Revolutionizing manufacturing with Enterprise AI


Increase Throughput, Supply Chain Efficiencies, and Services Revenue helps leading manufacturers rapidly integrate data from enterprise systems, operational sources, sensor networks, and external providers to power machine learning models that generate predictive insights. This addresses important goals such as inventory stock reduction (by as much as 35%), waste elimination due to quality defects (by over 20%), and generating $100s of millions in economic value annually for global manufacturers.

Manufacturing value chain

Applications Inventory Optimization

Reduce inventory holding costs, improve cash flow and supply chain visibility, and increase the productivity of inventory analysts. Inventory Optimization applies advanced machine learning to analyze variability in demand, supplier delivery times, quality issues, and product-line disruptions to build real-time recommendations and monitoring, so users can set optimization by confidence level and receive real-time notifications and root-cause analysis. Global manufacturers using Inventory Optimization have decreased inventory levels by 35%.
Learn more Predictive Maintenance

Aggregate petabyte-scale data from sensors, devices, enterprise systems, and operational systems (e.g., SCADA, OMS, GIS) to generate accurate predictions of asset failure. Predictive Maintenance provides planners and operators with comprehensive insight into asset risk, enabling them to maintain higher levels of asset availability, deliver services-based differentiation, and reduce maintenance costs.
Learn more Energy Management

Reduce energy costs and improve building operations through real-time tracking, analytics, and optimization. Energy Management uses machine learning techniques to enable accurate forecasting, benchmarking, building optimization, demand response, and anomaly detection to lower costs, improve operations, and meet energy-efficiency goals.
Learn more Sensor Health

Ensure the operational health and optimal deployment of IoT sensor devices with machine learning. Sensor Health uses advanced AI/machine learning to predict sensor failures and identify sensor and network health issues with a high degree of precision.
Learn more CRM

Leverage real-time AI/machine learning to drive operational excellence and improve profitability across sales, marketing, and customer service. CRM delivers AI-generated forecasts and scores in real time using insights from internal and external data sets.
Learn more

Use Cases

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Multi-Echelon Inventory Optimization

Access a comprehensive view of global inventory levels across individual lines and factories and entire supply networks. Perform scenario planning and root cause analysis, optimize inventory levels, and manage suppliers comprehensively.

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Supply Network Optimization

Address supply network variability by pinpointing issues and streamlining operations across individual supply chains and collective supply networks. Perform scenario planning, improve understanding of supplier performance, and generate recommendations based on live data.

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Yield Optimization

Improve throughput and product quality by quickly detecting and mitigating emergent process issues. Apply advanced machine learning techniques to predict downstream product yield issues and pinpoint problematic process steps.

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Price Optimization

Aggregate sourcing data into a unified federated image to perform pricing analytics and visualization. Build optimal price estimates for raw materials based on advanced machine learning analysis of previous pricing and expected consumption.

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Warranty Optimization

Identify componentry at risk and proactively alert customers to potential issues to increase service satisfaction levels and reduce downtime. Maintain visibility of individual components at factory, distribution, or customer locations.

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Profitable BOM

Maintain accurate bill of materials (BOM) pricing and componentry for highly complex products at each stage of engineering, delivery, and after-market. Calculate profitability for design, as-built, and added components for aftermarket stages.

Address use cases with the C3 AI Suite

The C3 AI Suite is a purpose-built platform for developing and operating AI applications that address industry and company-specific use cases. It offers a cohesive, low-code/no-code development environment with a complete and comprehensive set of tools and services to design, build, deploy, and operate advanced, enterprise-scale AI applications.

Explore the C3 AI Suite


Sam Anderson
3M Developers

3M Developers

Members of the CoE

“When we build these applications with, we can pull the data from all these different source systems to shape into exactly the architecture we want that data to be in, and take that data and get creative with it.”

Jennifer Austin
Jennifer Austin

Jennifer Austin

Manufacturing & Supply Chain Analytics Solutions Implementation Leader

“Within six months, we were already seeing value from the application.”

Henry Chang
Henry Chang

Henry Chang

Vice President, 3M Connect

“We’ve been engaged with the team to figure out better processes and make user-friendly applications that enable our data scientists to draw insights and conclusions to drive outcomes.”

Proven results in weeks, not years

Get insights into’s capabilities, enterprise AI best practices, and highest-value use cases.
Gain insights into the C3 AI Suite's capabilities, its model-driven architecture, and test it against your company's sample data set.
Identify a high-impact business problem and collaborate with the team to rapidly build an AI application that solves it.
Scale and deploy a tested application into production. Incorporate user feedback and optimize algorithms to drive maximum economic value.

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