Here are 1-2 brief analogies to describe Innodata (INOD):

• Accenture for AI training data.
• Oracle for AI's foundational data infrastructure.

• AI Data Solutions: Provides high-quality data annotation, labeling, collection, and validation services essential for training and improving artificial intelligence and machine learning models.
• Content Services and Operations: Offers comprehensive services for digitizing, structuring, enriching, and managing large volumes of diverse content, including text, images, and video.
• Intelligent Automation: Delivers solutions leveraging AI, machine learning, and robotic process automation to automate complex business processes and enhance operational efficiency for enterprises.

Innodata (NASDAQ: INOD) primarily sells its AI-enabled services and solutions to other companies, operating on a Business-to-Business (B2B) model. Its customer base includes large enterprises across various industries such as technology, media, publishing, financial services, and retail.

Based on Innodata's annual report (Form 10-K) for the fiscal year ended December 31, 2023, the company stated a significant customer concentration:

• For the year ended December 31, 2023, one customer accounted for 24% of its total revenues.
• For the year ended December 31, 2022, one customer accounted for 27% of its total revenues.
• For the year ended December 31, 2021, one customer accounted for 28% of its total revenues.

While Innodata discloses its dependency on these major customers, the company does not publicly identify the specific names of these customer companies in its regulatory filings or investor communications, likely due to confidentiality agreements.

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Jack S. Abuhoff, Chairman & CEO

Jack S. Abuhoff is the co-founder of Innodata and has served as its Chief Executive Officer since September 1997. In November 2025, he also became the Chairman of the company. His professional background encompasses large-scale IT outsourcing, Sino-American infrastructure joint ventures, and international finance, with experience in both operational and advisory capacities. Prior to Innodata, he was the Chief Operating Officer for Charles River Corporation and held positions at White & Case LLP and Chadbourne & Parke LLP. He holds an A.B. from Columbia College and a J.D. from Harvard Law School.

Marissa Espineli, Interim Chief Financial Officer

Marissa Espineli serves as Innodata's Interim Chief Financial Officer. She has been the Vice President of Finance since 2012 and previously held the role of Corporate Controller. Before joining Innodata, she gained experience in key finance positions at major U.S.-based companies in the consumer goods, food & beverages, and industrial products sectors. She began her career in public accounting as a Senior Auditor, specializing in taxation and financial audits. She holds a Bachelor of Science in Business.

Rahul Singhal, President & Chief Revenue Officer

Rahul Singhal was promoted to President and Chief Revenue Officer in November 2025. He joined Innodata in 2019, having previously spent over a decade at IBM in various leadership capacities, including Program Director for IBM Watson Platform APIs. He also served as Chief Product Officer at Equals3.AI and is an Adjunct Professor at New York University, where he teaches Competitive Strategy and Advanced Experimental Design and Machine Learning.

Ashok Mishra, Executive VP & COO

Ashok Mishra is the Executive Vice President and Chief Operating Officer of Innodata. His previous roles at Innodata Isogen Inc. included Senior Vice President and Assistant Vice President.

Amy Agress, Senior VP & General Counsel

As Senior Vice President and General Counsel, Amy Agress is responsible for overseeing Innodata's global legal functions, providing counsel to the board and management, ensuring regulatory compliance, and contributing to business strategy from a legal perspective. She has over thirty years of corporate legal expertise, having previously worked as an associate at a general practice law firm in New York City. She earned a Bachelor of Arts in History from New York University and a Juris Doctor from Fordham University School of Law.

The rapid advancement and widespread adoption of generative artificial intelligence (AI) and large language models (LLMs) pose a clear emerging threat. These technologies are increasingly capable of automating data annotation, data generation, and complex data processing tasks, which constitute a significant portion of Innodata's core services. This could significantly reduce the demand for human-in-the-loop data engineering and annotation, either by enabling clients to perform these tasks more efficiently in-house or by shifting market demand towards entirely AI-driven solutions from competitors, thereby disrupting Innodata's traditional service offerings.

