Innodata Expanded Services for Agentic AI Development
The data company shifted its focus toward supporting the lifecycle of AI agents for enterprise customers.
Updated on Sept. 22, 2026 in Artificial Intelligence
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In the second quarter of 2026, Innodata expanded its service offerings to include agentic artificial intelligence and reinforcement learning development for two major technology customers. This pivot marks a strategic move from providing basic training data to supporting the full agent-deployment cycle.
Why it matters
By moving into agentic evaluation and reinforcement-learning environments, the firm aims to capture higher-value enterprise contracts within the AI infrastructure stack. The transition reflects the industry-wide focus on moving models beyond static responses toward autonomous, long-horizon task completion.
The company reported $92.1 million in second-quarter revenue, representing 58% growth compared to the prior year. Adjusted EBITDA reached $25.4 million, a 92% increase versus the same period in the prior year.
The players
Innodata
A provider of data engineering and AI training services that has expanded its stack to include observability and reinforcement-learning environments for agentic AI.
The details
Innodata utilizes reinforcement learning environments—simulated spaces where an AI learns via trial and error—to test and deploy agents for enterprise workflows. The firm also provides observability platforms to monitor agent performance and dynamic benchmarking to identify model weaknesses. These tools are designed to personalize long-horizon agents—AI systems capable of completing sequences of tasks over extended timeframes—for use in complex environments like desktop computing.
Timeline
Q2 2026: Innodata provided services to two major technology customers.
2026: The company projects at least 40 percent revenue growth.
The Tech Race
This development aligns with the broader industry transition from static model training toward the operational requirements of agentic AI. It positions the company to compete as a specialized provider for enterprise clients building agents capable of long-horizon tasks.
Innodata is currently targeting enterprise clients in the banking and insurance sectors for future pilot programs. These services are not yet available to individual developers or for retail consumer use.
The takeaway
The move signals that the most viable revenue path for legacy data firms is providing the infrastructure to test and debug autonomous agents. Investors should monitor future pilot program announcements with banking and insurance companies to confirm if this strategy scales as projected.
Further reading
For more on the development of autonomous systems, visit Artificial Intelligence.
Source note: This article includes information reported by Quartz.
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