AI Index / Innodata Inc.
Innodata Inc. (INOD)
Main revenue sources: (1) Generative AI data engineering for LLMs (pretraining/post‑training datasets, evaluation, long‑context data) – AI directly drives this. (2) Agentic AI lifecycle services (agent evaluation/observability platform, optimization pipelines, adversarial simulation/guardrails) – direct AI. (3) Physical AI/robotics data systems (egocentric/affordance datasets, world models; drone/small-object perception) – direct AI. (4) Managed services for hyperscalers, Mag 7, sovereign AI, enterprises; expanding trust & safety – direct AI. Revenue is predominantly AI‑linked and growing via diversification beyond the largest customer.
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We are seeing robust demand across the entire generative AI life cycle, spanning development, evaluation and ongoing model optimization. And we believe we are gaining traction with a broad and diversified number of large customers.
- Jack Abuhoff
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Quotes from innodata Executives About Artificial Intelligence and Generative AI
Every innovation I am about to discuss is fundamentally a data innovation. Whether the goal is more capable LLMs, more reliable autonomous agents or more intelligent physical AI systems, data quality, data composition, data validation and data engineering at scale are at the heart of the matter.
- Jack Abuhoff
We believe that autonomous agents may represent the most significant business innovation opportunity since the advent of electricity.
- Jack Abuhoff
Our customers are moving fast, driving shorter development cycles and responding faster to research breakthroughs.
- Jack Abuhoff
Historically, customers told us the kind of training data they wanted. Increasingly, however, they are asking us to diagnose model performance, design the right training data sets and demonstrate that those data sets will materially improve outcomes.
- Jack Abuhoff
We're pleased to share that we anticipate soon kicking off a managed services engagement with a hyperscaler in which we will use our platform to create test data at scale, perform automated evaluations and identify critical model vulnerabilities in order to improve performance of its customer-facing intelligent virtual assistant.
- Jack Abuhoff
We believe our system generates realistic adversarial attacks at scale in a meaningful way that exceeds existing alternatives.
- Jack Abuhoff
Our work is garnering interest from CISOs and security leaders at some of the world's premier AI and cybersecurity companies as well as relevant experts in government.
- Jack Abuhoff
Finally, we recently developed an AI model for drone and other small object detection that exceeds prior state-of-the-art benchmarks by 6.45%.
- Jack Abuhoff
We believe 2026 will also mark the acceleration of physical AI, intelligent systems that perceive and interact with the physical world.
- Jack Abuhoff