Simplify AI for inspection

A hybrid "no code" approach to artificial intelligence allows organizations to easily deploy machine learning to improve the reliability and lower the cost of inspection, without time-consuming algorithm development or replacing infrastructure and processes.

AI algorithm training traditionally requires multiple time-consuming steps and dedicated coding to input images, label defects, fine-tune detection and optimize models. A "no code" approach allows users to upload images and data captured during traditional inspection to software that automatically generates plug-in AI skills with minimal human input.

Pleora's AI Gateway integrates plug-in skills for machine learning classification, sorting, detecting and hyperspectral capabilities, with powerful processing to accelerate the deployment of customized algorithms. AI for inspection excels at locating, identifying and classifying objects and segmenting scenes and defects, with less sensitivity to image variability or distortion. AI algorithms are also more easily adapted to identify different types of defects or meet unique pass/fail tolerances based on requirements for different customers without rewriting code.

From an infrastructure perspective, AI capabilities can be integrated into existing applications without changing hardware or software. In an inspection application, an AI Gateway intercepts the camera image feed and applies the selected plug-in AI skills. Users can also develop AI skills for custom requirements that are uploaded to the gateway. The gateway sends the AI processed data over a GigE Vision connection to the inspection and analysis application, which seamlessly receives the video as if it were still connected directly to the camera.