Neurala Vision Inspection Automation (VIA) software brings new technology to visual inspection

Our patented Lifelong-Deep Neural Network© (L-DNN) has significant advantages over machine vision and traditional DNN technology.

Neurala VIA for visual quality inspection

Neurala VIA software consists of two modules, Brain Builder and Inspector. It can be installed on any computer with a NVIDIA GPU or an Intel i7 Processor. Brain Builder enables creation of AI models, walking users (including those with little or no prior AI expertise required) through the steps to build a well-performing model. Once a model has been created in Brain Builder, Inspector integrates that model into the production line, connecting to any GigE camera and outputting the image analysis directly on industrial networks.

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Advantages of Lifelong-DNN vs. Traditional DNN

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Less Data Required

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Instantaneous Learning

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Directly on small compute edge

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Continues to learn

Brain Builder™ cloud-based platform

Brain Builder, part of the Neurala VIA product, is a cloud-based solution that enables rapid AI prototyping, allowing users to annotate and train at the same time. Because of L-DNN's accelerated learning speed, learning can occur as new image data becomes available, so precision gains are instantaneous. Users can quickly iterate instead of having to wait hours, days or weeks to understand results.

Neurala VIA Inspector

Neurala VIA Inspector allows for seamless integration on the factory floor: collecting images from virtually any GigE vision camera, and providing outputs over an industrial network directly to the PLC controlling the applicable machine to run the vision AI models.

Only "good" product images needed

Neurala’s AI can be trained with only acceptable, or good product images, unlike traditional DNNs that need both good and bad examples. Working with good samples only, L-DNN produces an anomaly signal when an alteration occurs. This results in tremendous time savings since defective products appear infrequently and randomly, and it would take a long time to collect their image data.