In the wave of artificial intelligence, Palantir (PLTR) has demonstrated the core traits of a successful enterprise-level AI company: it not only serves as a foundational platform for clients to build AI applications but also efficiently converts pilot projects into large-scale deployments, continuously cross-sells to existing clients while expanding into new business areas, and actively explores opportunities across industries and new verticals. In contrast, Innodata (INOD), though smaller in scale, exhibits a similar growth trajectory. The company is transitioning from traditional data services to focus on the data and evaluation layer within enterprise AI architecture—an area Palantir has yet to deeply penetrate.
From a financial performance perspective, Palantir achieved a 48% year-over-year revenue growth in the second quarter of fiscal year 2025, surpassing $1 billion, with U.S. commercial and government revenues surging by 93% and 53%, respectively. Its “Rule of 40” score jumped to 94, indicating a robust business model efficiency. Innodata also delivered impressive results, with revenue growing 79% to $58.4 million during the same period, and adjusted EBITDA increasing by 375%. Management further raised its full-year growth expectation to over 45%, reflecting strong project pipelines and deep collaborations with major clients.
Palantir’s uniqueness lies in its approach of not relying on large language models but instead using an ontological framework to connect physical and digital assets, thereby enhancing AI’s contextual understanding and practical problem-solving capabilities. Innodata adopts a similar strategy, shifting toward providing “intelligent data”—high-quality, complexly structured training data designed to improve the accuracy, security, and reasoning abilities of clients’ AI models. The company also collaborates with large tech firms on model testing and optimization, gradually embedding itself into client ecosystems to enhance customer stickiness and pricing power.
In terms of business expansion, Palantir drives growth through high-value clients, securing numerous contracts worth millions and tens of millions of dollars. Innodata, while improving profitability, is actively expanding its revenue base. It has won multiple new projects from its largest client and expects annual revenue from one major client to jump from $200,000 to $10 million. Its adjusted EBITDA margin has also improved from 9% to 23%.
In the realm of agentic AI, Palantir leverages Functional Discourse Engineering (FDE) within its AIP platform to drive autonomous task execution and system evolution. Innodata is also committed to helping enterprises build AI systems capable of autonomous action, providing simulated training data and security monitoring services. The company plans to increase its investments in data and evaluation for agentic AI and robotics, targeting broader future markets.
Palantir’s price-to-earnings ratio of approximately 114 reflects market recognition of its industry leadership. For Innodata to achieve a similarly high valuation, it must continue to expand its client base, deepen existing customer relationships, enhance the indispensability of its products, and establish a dominant position in the AI performance market. Despite facing significant execution risks, Innodata has the potential to become the next Palantir by the 2030s.
