Invisible AI measures manual assembly with its own cameras, Roboflow builds any vision task on any camera

Invisible AI sells an on-premises vision system for manual assembly lines. Each station gets an Invisible AI edge device, which pairs an Intel RealSense 3D camera with an NVIDIA Orin NX chip and up to 4 TB of storage, and the software tracks operator motion to capture cycle-level data on every station: cycle times, process drift, and ergonomic risk. Industrial engineers use it in place of stopwatch time studies, and apps such as Assembly Monitor, Ergo Monitor, and Robot Safety are sold by subscription.

Manufacturers that need vision beyond operator motion often choose Roboflow. Their engineers use the industrial, GigE, or RTSP cameras already on the line, label their own images with AI assistance through Auto Label, and train a specialized model such as RF-DETR for defect detection, assembly verification, cycle time monitoring, OCR, or safety. Models deploy to a Jetson, an air-gapped server, or the Roboflow AI1 device with PLC triggers built into Workflows, and Vision Events logs every prediction and image from every camera into one searchable dashboard across lines and plants.

Each trained model is exposed over MCP as a vision sub-agent, so agents can call it whenever they need to see the line precisely. Manufacturers pick Roboflow because one platform covers every camera and every use case in the plant, and they own the models they train.

Invisible AI vs Roboflow: feature by feature

Both can run vision AI on the factory floor with no cloud dependency. The difference is whether the cameras, the models, and the use cases are yours to choose.