From planning to scaling, unlock the power of AI for industrial vision applications.
Watch how teams build, deploy and maintain AI visual inspection without writing code.
The ReliVision platform enables users with no coding expertise to build and manage end-to-end AI solutions all on their own, enabling them to utilize their domain expertise to differentiate, while staying private.
From data curation to shop-floor deployment, every step of the AI inspection lifecycle in one platform.
Mark arbitrary objects and defects, define labels, compare and merge annotations, and import or export in industry-standard formats, all in one place.
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Choose an AI model from a rich and continuously growing library. Train, test and compare different models to pick the best for your QA application.
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Access key training parameters and train with a single click. Monitor performance, retrain on demand and compare results to get the best model.
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From a limited set of validated defects, ReliVision generates realistic synthetic variations, so models are ready early while all data stays local and secure.
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Operators give feedback on inspection results through ReliAudit’s web interface, improving the solution and adapting it to production changes, 24/7.
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Replicate high-performing solutions across lines and sites at no cost and scale computing power seamlessly with a synchronized distributed architecture.
Learn more →Real inspection playbooks covering classification, object detection, and detection combined with classification. Pick one and follow it step by step.
Sort rotors into defected and no-defect classes with a whole-image classifier trained on a small, balanced sample set.
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Detect scratches on device surfaces in two classes, so defect severity comes straight out of the model.
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Detect the imprinted alphanumeric characters on metal plates, annotated with rectangles, to verify markings automatically.
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A detector finds each wafer, then a classifier labels it Good, Small Defect or Big Defect.
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Practical, task-by-task guides for the workflows QA teams use every day in ReliVision.
Annotate where defects belong, pick a defect from the GenAI library and generate a synthetic defect dataset.
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Generate a custom image-processing node from a text prompt and reference image to pre-label defects.
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Train an inspection model from only a handful of real defect images, boosted with synthetic defects.
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“To achieve successful automation, it is crucial to have a product that can quickly adapt to production changes. We are using ReliVision at Foxconn to perform visual inspections, resulting in significant increase in quality while also having the ability to maintain the solution.”
“With ReliVision we are able to digitize inspections of construction panels and improve our overall process efficiency with a proactive QA approach. All this is maintained by our staff thanks to the Relimetrics’ in-line retraining technology.”
“Relimetrics collaborated with Lockheed Martin Aeronautics to develop AI-based machine vision enabled robotics for automating aircraft manufacturing and assembly processes. This innovation in automatic work-object identification allows the system to manage greater degrees of complexity compared with traditional machine vision.”
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“Relimetrics solution is embedded within our assembly line and enables immediate feedback to the operators and line managers to address any occurring issues right away. ReliVision has no fatigue-induced errors and moved the performance from 2.1σ to 4.2σ.”
Try ReliVision for free. No credit card required.
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