AI Cloud for


DataRobot AI Cloud for Manufacturing is uniquely designed for today’s manufacturing challenges and opportunities—and lays the foundation for the next generation of intelligent business.


AI in Manufacturing

In the rapidly-evolving manufacturing industry, AI Cloud for Manufacturing is helping companies to streamline operations, solve supply chain issues, and prepare for a strong, sustainable future.

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Supply Chain Management

Predict late shipments to prepare for foreseeable delays in your supply chain network and take data-driven corrective action. 

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Inventory Forecasting

Leverage AI to gain insights into seasonal demand and economic conditions on incoming volume.

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Quality Assurance

Through cutting-edge AI, ensure product quality, while streamlining operational processes and reducing manufacturing costs.

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Predictive Maintenance

Utilize AI to proactively find the maintenance decisions that maximize total production and minimize costs.


AI in Manufacturing

Explore How to Modernize Your Demand Forecasting, Supply Chain, and Predictive Maintenance


DataRobot’s Manufacturing Customers Are Shaping the Future

AI Cloud for Manufacturing is transforming the manufacturing industry

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Manufacturers need AI Cloud to address consumer demands, optimize operations and keep their employees safe

Manufacturers are facing unprecedented challenges on a global scale. Supply chain disruptions, shipping bottlenecks, sustainability concerns, and maintenance backlogs are further compounded by a rapidly evolving landscape of high consumer expectations and increased operational complexity. Manufacturers need to find new ways to solve some of their most important issues.

Discover more AI use cases for Manufacturing

  • Supply Chain Disruptions

    Supply chain disruptions are expected to become more common. According to the Economist Intelligence Unit, 54 percent of executives say that organizations must make significant changes in order to effectively manage supply chain disruptions in the next five years

  • Sustainability

    Sustainable operations are no longer optional. Companies could face up to $120 billion in increased costs from environmental risks in their supply chains within five years. And failure to meet targets can jeopardize customer loyalty and market opportunities (CDP).

  • Quality and Defects

    Defective materials reduce efficiency and increase the cost of manufacturing. They generate waste, lead to downtime, and require resource-intensive quality assurance and remediation. For example, an aerospace giant recently estimated that manufacturing quality defects will cost the company $1 billion (Seattle Times).

  • Downtime

    Unplanned downtime costs industrial manufacturers an estimated $50 billion annually. Equipment failure is the cause of 42 percent of this downtime, with unplanned outages resulting in excessive maintenance, repair, and equipment replacement (IndustryWeek).


AI Cloud for Manufacturing Demo: Visual AI

See how AI Cloud for Manufacturing uses Visual AI to overcome challenges such as automatically classifying product defects and detecting plant disease. 

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Get Started With DataRobot Today