Invisible AI

Invisible AI offers a cutting-edge manufacturing vision platform designed to improve worker productivity and safety through the use of advanced AI technology. The platform employs AI vision sensors to analyze human motion and objects on the factory floor in real time, leveraging NVIDIA-powered AI chipsets and synchronized depth-sensing cameras. This system provides on-premise data management and storage, capable of holding up to 3 months and 2TB of data per device, ensuring data security and real-time feedback without the need for cloud access. The platform integrates workforce movement data with PLC/MES datasets, offering a comprehensive view of plant floor activities. Key features include ergonomics monitoring, forklift tracking, and incident root-cause analysis, all aimed at protecting the workforce. Additionally, the AI-powered root-cause analysis utilizes 3D video capture for enhanced product traceability. Invisible AI’s edge devices are powered over ethernet, requiring minimal infrastructure investment, and the software application is available in English, Spanish, and German. The system integrates seamlessly with MES systems, PLC controllers, torque guns, and other third-party systems, tracking 17 human body joints in 3D for ergonomics monitoring. Customizable safety reports and real-time or recorded video audits are also provided. Invisible AI has raised $15 million in Series A funding, bringing the total amount raised to $21 million, and partners with Toyota Motor North America and prominent aerospace OEMs and suppliers to enhance factory efficiency and worker safety. The platform supports high-mix lines and both fixed and moving assembly operations, offering solutions for safety, quality, production management, and continuous improvement. It also provides a digital twin of the plant for streamlined continuous improvement and new product line planning. Ensuring data security, Invisible AI employs robust encryption measures and conducts regular vulnerability assessments and penetration testing.