The world's most advanced industrial companies are deploying large-scale AI initiatives with NVIDIA technologies. GPU-accelerated computing enables industrial-scale AI so you can take advantage of unprecedented amounts of sensor and operational data to improve time to insight, optimize operations, and reduce costs.


NVIDIA and sysGen's combined AI solutions provide an easier, faster path to GPU-accelerated deep learning and machine learning models.

Gain greater ACCURACY

Use Deep Learning to make your industrial inspection and predictive maintenance algorithms even more accurate

leverage AI at INDUSTRIAL scale

Take advantage of the vast amount of data from your devices to train your AI algorithms faster and optimize your operations at scale.



  • HPC
  • Modeling and Simulation
  • Design for manufacturability and maintainability


  • Forecasting
  • Supply chain optimization


  • Robotics
  • CV Inspection
  • Preventive maintenance
  • Process control


  • Preventive maintenance
  • On-site inspection
  • Logistics optimization
  • Inventory optimization
AI in industry


With your data, you can train your algorithms and boost insights.

Industrial inspection

NVIDIA GPUs are used to create the most precise automated inspection solutions for semiconductor, electronics, automotive component and assembly manufacturing.

With associated software tools, GPUs enable efficient training of models for greater precision and optimized inference deployment at the edge. These models significantly improve the accuracy of industrial inspection, resulting in reduced test deviations and increased impact with higher throughput performance.

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Increase in return on investment by 1%, raising profit for the year by 60 million €

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64 % lower rates for test deviations

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200% automotive inspection throughput

Preventive maintenance

GPU-accelerated predictive maintenance solutions help industrial organizations reduce operational costs by delivering higher accuracy than traditional machine learning methods for predicting equipment failures.

By reducing defects and unplanned downtime, NVIDIA GPUs and add-on software enable industrial companies to operate smarter and safer while lowering operating costs.

Oil & Gas
Baker Hughes GE's Deep Learning-based predictive maintenance solution is powered by NVIDIA's DGX. It delivers a probability orchestration engine with a catalog of models supported by NVIDIA GPUs to predict equipment failures two months in advance. The solution can be deployed within weeks,and provides 4 to 5 times more accuracy in predicting device failures.
Aerospace and manufacturing
NVIDIA's ecosystem of software partners and system integrators provides GPU-accelerated machine learning and next-generation predictive deep learning solutions so you can train a model faster for greater accuracy.
Download predictive maintenance whitepaper
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Faster deployment

Accelerate your results with pre-built and pre-trained Deep Learning algorithms designed specifically for industrial devices.

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More accuracy

Achieve a 50% reduction in false positives and a 300% reduction in false negatives.

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Faster algorithm training

Ensure a 50 times faster workout.

Robotics in manufacturing

AI-enabled smart factories are changing the manufacturing landscape. This includes everything from compact robots trained to perform specific tasks to autonomous rovers that deliver parts in production lines to cooperative robots ("cobots") that work alongside workers on the assembly line.

With end-to-end solutions powered by NVIDIA EGX and Jetson™ in the periphery with NVIDIA GPUs in the cloud, industrial robot outcomes are more efficient and reduce costs at scale.
Read the presentation of the Musashi solution
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More accuracy

Increase robot assembly accuracy from 60% to 95%.

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Robotics inspection

Automate repetitive, error-prone tasks with AI-enabled robots equipped with computer vision.

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Logistics optimization

Improve logistics and operations with robots that select, transport and deliver parts on the assembly line.

Accelerated Computing at the Edge

Modern industrial edge computing requires GPU-powered compute capabilities for industrial inspection and robotics in factories, as well as predictive maintenance of equipment and devices in the field. NVIDIA EGX and Jetson solutions accelerate even the most powerful edge computing systems for these applications, and beyond.
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The NVIDIA data center platform makes training Deep Learning and machine learning models significantly faster, delivering insights that could not be achieved before. From edge to data center hosted AI models, NVIDIA Data Center Tesla GPUs are available at sysGen for every major computing system to accelerate the training of AI models in your data center.

They are also available in NVIDIA DGX systems, equipped with DGX add-on software for rapid deployment to meet the demand of deep learning and machine learning developers.
data center


Cloud computing has revolutionized industries through democratization of the data center, bringing disruptive changes in how businesses operate.

NVIDIA GPUs are available on demand in all major cloud platforms worldwide, and NVIDIA GPU Cloud (NGC) provides GPU-accelerated containers for easy deployment, including Deep Learning frameworks such as TensorFlow, PyTorch, MXNet, and more.
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NVIDIA software libraries and SDKs create a scalable solution that enables customers to deploy inference and AI in the cloud, on your servers, or in the edge. This software investment is designed to accelerate customer implementation time and reduce overall development costs.

These NVIDIA SDK investments include JetPack™ for embedding, DeepStream for IVA, Isaac™ TensorRT™ for inference, Transfer Learning Toolkit for optimizing DNNs, NVIDIA GPU Cloud for containers and AI software, and more.
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