Innodata (INOD) primarily operates in the fields of AI data engineering, data annotation, data curation, and providing training data for large language models (LLMs). The addressable markets for its main products and services include:

• The global data annotation and labeling market is projected to reach $3.63 billion in 2025 and is expected to grow at an annual rate of 26.5% through 2035. Another estimate for the global data annotation and labeling market projects it to reach $29.6 billion in 2033.

• The global generative AI market, which encompasses Innodata's AI data engineering and LLM training services, is projected to grow from $37 billion in 2022 to $1.36 trillion by 2032, at a compound annual growth rate (CAGR) of 45%. A subset of this, the generative AI IT-focused services market, which Innodata directly competes in, is expected to grow from $83 million in 2022 to $85 billion in 2032. This market is also cited as having a total addressable market (TAM) opportunity of $200 billion by 2029.

• The global AI-related healthcare market, where Innodata has expanded its AI data annotation capabilities for patient medical records, is projected to reach $62 billion by 2027.

• Innodata has also launched a federal business unit in the U.S. to address an expanding federal AI market, indicating strong market demand within the U.S. government sector.

1. Expansion with Existing Big Tech Clients: Innodata anticipates significant revenue growth from deepening its relationships and expanding its services with existing major technology and AI innovation labs, including its largest customer. The company has already seen substantial growth with its other Big Tech customers and is conducting pilot programs that could lead to seven- or eight-figure revenue opportunities.
2. Acquisition of New Big Tech Clients: Innodata is actively pursuing and is in discussions to secure new Big Tech clients, with at least five new prospective clients identified, including two major players in the commerce, cloud, and AI sectors. A preliminary agreement with one additional tech giant is expected to contribute approximately $6.5 million annually to revenue.
3. Growth in AI Data Preparation Services (Digital Data Solutions Segment): The Digital Data Solutions (DDS) segment, which specializes in AI data preparation services such as collecting, annotating, and training AI algorithms, is a primary driver of revenue. The increasing demand for AI and data-driven solutions, including pre-training data contracts, is expected to fuel this growth. One such investment in pre-training data capabilities has already led to contracts potentially generating $68 million.
4. Launch and Expansion of Innodata Federal: The company recently launched Innodata Federal, a new business unit focused on providing mission-critical AI solutions to U.S. government agencies. This initiative has already secured an initial project with a high-profile customer, projected to generate $25 million, primarily in 2026. This represents a strategic expansion into a new and significant market.
5. Focus on Generative AI and Large Language Models (LLMs): Innodata is strategically positioned as a key beneficiary of the growing market for Artificial Intelligence and Generative AI. The company supports Big Tech firms and enterprises in adopting large language models and other AI technologies at scale, with investments in generative AI services and LLMs expected to drive future revenue growth.

Share Repurchases

No significant dollar amount of share repurchases has been reported by Innodata over the last 3-5 years.

Share Issuance

• Innodata recorded $7.1 million in additional paid-in capital during the first half of 2025, which contributed to a 37% increase in equity.
• The company generated cash from the exercise of stock options, with $0.6 million in 2023, $0.1 million in 2022, $0.2 million in 2021, and $0.1 million in 2020.
• Innodata has a 2021 Equity Compensation Plan authorizing the issuance of up to 4 million shares of common stock for awards, potentially leading to future share dilution.

Inbound Investments

• Innodata entered into a second amendment to its Credit Agreement on August 5, 2024, providing for a secured revolving line of credit of up to $30.0 million. This facility remained undrawn as of December 31, 2024.

Outbound Investments

No significant outbound investments, such as acquisitions or strategic investments in other companies, have been reported by Innodata over the last 3-5 years.

Capital Expenditures

• Capital expenditures for the nine months ended September 30, 2025, totaled $8.286 million, an increase from $5.522 million for the same period in 2024.
• Innodata anticipates approximately $11.0 million in capital expenditures for the next 12 months (from Q3 2025), primarily focused on technology infrastructure and software development.
• The company's capital expenditures were approximately $4.1 million in 2024, $2.7 million in 2023, $2.1 million in 2022, $1.9 million in 2021, and $1.4 million in 2020.