (loss) attributable to non-controlling interests | |
| 4 | | |
| 2 | | |
| 19 | | |
| (70 | ) |
Net income (loss) attributable to Innodata Inc. and Subsidiaries | |
$ | 1,652 | | |
$ | (1,960 | ) | |
$ | (908 | ) | |
$ | (11,935 | ) |
| |
| | | |
| | | |
| | | |
| | |
Income (loss) per share attributable to Innodata Inc. and Subsidiaries: | |
| | | |
| | | |
| | | |
| | |
Basic | |
$ | 0.06 | | |
$ | (0.07 | ) | |
$ | (0.03 | ) | |
$ | (0.44 | ) |
Diluted | |
$ | 0.05 | | |
$ | (0.07 | ) | |
$ | (0.03 | ) | |
$ | (0.44 | ) |
Weighted average shares outstanding: | |
| | | |
| | | |
| | | |
| | |
Basic | |
| 28,728 | | |
| 27,392 | | |
| 28,131 | | |
| 27,278 | |
Diluted | |
| 31,983 | | |
| 27,392 | | |
| 28,131 | | |
| 27,278 | |
INNODATA INC. AND SUBSIDIARIES
CONDENSED CONSOLIDATED BALANCE SHEETS
(Unaudited)
(In thousands)
| |
December 31, 2023 | | |
December 31, 2022 | |
ASSETS | |
| | | |
| | |
Current assets: | |
| | | |
| | |
Cash and cash equivalents | |
$ | 13,806 | | |
$ | 9,792 | |
Short term investments – other | |
| 14 | | |
| 507 | |
Accounts receivable, net | |
| 14,288 | | |
| 9,528 | |
Prepaid expenses and other current assets | |
| 3,969 | | |
| 3,858 | |
Total current assets | |
| 32,077 | | |
| 23,685 | |
Property and equipment, net | |
| 2,281 | | |
| 2,511 | |
Right-of-use asset, net | |
| 5,054 | | |
| 4,309 | |
Other assets | |
| 2,445 | | |
| 1,498 | |
Deferred income taxes, net | |
| 1,741 | | |
| 1,475 | |
Intangibles, net | |
| 13,758 | | |
| 12,526 | |
Goodwill | |
| 2,075 | | |
| 2,038 | |
Total assets | |
$ | 59,431 | | |
$ | 48,042 | |
| |
| | | |
| | |
LIABILITIES, NON-CONTROLLING INTERESTS AND STOCKHOLDERS’ EQUITY | |
| | | |
| | |
| |
| | | |
| | |
Current liabilities: | |
| | | |
| | |
Accounts payable, accrued expenses and other | |
$ | 9,245 | | |
$ | 9,880 | |
Accrued salaries, wages and related benefits | |
| 7,799 | | |
| 6,136 | |
Income and other taxes | |
| 3,848 | | |
| 3,230 | |
Long-term obligations – current portion | |
| 1,261 | | |
| 877 | |
Operating lease liability - current portion | |
| 782 | | |
| 693 | |
Total current liabilities | |
| 22,935 | | |
| 20,816 | |
Deferred income taxes, net | |
| 22 | | |
| 65 | |
Long-term obligations, net of current portion | |
| 6,778 | | |
| 5,079 | |
Operating lease liability, net of current portion | |
| 4,701 | | |
| 4,036 | |
Total liabilities | |
| 34,436 | | |
| 29,996 | |
Non-controlling interests | |
| (708 | ) | |
| (727 | ) |
STOCKHOLDERS' EQUITY | |
| 25,703 | | |
| 18,773 | |
Total liabilities, non-controlling interests and stockholders’ equity | |
$ | 59,431 | | |
$ | 48,042 | |
INNODATA INC. AND SUBSIDIARIES
CONDENSED CONSOLIDATED STATEMENTS OF CASH FLOWS
(Unaudited)
(In thousands)
| |
Year Ended | |
| |
December 31, | |
| |
2023 | | |
2022 | |
Cash flows from operating activities: | |
| | | |
| | |
Consolidated net loss | |
$ | (889 | ) | |
$ | (12,005 | ) |
Adjustments to reconcile consolidated net loss to net cash | |
| | | |
| | |
provided by operating activities: | |
| | | |
| | |
Depreciation and amortization | |
| 4,716 | | |
| 3,889 | |
Stock-based compensation | |
| 4,027 | | |
| 3,283 | |
Deferred income taxes | |
| (276 | ) | |
| 217 | |
Provision for doubtful accounts | |
| 426 | | |
| 480 | |
Pension cost | |
| 1,046 | | |
| 943 | |
Loss on lease termination | |
| - | | |
| 125 | |
Changes in operating assets and liabilities: | |
| | | |
| | |
Accounts receivable | |
| (5,116 | ) | |
| 1,303 | |
Prepaid expenses and other current assets | |
| 372 | | |
| (226 | ) |
Other assets | |
| (171 | ) | |
| 750 | |
Accounts payable, accrued expenses and
other | |
| (490 | ) | |
| 322 | |
Accrued salaries, wages and related benefits | |
| 1,653 | | |
| (310 | ) |
Income and other taxes | |
| 605 | | |
| 13 | |
Net cash provided by (used in) operating activities | |
| 5,903 | | |
| (1,216 | ) |
Cash flows from investing activities: | |
| | | |
| | |
Capital expenditures | |
| (5,564 | ) | |
| (6,526 | ) |
Proceeds from (purchase of) short term investments - others | |
| 493 | | |
| (507 | ) |
Net cash used in investing activities | |
| (5,071 | ) | |
| (7,033 | ) |
Cash flows from financing activities: | |
| | | |
| | |
