Automate Visual Inspections

Brain Builder custom vision AI enables faster, easier, and less expensive inspections automation and manufacturing processes

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INDUSTRIAL - WORKSPACE
build

Build

Create automated visual inspections with very little data in less than 30 minutes

deploy

Deploy

Quickly integrate the neural network with your lines, vision system, and cameras

analyze

Analyze

Improve performance over time as additional data is captured and defects detected

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Enhanced inspection beyond traditional computer vision

Unlike traditional computer vision for measurement, barcode reading, and assessing whether an object is present, deep learning is far better suited automating for the subjective assessment of product quality. Examples of ideal applications for deep learning as a tool for automated inspection are: defect detection, product quality classification, assembly verification, and texture/surface classification. 

INDUTRIAL - PROJECTS
INDUSTRIAL - LIBRARY

Why does traditional deep learning fail for most industrial applications?

They frequently require large amounts of data: for most industrial processes, sourcing images of good product is easy but accessing large amounts of defective product images presents a challenge. Due to large data requirements and a need for AI expertise and expensive hardware, adding deep learning to industrial processes is time consuming and expensive – placing it out of reach for many use cases. Brain Builder changes all this. 

How can Brain Builder support my industrial use case?

Brain Builder allows you to quickly and simply:

  • Produce and test an inspection algorithm with very little data
  • Assess use-case feasibility without an AI expert or expensive hardware
  • Refine precision over time and deploy to the edge, removing the need for cloud connectivity
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INDUSTRIAL - BRAINSCORE

Neurala’s at-the-edge learning is critical to a variety of applications, such as finding a lost child in a crowd. We looked at many companies to help us explore different applications of artificial intelligence for public safety, and Neurala had the neural network technology we were looking for.

Paul Steinberg, CTO

Neurala and the NVIDIA Jetson AI platform work together to develop innovative deep learning solutions for inferencing and learning at the edge. This enables a new class of intelligent machines.

Murali Gopalakrishna, Head of Intelligent Devices
NVIDIA

Neurala’s architecture is well-suited to run on the edge. It’s small and lightweight, and we can get the technology as close to the sensors as possible. There’s a feature set that is available now that’s real and tangible. Neurala has an architecture that can evolve as customer needs and requirements change

Charlie Elliot, Director of Product
Aeryon

Neurala's AI vision technology lets us process images faster, reduce our costs, and scale to meet our customer's needs in a way that simply wasn't possible before.

Tim Rowland, CEO
Badger Technologies

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