Build AI Agents for Visual Inspection in Manufacturing

Build an AI agent for visual inspection by connecting defect detection, object tracking, visual reasoning, and review actions in Roboflow Workflows. Use RF-DETR to detect damage and Gemini to assess it, then send operators a structured report with image evidence to guide their next step. Visual inspection in manufacturing involves more than finding a defect. Teams also need to identify the impacted item, understand the damage, save image evidence, and decide what to do next. An AI agent for visual inspection connects a defect detector with a reasoning model and workflow logic to handle these steps. The detector finds visible defects, while a vision-language model examines the image and produces a structured assessment. The workflow can then notify an operator, submit a review ticket, or pass the result to another system. This is useful when detecting damage is only the first part of the quality-control process. A vision agent can also become part of a physical AI system when its outputs connect to equipment that acts in the real world. For example, a PLC could use an inspection signal to divert a damaged carton, subject to the machine’s control logic and safety checks. In this guide, we will use Roboflow…