Ainos CEO Outlines Long-Term Strategy to Digitize Smell
Ainos released a statement from CEO Eddy Tsai, outlining the Company's long-term platform strategy to digitize smell as a native data language for artificial intelligence, its execution priorities for 2026, and the complementary roles of Ainos and its wholly owned AI software subsidiary, ScentAI, within the SmellTech platform - AI Nose. The company said, "Ainos is executing a disciplined, long-term strategy to transform smell from a sensory signal into a structured data language that artificial intelligence systems can understand, learn from, and scale. While AI has successfully converted text, images, and sound into computable tokens, smell remains one of the last major human senses not yet systematically digitized. We believe this represents a structurally significant opportunity in the evolution of AI. AI Nose, our SmellTech platform, is designed as a layered and tightly integrated architecture to support scalability, data consistency, and long-term platform durability. Ainos is operating at the edge of the physical world, designing, manufacturing, and deploying its AI Nose sensing hardware. Ainos maintains control over sensor design, firmware, calibration, manufacturing processes, quality assurance, and global certifications to ensure that scent data generated across deployments is reliable, repeatable, and suitable for large-scale AI training. Ainos is adopting a dual-engine platform architecture based on long-term design considerations rather than organizational or short-term operational factors. Ainos believes that combining sensing, data generation, and AI intelligence within a single operating structure could constrain scalability and long-term value creation. By separating the sensing layer from the intelligence layer, the platform is designed to preserve strategic flexibility, governance clarity, and scalability as deployments expand. Within the SmellTech platform, Ainos focuses exclusively on sensing hardware, physical deployment, and data generation, while ScentAI focuses on AI models, data abstraction, and intelligence delivery. The two entities will not compete at the product or customer level. Instead, they will operate as complementary layers within a unified platform architecture, reducing role ambiguity and long-term operational friction. ScentAI is positioned to develop the Smell Language Model, the core AI system of the SmellTech platform. SLM is designed to classify, contextualize, and enable cross-environment learning of scent data in a structured, trainable format. Through SLM, we expect scent to become an AI-native data asset that can be scaled and monetized through enterprise APIs, SaaS offerings, and model licensing, while Ainos retains ownership of its core datasets and AI models. In 2026, Ainos is committed to driving scaled deployment, with an initial focus on advanced semiconductor manufacturing and robotic applications. These environments demand high sensing precision, reliability, and continuous data generation, making them well-suited for accelerating data accumulation and AI model training. We view these applications as a strong starting point in our expansion to the industrial market, with the AI Nose platform positioned to extend well beyond these initial markets as deployment scales."
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Purpose of Stock Splits: Stock splits increase the number of shares while maintaining market value, making stocks more affordable, whereas reverse splits reduce share count to meet exchange requirements and avoid delisting.
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Technological Advancements: The AI Nose technology will enable real-time monitoring of airborne chemicals, predictive maintenance, and improved manufacturing precision, ultimately contributing to smarter and more sustainable factory operations.
