Scentience
"Building the world's largest continuously learning platform for robotic chemical perception."
US startup designing neuromorphic olfactory sensors, edge AI models, and developer APIs to give robots a sense of smell for navigation, security, and.
Scentience, Inc. is a robotics technology startup founded in 2024 and based in the Dallas-Fort Worth area of Texas. The company was founded by Kordel K. France, PhD, an AI architect and roboticist conducting research in machine olfaction at the University of Texas at Dallas. Scentience's stated mission is to build the world's largest continuously learning platform for robotic chemical perception.
The company's hardware flagship is the S1 Olfactory Processing Unit (OPU), a neuromorphic silicon chip designed to perform real-time molecular sensing and computational chemistry. The S1 is packaged to integrate into diverse robotic form factors including humanoids, unmanned aerial vehicles, and mobile service robots. The first-generation S0 OPU has been superseded by the S1. The S1 is available via waitlist.
On the software side, Scentience developed the OVLM (Olfaction-Vision-Language Model), described as the world's first fully unified multimodal model fusing olfactory, visual, and language reasoning. The OVLM runs entirely at the edge using Int8 quantization for embedded deployment and is available on the Apple App Store. A companion OVL-Action Model (OVLAM) is designed specifically for scent-based robot navigation, enabling a robot to localize and track an odor source through a space. Developer access is provided through the Scentience Olfaction APIs, documented at scentience.ai/api-docs. Model weights are published on HuggingFace (scentience-ovlc-v1 joint olfaction-vision-language classifiers).
The Sigma data collection app (iOS, Android in development) captures six time-aligned modalities — olfaction, vision, audio, language, inertial, and environmental data — and feeds ScentNet, the first open multimodal dataset integrating chemical olfaction with vision, depth/LiDAR, audio, language, and inertial data.
Target applications include security robotics (explosives and narcotics detection), search and rescue, UAV olfactory navigation, humanoid robot sensory systems, robotic surgery screening, home air quality monitoring, and VR/XR scene enhancement. The company has published at least five arXiv papers in 2025-2026 covering olfactory inertial odometry, sensor calibration, diffusion graph neural networks for hazard robotics navigation, and simulation-to-real olfactory stacks. Multiple patents are pending on the OVLM technology. The company is bootstrapped with no external funding rounds announced as of mid-2026.
Primary type & automation activities this supplier delivers:
S1 Olfactory Processing Unit
- Model: S1 OPU
- Launch Year: 2024
Neuromorphic silicon chip for real-time molecular sensing and chemical analysis, designed to integrate into humanoids, UAVs, and mobile robots.
OVLM Olfaction-Vision-Language Model
- Model: OVLM
- Launch Year: 2025
World's first unified edge-deployable olfaction-vision-language model enabling interwoven scent, visual, and language reasoning on embedded hardware.
OVL-Action Model
- Model: OVLAM
- Launch Year: 2025
Companion action model enabling scent-based robot navigation and odor source localization for mobile robots and UAVs.
Contact Scentience
WEBSITE
https://scentience.aiHEADQUARTERS
United States
Company Facts
Founded
2024
Primary Role
Manufacturer
Company Size
-
Primary Region
North America
Annual Sales
-
Funding Stage
-
Funding Total
-
Inbolt CEO to Address Physical AI Deployment Challenges at RoboBusiness 2023
Inbolt's CEO Rudy Cohen will present at RoboBusiness on October 20-21, discussing the deployment challenges of physical AI in robotics. He argues that the real bottleneck lies in the integration between perception and motion, rather than data availability. Cohen's insights are based on experiences from over 100 factories and extensive production data from major automotive companies. The significance of this discussion is underscored by Inbolt's innovative approach to robotics, which combines vision and AI to enhance manufacturing processes. By addressing the integration tax and improving real-time control, Inbolt aims to streamline deployments that currently incur high costs and lengthy timelines. Cohen's presentation will challenge prevailing assumptions about the limitations of physical AI. Looking ahead, attendees of RoboBusiness can expect to gain valuable insights into the practical applications of physical AI in manufacturing. Cohen's talk will highlight how existing production data can demonstrate the commercial viability of physical AI, potentially reshaping industry perspectives on its deployment. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Design / Development Events News Inbold
Suoteng Juchuang Advances Digital Laser Radar for Mass Production at IFA
Suoteng Juchuang has unveiled multiple digital laser radars at the IFA, signaling a move towards mass production applications. This development highlights the company's commitment to advancing technology in the field of digital laser radar, which is crucial for various industries. The introduction of these digital laser radars is significant as it reflects the growing demand for advanced sensing technologies in automation and robotics. Suoteng Juchuang's innovations could enhance operational efficiency and accuracy in applications ranging from industrial automation to smart vehicles. Looking ahead, industry stakeholders should monitor Suoteng Juchuang's progress in scaling production and the potential adoption of its digital laser radar technology across different sectors. No further timeline was disclosed at the time of publication.
