Is Innodata Becoming a Critical Data Partner for Big Tech AI?

Innodata’s INOD rapid evolution from a niche data-services provider to a core infrastructure player in the generative AI ecosystem is increasingly evident in its latest results and strategic disclosures. The company delivered record third-quarter 2025 revenues of $62.6 million, up 20% year over year, alongside strong adjusted EBITDA margins of 26%. Innodata is becoming deeply embedded in the AI supply chains of the world’s largest technology companies.

Management disclosed that six of its eight existing Big Tech customers are expected to grow meaningfully in 2026, with verbal confirmation of a major expansion from the company’s largest customer. Just as importantly, Innodata has landed or is finalizing five additional Big Tech relationships—including two global leaders in commerce, cloud and AI—each positioned to spend heavily on generative AI data, evaluation and safety engineering. This broadening roster signals rising trust in Innodata’s ability to deliver high-quality pretraining and post-training datasets, model-safety frameworks and agentic AI evaluation systems at scale.

The company is also capturing early share in emerging strategic vectors, including sovereign AI programs, federal AI deployment and enterprise generative AI integration—each reinforcing its role as a foundational data partner. Its pretraining data initiatives alone represent roughly $68 million in potential revenue, validating the shift toward higher-value, harder-to-replicate data assets.

With accelerating Big Tech spend, deepening customer entrenchment, and expanding capabilities across the full AI lifecycle, Innodata appears increasingly positioned as a mission-critical data engineering partner powering the next wave of generative AI breakthroughs.

Innodata’s Position Against Competitors in the Big Tech AI Supply Chain

Within the public-company landscape, Cognizant Technology Solutions CTSH and IBM IBM stand out as two of the most frequently cited competitors in AI data services and enterprise AI integration. Cognizant has long provided large-scale digital operations and AI-enabled services, making it a recurring contender in data-rich transformation programs. However, Cognizant often focuses on broad IT modernization rather than the specialized, high-precision data engineering Big Tech now requires—leaving room for Innodata’s deeper expertise.

IBM, meanwhile, has expanded its AI footprint through Watsonx and its consulting division, positioning IBM as a notable rival in AI governance, model evaluation and enterprise deployment. Yet IBM typically emphasizes platform-led transformations, whereas Innodata is gaining traction in high-quality pretraining data, agentic AI evaluation and model safety—segments Big Tech increasingly prioritizes. As IBM and Cognizant continue competing for enterprise AI spend, neither matches Innodata’s growing specialization in frontier-model data pipelines, strengthening its role as a critical partner for Big Tech AI.

INOD’s Price Performance, Valuation & Estimates

Shares of Innodata have gained 48.8% in the past six months against the industry’s decline of 1%.

INOD Six-Month Price Performance

From a valuation standpoint, INOD trades at a forward price-to-earnings ratio of 51.36, much higher than the industry’s average of 16.81.

P/E (F12M)

The Zacks Consensus Estimate for INOD’s 2025 earnings has increased to 86 cents from 78 cents in the past 30 days. 
 

INOD currently sports a Zacks Rank #1 (Strong Buy). You can see the complete list of today’s Zacks #1 Rank stocks here.

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This article originally published on Zacks Investment Research (zacks.com).

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