Neurala Announces VIA Software to Help Manufacturers Improve Quality Inspection

June 16, 2020

News

Vision AI enables manufacturers to improve throughput, quality, and production speed with finite resources.

Neurala announced its VIA (Vision Inspection Automation) software, an integrated solution to help manufacturers improve quality inspection on the production line while scaling to meet product demands. 

Neurala's VIA software enables manufacturers who have not worked with AI before to train and use vision AI to identify defects in products or packaging on the production line. And, with the ability to run directly on existing hardware on the factory floor, VIA makes AI accessible to industrial automation users who prefer not to rely on internet access or connectivity to the cloud. As a result, manufacturers can keep their data on the factory site, without concerns about privacy or lag time that are typically associated with cloud deployments.

VIA provides:

  • ROI: With less data required and faster training, VIA automates quality inspection processes that were previously not viable - improving inspection rates, decreasing human intervention, and allowing smaller batches to be inspected.
  • Optimization: Allows production facilities to avoid wasted resources by catching defects early.
  • Flexibility: Ability to train and run multiple AI models, compatible with any GigE camera and mid-range industrial PC.
  • Anomaly Recognition: Identifies any product that deviates from the "acceptable" images without having to collect images of defective parts.

For more information, visit: https://www.neurala.com/

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Tiera Oliver, editorial intern for Embedded Computing Design, is responsible for web content edits as well as newsletter updates. She also assists in news content as far as constructing and editing stories. Before interning for ECD, Tiera had recently graduated from Northern Arizona University where she received her B.A. in journalism and political science and worked as a news reporter for the university's student led newspaper, The Lumberjack.

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