Robotics Automation AI
China’s Dexterous Hand Industry, 2026 Part 2 — The Technology
Linkage, tendon, direct drive or hybrid — and why hardware is converging while the DL1–DL5 manipulation scale decides who wins. Part 2 of 3.
China’s Dexterous Hand Industry, 2026 Part 1 — The Demand Picture
MIR Databank puts China dexterous hand shipments above 30,000 units in 2026, yet only 3.5% of 2025 demand came from factory production. Part 1 of 3.
Monumental's CEO Discusses Robotics Potential in Construction Industry
In a recent episode of Lexicon, Salar al Khafaji, founder and CEO of Monumental, highlighted the overlooked potential of robotics in the construction industry. He emphasized the challenges of deploying autonomous robots on unpredictable building sites and the need for specialized machines to address rising construction costs and housing shortages. Al Khafaji pointed out that construction has not received the technological attention it deserves, despite its significant economic and social impact. He believes that the industry is vast and underappreciated by tech founders, which is why he pivoted from data visualization to focus on tangible impacts in construction. Monumental has developed autonomous robots capable of transporting materials and constructing brick walls on commercial sites. However, al Khafaji noted that real-world deployment presents unique challenges, such as varying environmental conditions that affect sensors and computer vision systems. No further timeline was disclosed at the time of publication.
AI and Robotics Innovation
Emerging 2D Flex Feeding Revolutionizes Industrial Part Picking with Simplified Vision Systems
The article discusses the advancements in 2D Flex feeding technology, which simplifies robotic vision for industrial part picking. Unlike traditional 3D bin picking, this new approach allows for quicker and more reliable implementations, making it accessible for a broader range of applications. This innovation is significant as it enhances the capabilities of industrial robots in manufacturing, reducing the complexity associated with advanced vision systems. Experts Nicholas Kern from SICK and Nick Barron from Feedall highlight the advantages of flex feeding over bowl feeding, showcasing early adopters who are already experiencing substantial benefits. Looking ahead, the future of feeding robots appears promising with the integration of smarter vision systems. As this technology continues to evolve, it will be essential to monitor its adoption and impact on manufacturing efficiency and productivity. No further timeline was disclosed at the time of publication.
Factory / Robotics
Dyson Introduces Nurovi Robot Cleaners and First Oral-Care Device with AI Vision
Dyson has unveiled a new family of robot cleaners named Nurovi and its first oral-care device, CameraJet, at the Dyson Unveiled event in Berlin. This marks a significant shift towards appliances that utilize artificial intelligence, vision systems, and sensor-based automation to interpret and respond to their environments. The introduction of the Nurovi robot cleaners, which includes three models with advanced cleaning mechanisms, highlights Dyson's commitment to moving beyond traditional mechanical performance. The r2 Nurovi Wash+Dry features a triangular rotating mop and real-time dust particle measurement, while the r3 Nurovi Spot+Scrub UV employs AI for stain detection and enhanced suction capabilities. Looking ahead, Dyson aims to integrate AI and machine learning across its product lines, including oral care and home appliances. No further timeline was disclosed at the time of publication.
All News
Lyte Secures $165 Million in Series C Funding to Enhance Robot Sensing Capabilities
Lyte AI Inc. has successfully raised $165 million in Series C funding, achieving a post-money valuation of $1.6 billion. Founded in 2021, the Sunnyvale-based company specializes in designing processors, multimodal sensors, and software that enable robots to accurately perceive their surroundings. This funding will accelerate the deployment of LyteVision, their perception platform, into various robotics applications. The significance of this funding round lies in Lyte's innovative approach to solving the sensing challenges faced by robots. According to co-founder and CEO Alexander Shpunt, the company focuses on creating a comprehensive perception foundation, from custom silicon to spatial data generation. With this investment, Lyte aims to expand its reach across industries such as inspection, logistics, and manufacturing, where accurate sensing is crucial for operational safety and efficiency. Looking ahead, Lyte plans to significantly grow its workforce, hiring across multiple domains including silicon, software, and operations. The company has already raised a total of $272 million since its inception and is poised to become a key player in the robotics sector, as indicated by the strong demand for its technology from early customers. No further timeline was disclosed at the time of publication.
Artificial Intelligence Artificial Intelligence / Cognition Design / Development Financial Investments News
World Labs Launches Atlas World Model for 3D Environment Simulation
World Labs has unveiled Atlas, a new world model aimed at generating, reconstructing, and simulating 3D environments. This model supports Real-to-Sim workflows, allowing robots to navigate and manipulate spaces reconstructed from images or videos. Atlas can create RGB and depth data that robots would encounter, enhancing their operational capabilities. The introduction of Atlas is significant as it enables developers to recreate interactions with various objects and simulate different training scenarios. By using a limited number of real-world recordings, Atlas can generate complex environments, which is crucial for advancing robotic applications. This multimodal model combines text, images, video, and 3D information, providing a comprehensive tool for robotics and beyond. Looking ahead, Atlas is entering early access with select partners and will also enhance future versions of World Labs' Marble world-generation product. The capabilities of Atlas in producing explicit 3D outputs and supporting diverse applications will be key areas to monitor as the technology evolves.
