We use cookies to understand how you use our site and to improve your experience.
This includes personalizing content and advertising.
By pressing "Accept All" or closing out of this banner, you consent to the use of all cookies and similar technologies and the sharing of information they collect with third parties.
You can reject marketing cookies by pressing "Deny Optional," but we still use essential, performance, and functional cookies.
In addition, whether you "Accept All," Deny Optional," click the X or otherwise continue to use the site, you accept our Privacy Policy and Terms of Service, revised from time to time.
You are being directed to ZacksTrade, a division of LBMZ Securities and licensed broker-dealer. ZacksTrade and Zacks.com are separate companies. The web link between the two companies is not a solicitation or offer to invest in a particular security or type of security. ZacksTrade does not endorse or adopt any particular investment strategy, any analyst opinion/rating/report or any approach to evaluating individual securities.
If you wish to go to ZacksTrade, click OK. If you do not, click Cancel.
Innodata Bets on Agentic AI: Is it the Next Revenue Wave?
Read MoreHide Full Article
Key Takeaways
Innodata is monetizing Agentic AI with judge systems for evaluating and refining autonomous agents.
Recent work with Palantir highlights INOD's role in complex AI deployments using multimodal data.
INOD expects more than 45% revenue growth in 2025, supported by strong margins and recurring AI services.
Innodata Inc. (INOD - Free Report) is increasingly positioning itself at the center of Agentic AI, a fast-emerging layer of generative AI where autonomous agents perform multi-step tasks with limited human intervention. Management’s third-quarter 2025 update suggests this shift is not theoretical—it is already translating into commercial opportunities tied to evaluation, refinement and safety of agentic systems.
Unlike basic model training, Agentic AI introduces new complexity — agents must be tested for task success, behavioral consistency, decision logic and failure modes. Innodata has built specialized “judge” frameworks—task-success, diagnostic and profiling judges—that help big-tech model builders evaluate and fine-tune autonomous agents operating in real-world workflows. These capabilities are increasingly embedded in reinforcement learning pipelines, making them recurring rather than one-off services.
The revenue potential lies in depth, not breadth. Agentic systems demand continuous iteration, monitoring and retraining, expanding the lifetime value of customer engagements. Management noted that Agentic AI work often builds on existing relationships with hyperscalers and frontier model developers, allowing Innodata to layer higher-value services on top of its core data-engineering base.
Recent wins reinforce this trajectory. In January 2026, Innodata was selected by Palantir (PLTR - Free Report) to support advanced AI deployments involving complex multimodal data—an example of agent-like systems operating in high-stakes environments where precision and reliability are critical.
Financially, Innodata enters this phase from a position of strength, with expanding margins, strong cash generation and guidance for more than 45% growth in 2025. If Agentic AI adoption accelerates as enterprises move from pilots to production, Innodata’s early investments could unlock a durable next wave of revenue rather than a short-cycle AI spike.
INOD’s Competitive Landscape in Agentic AI
In the emerging Agentic AI arena, two peers that investors are watching alongside Innodata are Upstart Holdings (UPST - Free Report) and C3.ai (AI - Free Report) . Both companies are carving differentiated paths in AI that touch aspects of autonomy, evaluation, and enterprise deployment.
Upstart isn’t a traditional data-engineering firm, but its AI-driven credit decisioning platforms rely on advanced autonomous models that continuously iterate on consumer risk predictions. Upstart’s focus on automated decision frameworks parallels Innodata’s “judge” systems for agent evaluation, underscoring how autonomous logic layers are monetized in vertical applications. Investors should watch Upstart’s expansion into new loan products as a barometer for broader agentic value creation.
C3.ai, by contrast, offers a comprehensive enterprise AI platform that includes model deployment, monitoring, and governance—core elements of scaling agentic systems in production. C3.ai’s push into autonomous predictive maintenance and real-time optimization mirrors the operational dimensions where Innodata’s services may intersect or compete. While each plays in adjacent segments of the agentic ecosystem, both Upstart and C3.ai highlight the competitive pressures and total addressable market that Innodata aims to capture with its specialized AI data services.
