Summary
A global chemical and specialty materials company needed a way to scale AI-driven operational improvements across its worldwide operations. By leveraging Cognite's market-leading industrial data and AI software, the company rapidly moved from proof of concept to full-scale deployment, rolling out over 50 AI use cases across 50 global sites in just two years.
Key Results:
- Accelerated efficiency: Streamlined workflows in maintenance, production, and operations.
- Cost savings: Multi-million-dollar avoided costs through predictive maintenance and optimization.
- AI-powered future: A robust data foundation enabling continued innovation with industrial AI agents.
The Challenge: Unlocking AI at Scale
This company faced a challenge common in industrial operations: digital and AI initiatives remained stuck at the pilot or lighthouse stage. The company knew routine maintenance, troubleshooting, and decision-making would benefit from real-time insights. Yet, despite multiple digital transformation efforts to increase operational efficiencies, the company struggled to scale use cases from one site to another due to the lack of a unified data foundation across sites. Key hurdles included:
- Fragmented data: Critical information was spread across disparate systems, requiring manual intervention.
- Limited scalability: AI-driven solutions were designed for single sites, preventing broader impact.
The company needed a way to break through these barriers—moving from isolated proof of concepts to enterprise-wide transformation.
Solution
A Scalable Data and AI Foundation with Cognite
To achieve rapid and sustainable scale, the company partnered with Cognite to establish a unified industrial data and AI foundation that would allow them to scale advanced use cases across the enterprise —powered by Cognite Data Fusion® and accelerated by Cognite Atlas AI™, a low-code industrial agent workbench designed to automate complex workflows.
With Cognite, the company created a single source of truth, mapping relationships across hundreds of billions of operational, engineering, and IT data records to build a real-time digital representation of their operations. By contextualizing this data into an industrial knowledge graph, it became instantly accessible to people, applications, and AI models—enabling faster insights, analysis, and tailored AI-driven solutions.
At the core of this industrial knowledge graph is a universal, real-time data model, which is crucial for scaling digital initiatives across multiple sites and use cases. Traditional data integration methods struggle to keep pace with the dynamic nature of industrial environments—when a single change occurs in a source system, it can break integrations and require costly, time-consuming fixes across every application that relies on that data. Cognite’s universal, industrial data modeling approach eliminates this fragility by creating a harmonizing layer that abstracts complexity and ensures consistency across all systems.
This open, extensible model acts as the application instructions for AI and digital workflows—allowing teams to quickly deploy new use cases without coding data models from scratch each time. Instead of rebuilding integrations and defining the data model for every site, function, or workflow, organizations can apply the same universal, AI-ready foundation across their entire enterprise—ensuring that as operations evolve, their AI and analytics solutions scale effortlessly alongside them.
This approach delivered:
- Rapid deployment: A standardized data model allowed AI-driven use cases to scale across sites without starting from scratch.
- AI-powered automation: Industrial AI agents for automated troubleshooting, maintenance, and production optimization.
- User-first digital transformation: Frontline workers gained intuitive, real-time access to insights in the field—reducing time spent sharing observations and reports from the field and improving decision-making.
With this scalable industrial data and AI foundation in place, the company moved beyond isolated use cases to deploy AI solutions at speed—transforming operations across its global network and empowering business and front-line users to make data-driven decisions in real-time.
Impact
Scaling Value Across the Enterprise
In just two years, the company successfully scaled AI and data-driven solutions across all 50 global sites, delivering measurable business value:
- Efficiency gains: AI-powered workflows optimized isolation planning, maintenance, and troubleshooting, saving over 100,000 hours annually.
- Predictive maintenance: Increased equipment insights helped prevent failures and reduce costs, avoiding millions in unplanned downtime.
- Real-time operations support: Engineers and operators accessed live insights in the field, improving resolution times and collaboration.
- Future-ready AI strategy: The robust data foundation now supports continuous innovation, with industrial AI agents automating even more aspects of operations.
With a scalable, AI-powered approach, the company is now positioned to accelerate digital transformation even further—expanding industrial AI applications to drive efficiency, resilience, and competitive advantage.