Proceeds from exercise of stock options | |
| 3,324 | | |
| 332 | |
Payment of long-term obligations | |
| (452 | ) | |
| (639 | ) |
Net cash provided by (used in) financing activities | |
| 2,872 | | |
| (307 | ) |
Effect of exchange rate changes on cash and cash equivalents | |
| 310 | | |
| (554 | ) |
Net increase (decrease) in cash and cash equivalents | |
| 4,014 | | |
| (9,110 | ) |
Cash and cash equivalents, beginning of year | |
| 9,792 | | |
| 18,902 | |
Cash and cash equivalents, end of year | |
$ | 13,806 | | |
$ | 9,792 | |
INNODATA INC. AND SUBSIDIARIES
RECONCILIATION OF GAAP TO NON-GAAP FINANCIAL
MEASURES
(Unaudited)
(In thousands)
| |
Three Months Ended December 31, | | |
Year Ended December 31, | |
Consolidated | |
2023 | | |
2022 | | |
2023 | | |
2022 | |
Net income (loss) attributable to Innodata Inc. and Subsidiaries | |
$ | 1,652 | | |
$ | (1,960 | ) | |
$ | (908 | ) | |
$ | (11,935 | ) |
Provision for income taxes | |
| 248 | | |
| 229 | | |
| 1,028 | | |
| 1,522 | |
Interest expense | |
| 105 | | |
| 9 | | |
| 400 | | |
| 11 | |
Depreciation and amortization | |
| 1,237 | | |
| 1,053 | | |
| 4,716 | | |
| 3,889 | |
Severance** | |
| - | | |
| - | | |
| 580 | | |
| - | |
Stock-based compensation | |
| 1,029 | | |
| 913 | | |
| 4,027 | | |
| 3,283 | |
Non-controlling interests | |
| 4 | | |
| 2 | | |
| 19 | | |
| (70 | ) |
Adjusted EBITDA (loss) - Consolidated | |
$ | 4,275 | | |
$ | 246 | | |
$ | 9,862 | | |
$ | (3,300 | ) |
| |
Three Months Ended December 31, | | |
Year Ended December 31, | |
DDS Segment | |
2023 | | |
2022 | | |
2023 | | |
2022 | |
Net income (loss) attributable to DDS Segment | |
$ | 974 | | |
$ | (501 | ) | |
$ | 223 | | |
$ | (711 | ) |
Provision for income taxes | |
| 246 | | |
| 228 | | |
| 1,018 | | |
| 1,423 | |
Interest expense | |
| 104 | | |
| 9 | | |
| 395 | | |
| 10 | |
Depreciation and amortization | |
| 351 | | |
| 211 | | |
| 1,161 | | |
| 694 | |
Severance** | |
| - | | |
| - | | |
| 33 | | |
| - | |
Stock-based compensation | |
| 986 | | |
| 760 | | |
| 3,511 | | |
| 2,690 | |
Non-controlling interests | |
| 4 | | |
| 2 | | |
| 19 | | |
| 4 | |
Adjusted EBITDA - DDS Segment | |
$ | 2,665 | | |
$ | 709 | | |
$ | 6,360 | | |
$ | 4,110 | |
| |
Three Months Ended December 31, | | |
Year Ended December 31, | |
Synodex Segment | |
2023 | | |
2022 | | |
2023 | | |
2022 | |
Net income (loss) attributable to Synodex Segment | |
$ | 238 | | |
$ | (282 | ) | |
$ | 219 | | |
$ | (2,525 | ) |
Depreciation and amortization | |
| 144 | | |
| 174 | | |
| 623 | | |
| 656 | |
Severance** | |
| - | | |
| - | | |
| 6 | | |
| - | |
Stock-based compensation | |
| (10 | ) | |
| 130 | | |
| 167 | | |
| 258 | |
Non-controlling interests | |
| - | | |
| - | | |
| - | | |
| (74 | ) |
Adjusted EBITDA (loss) - Synodex Segment | |
$ | 372 | | |
$ | 22 | | |
$ | 1,015 | | |
$ | (1,685 | ) |
| |
Three Months Ended December 31, | | |
Year Ended December 31, | |
Agility Segment | |
2023 | | |
2022 | | |
2023 | | |
2022 | |
Net income (loss) attributable to Agility Segment | |
$ | 440 | | |
$ | (1,177 | ) | |
$ | (1,350 | ) | |
$ | (8,699 | ) |
Provision for income taxes | |
| 2 | | |
| 1 | | |
| 10 | | |
| 99 | |
Interest expense | |
| 1 | | |
| - | | |
| 5 | | |
| 1 | |
Depreciation and amortization | |
| 742 | | |
| 668 | | |
| 2,932 | | |
| 2,539 | |
Severance** | |
| - | | |
| - | | |
| 541 | | |
| - | |
Stock-based compensation | |
| 53 | | |
| 23 | | |
| 349 | | |
| 335 | |
Adjusted EBITDA (loss) - Agility Segment | |
$ | 1,238 | | |
$ | (485 | ) | |
$ | 2,487 | | |
$ | (5,725 | ) |
**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)
| |
Three Months Ended December 31, | | |
Year Ended December 31, | |
| |
2023 | | |
2022 | | |
2023 | | |
2022 | |
Revenues: | |
| | |
| | |
| | |
| |
DDS | |
$ | 19,646 | | |
$ | 13,579 | | |
$ | 61,576 | | |
$ | 56,523 | |
Synodex | |
| 1,807 | | |
| 1,729 | | |
| 7,511 | | |
| 7,105 | |
Agility | |
| 4,659 | | |
| 4,067 | | |
| 17,688 | | |
| 15,373 | |
Total Consolidated | |
$ | 26,112 | | |
$ | 19,375 | | |
$ | 86,775 | | |
$ | 79,001 | |
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Innodata (NASDAQ:INOD)
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