INOD’s Price Performance, Valuation & Estimates
Shares of Innodata have gained 23.1% in the past six months, outperforming the Zacks Technology Services industry’s 3.9% growth.
INOD 6-Month Price Performance
Image Source: Zacks Investment Research
From a valuation standpoint, INOD trades at a forward price-to-earnings ratio of 45.86, much higher than the industry’s average of 23.64.
P/E (F12M)
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for INOD’s 2026 earnings has remained unchanged at $1.20 in the past 60 days. The company is expected to report 89 cents per share in 2025.
Image: Bigstock
Innodata Bets on Agentic AI: Is it the Next Revenue Wave?
Key Takeaways
Innodata Inc. (INOD - Free Report) is increasingly positioning itself at the center of Agentic AI, a fast-emerging layer of generative AI where autonomous agents perform multi-step tasks with limited human intervention. Management’s third-quarter 2025 update suggests this shift is not theoretical—it is already translating into commercial opportunities tied to evaluation, refinement and safety of agentic systems.
Unlike basic model training, Agentic AI introduces new complexity — agents must be tested for task success, behavioral consistency, decision logic and failure modes. Innodata has built specialized “judge” frameworks—task-success, diagnostic and profiling judges—that help big-tech model builders evaluate and fine-tune autonomous agents operating in real-world workflows. These capabilities are increasingly embedded in reinforcement learning pipelines, making them recurring rather than one-off services.
The revenue potential lies in depth, not breadth. Agentic systems demand continuous iteration, monitoring and retraining, expanding the lifetime value of customer engagements. Management noted that Agentic AI work often builds on existing relationships with hyperscalers and frontier model developers, allowing Innodata to layer higher-value services on top of its core data-engineering base.
Recent wins reinforce this trajectory. In January 2026, Innodata was selected by Palantir (PLTR - Free Report) to support advanced AI deployments involving complex multimodal data—an example of agent-like systems operating in high-stakes environments where precision and reliability are critical.
Financially, Innodata enters this phase from a position of strength, with expanding margins, strong cash generation and guidance for more than 45% growth in 2025. If Agentic AI adoption accelerates as enterprises move from pilots to production, Innodata’s early investments could unlock a durable next wave of revenue rather than a short-cycle AI spike.
INOD’s Competitive Landscape in Agentic AI
In the emerging Agentic AI arena, two peers that investors are watching alongside Innodata are Upstart Holdings (UPST - Free Report) and C3.ai (AI - Free Report) . Both companies are carving differentiated paths in AI that touch aspects of autonomy, evaluation, and enterprise deployment.
Upstart isn’t a traditional data-engineering firm, but its AI-driven credit decisioning platforms rely on advanced autonomous models that continuously iterate on consumer risk predictions. Upstart’s focus on automated decision frameworks parallels Innodata’s “judge” systems for agent evaluation, underscoring how autonomous logic layers are monetized in vertical applications. Investors should watch Upstart’s expansion into new loan products as a barometer for broader agentic value creation.
C3.ai, by contrast, offers a comprehensive enterprise AI platform that includes model deployment, monitoring, and governance—core elements of scaling agentic systems in production. C3.ai’s push into autonomous predictive maintenance and real-time optimization mirrors the operational dimensions where Innodata’s services may intersect or compete. While each plays in adjacent segments of the agentic ecosystem, both Upstart and C3.ai highlight the competitive pressures and total addressable market that Innodata aims to capture with its specialized AI data services.
INOD’s Price Performance, Valuation & Estimates
Shares of Innodata have gained 23.1% in the past six months, outperforming the Zacks Technology Services industry’s 3.9% growth.
INOD 6-Month Price Performance
Image Source: Zacks Investment Research
From a valuation standpoint, INOD trades at a forward price-to-earnings ratio of 45.86, much higher than the industry’s average of 23.64.
P/E (F12M)
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for INOD’s 2026 earnings has remained unchanged at $1.20 in the past 60 days. The company is expected to report 89 cents per share in 2025.
Image Source: Zacks Investment Research
INOD currently carries a Zacks Rank #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.