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Innodata INOD shares are trading at a premium valuation, as suggested by its Value Score of F. In terms of the 12-month price/sales (P/S), INOD is currently trading at 5.01X, higher than its median of 3.41X and the Zacks Computer – Services industry’s 1.92X.
INOD’s premium valuation is justified by its strong growth prospects and strategic positioning in the generative AI (GenAI) space. By focusing on Big Tech’s increasing investments in GenAI, Innodata has positioned itself as a key partner for data engineering, particularly in creating supervised fine-tuning data for training advanced AI models.
Morgan Stanley has projected combined capital expenditures of $300 billion in 2025 and $337 billion in 2026 for Amazon AMZN, Alphabet GOOGL, Meta Platforms META and Microsoft on GenAI and large language model (LLM) enabled advancements.
Price/Sales Ratio (F12M)
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This projected spending reflects a long-term focus on GenAI opportunities. Amazon, the top spender, is focusing on hyperscaler initiatives while leveraging its high-margin businesses for profitability.
Alphabet’s efforts center on AI-driven innovations in Search, YouTube and other platforms, boosting engagement and growth. Meta is emphasizing efficiency and improved monetization, particularly via Reels on Instagram.
Microsoft is heavily investing in public cloud adoption and AI, with expectations of strong commercial business growth in the coming years. It is rapidly gaining market share in e-commerce and retail, as well as increasing its share of consumer spending.
The surging capital expenditures by Big Tech on GenAI are providing a significant growth opportunity for Innodata. It is well-positioned to meet the growing demand for high-quality AI training data and drive its top-line growth.
Consequently, INOD shares have skyrocketed 291.8% in the trailing 12-month period, outperforming the Zacks Computer and Technology sector’s appreciation of 28.9% and the industry’s return of 10.5%.
One-Year Performance
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Innovative Portfolio & Expanding Footprint Aid INOD
INOD is capitalizing on its expertise in instruction-tuning data and Reinforcement Learning from Human Feedback (RLHF). With increasing concerns over intellectual property (IP) issues and the risks of “model collapse” from web-scraped data, INOD’s focus on creating proprietary, high-quality, supervised fine-tuning data is providing it a distinct competitive edge.
INOD’s cutting-edge Agility platform, designed for specialized workflows involving generative AI, has been experiencing growing demand in the market.