AI AI Use Cases Robotics Atlas real-to-sim World Labs
Leading Research Institutions Unite to Advance Soft Robotics and Physical AI
In recent years, advancements in large models have enhanced machines' language, visual, and reasoning capabilities. Concurrently, robotics is transitioning from traditional rigid systems to more flexible, perceptive forms. A significant intersection is emerging between Physical AI and Soft Robotics, prompting a shift in focus towards integrating materials, structures, mechanics, and perception systems into robotic intelligence. In 2026, the prestigious journal ACS Nano will publish a collaborative article by 37 scientists from 28 global research institutions, including Nanyang Technological University, Hebrew University of Jerusalem, MIT, ETH Zurich, Tsinghua University, Cornell University, and Northwestern University. The article, titled "Emerging Frontiers and Technological Challenges in Soft Robotics," will explore the paradigm shift in soft robotics and outline key scientific questions and technological challenges for the future. This article not only serves as a roadmap for soft robotics technology but also points towards a broader future of Embodied Physical Intelligence, where the body itself becomes part of the intelligence. The research framework connects fundamental scientific questions with cutting-edge studies in soft robotics, focusing on issues related to intelligence, perception, functionality, and adaptability, which are crucial for overcoming key technical challenges in deployment and integration.
Soft Robotics Physical AI Adaptive Systems Machine Learning Biomimicry
Ouster Expands into Drone Mapping and Autonomous Vehicles with Physical AI Technology
Ouster is advancing its technology that enables machines to perceive and navigate their environments, contributing to the growth of physical AI. The company is entering the drone mapping sector through a collaboration with GeoCue, while John Deere is integrating Ouster sensors into its GUSS autonomous vehicles. This expansion is significant as it highlights the increasing demand for physical AI solutions across various industries. Ouster's CEO, Angus Pacala, emphasized the company's commitment to exploring new markets and addressing the evolving needs for advanced sensing technologies in automation. Looking ahead, industry stakeholders should monitor Ouster's developments in drone mapping and its partnership with John Deere. No further timeline was disclosed at the time of publication.
Lyte Secures $165 Million Series C Funding Led by Maverick Silicon for Robot Perception
Lyte has announced a successful $165 million Series C funding round, led by Maverick Silicon. This financing values the company at $1.6 billion post-money and marks a significant step as Lyte prepares for production deployments. The funding is crucial for Lyte, a company specializing in physical AI perception, as it aims to enhance robots' understanding of their environments. With this investment, Lyte is positioned to advance its technology and expand its market presence, which is vital in the rapidly evolving robotics sector. Looking ahead, Andrew Homan from Maverick Silicon will join Lyte's board, indicating a strategic partnership that could influence future developments. No further timeline was disclosed at the time of publication.
ROBOTTODAY WEEKLY BRIEFING August 24 – 28, 2026
This week in robotics: XPeng's Dogotix raises over $900 million at a $6.3 billion valuation, Unitree's post-IPO slump revives bubble talk, Beijing's World Humanoid Robot Games close with a shift to real-world tasks, and Teradyne sues JAKA at Europe's Unified Patent Court. August 24–28, 2026.
WRC 2026 Core Components: 137 Robot Parts Suppliers
The third report in the WRC 2026 series. Report 1 mapped all 248 exhibitors by category and Report 2 covered the 139 that build finished robots. This one covers the 137 that build what goes inside them.
How a Robot Should Die: Phase 5, Lifecycle KPIs, and One Welding Arm's Four Years
When is a robot's time up? RSF's four-dimension scoring matrix, Data Erasure Certificates, hazmat compliance, and five KPIs that measure the lifecycle.
US Restrictions on Chinese Humanoid Robots: The Full Map
Every US restriction on Chinese humanoid robots — NDAA Sec. 163, GUARD Act, the 1260H list — plus the supply-chain math and a 4-tier map of decoupling.
The Most Important AI at WAIC Wasn't a Robot
At WAIC 2026, AI-native platforms quietly replaced interpreter hardware — what invisible AI infrastructure means for robotics and embodied AI.
Inside Guident: How Harald Braun Is Building the Safety Layer Every Autonomous Vehicle Needs
Guident CEO Harald Braun on the RMCC architecture, IRLS risk identification system, and why California’s 2026 AV mandates validate six years of platform development.
Supply Chain Reckoning: Can Boston Dynamics Avoid Becoming the Next iRobot?
A data-driven analysis comparing Boston Dynamics Atlas and Tesla Optimus supply chain strategies in 2026. Examines actuator costs, production ramp speeds, and how Boston Dynamics can avoid iRobot's bankruptcy by adopting a tiered supply chain approach. Includes component cost tables, risk heat maps, and strategic frameworks.
EXCLUSIVE INTERVIEW with DFRobot Founder Ricky Ye
Exclusive interview with DFRobot Founder & CEO Ricky Ye on lowering barriers in AI and robotics, the evolution of HUSKYLENS, open-source hardware, and the future of embodied AI.
