Ainos (NASDAQ:AIMD) is positioning its AI Nose technology as a new data layer for artificial intelligence by digitizing scent and converting chemical signals in the air into machine-readable information, Head of Corporate Development Jack Lu said during a company presentation.
Lu said the company’s core thesis is that AI systems can already process text, images and audio, but still lack the ability to interpret chemical information from physical environments. Ainos is seeking to address that gap through what it calls “smell AI,” using hardware, data and AI models to identify scent patterns and apply them in industrial and healthcare settings.
Ainos Targets Scent as an AI Data Layer
Lu compared the company’s opportunity to the development of computer vision, arguing that cameras existed for decades before digitized images enabled AI systems to learn from visual data. He said scent may be approaching a similar transition, as many early signals of problems appear in the air before they are visible or detectable by other systems.
Examples cited in the presentation included equipment failures, gas leaks, overheating cables, environmental changes and health-related signals. During a question-and-answer session, Lu pointed to an incident at Newark Airport in which personnel reportedly detected a burning smell in a control tower before the underlying issue was identified as overheated cables.
Ainos’ AI Nose system is designed to capture scent signals through hardware, convert those signals into what the company calls “Smell ID” data, feed that data into a “smell language model,” and deploy the resulting intelligence in real-world environments.
Lu said the company views scent data as difficult to replicate because it cannot be scraped from the internet in the same way as text, images or video. Instead, he said, scent data must be collected from physical deployments, which Ainos believes could create a competitive data advantage over time.
AI Nose Designed for Industrial Environments
According to Lu, the AI Nose device combines multi-sensor detection, cloud connectivity and AI analytics in a compact system roughly the size of a smartphone. The system uses sensor chips from outside companies, which Lu described as ecosystem partners, while Ainos focuses on integration, calibration, signal processing, scent digitization and AI interpretation.
The company said the platform is engineered for clean, controlled and continuous sensing, with attention to temperature, humidity, airflow and environmental stability. Lu said that in many applications the system can detect compounds at parts-per-billion levels, potentially enabling early identification of subtle environmental changes.
Ainos aims to place multiple AI Nose systems throughout a facility to create what Lu called a “smell map,” helping customers detect and locate potential problems earlier. He also said the platform is trainable, allowing customers to teach it new scent patterns and environmental conditions.
Semiconductor Manufacturing Seen as First Major Market
Lu said semiconductor manufacturing is Ainos’ first major industrial commercialization focus because chip factories use hundreds of specialty chemicals and gases and operate continuously. He said small changes in those environments can have meaningful operational consequences, and chipmakers already invest heavily in monitoring and process control.
The company has secured its first commercial order from what Lu described as one of the world’s leading semiconductor packaging and testing companies. He said the initial phase includes roughly 1,400 AI Nose systems under a three-year subscription structure, with a multi-phase deployment roadmap that could potentially scale beyond the initial rollout.
Lu described the deployment as recurring in nature, with each unit generating revenue while also expanding the company’s data footprint. He said Ainos is also building an ecosystem of partners in Asia, which he said accounts for roughly 70% of global semiconductor manufacturing capacity.
Partners mentioned in the presentation included Topco, which Lu said helps expand commercial reach through customer relationships and industry networks, and Truthful, which he said supports access within front-end fab infrastructure environments and assists with validation and deployment efforts.
Healthcare Infrastructure and Robotics Also in Focus
Ainos’ technology originated in healthcare and medical device applications, Lu said, with the company spending roughly 13 years developing AI Nose technology in environments where accuracy, reliability and validation are important. That work, he said, helped create the foundation for the company’s Smell ID datasets and smell language model.
The company is now applying the same platform in healthcare infrastructure programs with two leading Taiwanese medical centers. Lu said those deployments are intended to support hospital infrastructure and critical facility operations and are expected to generate more than 2,500 hours of environmental scent data for model improvement. He emphasized that the platform collects no images, audio or personal information.
In the Q&A session, Lu also said Ainos has projects with robotics customers in Asia to add scent detection capabilities to robotic platforms. He said robots may eventually use smell as an additional sensor input, similar to how humans can detect smoke or gas before seeing the source.
Company Frames Opportunity Around Data and Infrastructure
Lu said Ainos sees value across three layers: hardware, AI software and proprietary scent data. While all three are important, he said the data layer becomes increasingly significant over time because scent data must be gathered directly from real-world environments.
“The hardware really is the gateway for the signals to enter the digital world,” Lu said. “The software creates the intelligence.”
Lu said 2026 marks the beginning of commercialization for Ainos through chip manufacturing deployments, partner expansion and healthcare infrastructure programs. He framed the company’s goal as building “the smell infrastructure for physical AI,” with revenue and platform value growing as deployments expand.
Asked about the eventual size of a “smell data economy,” Lu said it is too early to assign a specific number but compared the potential trajectory to computer vision. He said the company is focused on building the infrastructure and datasets that could make digitized scent a foundation for new AI applications.
About Ainos (NASDAQ:AIMD)
Ainos, Inc (NASDAQ: AIMD) is a clinical‐stage biopharmaceutical company dedicated to developing inhalation therapies for patients with chronic pulmonary disorders. The company’s proprietary platform centers on a dry powder inhalation technology designed to deliver therapeutic agents directly to the lungs, potentially improving drug distribution and reducing systemic side effects compared to traditional oral or intravenous formulations.
The lead product candidate, AI‐401, is an inhaled formulation of ibuprofen in a dry powder format.
