Use cases

Aggregate, govern, and transform information from sensors, control systems, and enterprise systems into standardized, validated formats.

Unify and enrich data across your operations together through meaningful context, business logic, and relationships to create trusted, AI and analytics-ready data sets.

Unlock real-time visibility, improve decision-making, and enable new use cases like data science and machine learning.

Strengthen collaboration with secure OT/ET/IT data exchange with different stakeholders within your industrial ecosystem.

Share data between departments, applications, customers, or with partners, vendors, and suppliers.

Streamline supply chain operations, enable predictive maintenance, and accelerate innovation across integrated processes and stakeholders.

Democratize rich data across your organization with unified, enterprise‑wide visibility that delivers clear and actionable insights to every stakeholder.

Transform complex operational data into dynamic role-based visualizations that reveal trends, risks, and opportunities in seconds.

Empower teams at all levels, from leadership to frontline teams, to make confident, collaborative, and data-driven decisions that contribute directly to business outcomes.

Observe and analyze assets, processes and facilities at scale from anywhere in the world.

Visualize your operations centrally from the cloud with real-time data from sensors and other data-collecting devices.

Enable faster, smarter decision-making to streamline operations and uncover potential risks.

Use trusted data and models to simulate, predict, and optimize processes safely.

Create a dynamic digital twin that replicates your physical assets and operations, enriched with OT/ET/IT data from sensors, systems, and analytics.

Mirror real‑world performance, test “what‑if” scenarios, and make proactive decisions that improve efficiency, reduce costs, enhance safety, and drive continuous innovation throughout an asset’s lifecycle.

Strategic oversight of all mobile and fixed assets for their location, utilization, health, and failure indicators.

Gain insights to improve asset utilization, reduce fuel/energy consumption, and schedule maintenance interventions when needed, rather than on a fixed schedule or after a critical breakdown occurs.

Ensure that maintenance activities are performed effectively and economically to maximize asset performance, efficiency, and lifespan while minimizing costs and risks.

Apply advanced analytical techniques, using machine learning and artificial intelligence to identify unusual patterns or deviations in data generated by your assets and processes.

Detect anomalies such as equipment malfunctions, impending failures, quality defects, or other critical inefficiencies.

Analyze data in real time to detect irregularities early on, enabling proactive responses and enhancing overall operational safety and efficiency before an issue escalates.

Enable consistent, data‑centric design by authoring and managing information for 1D, 2D, and 3D project teams across disciplines, sites, regions, and organizations.

Create and maintain specifications, schematics, drawings, and intelligent 3D models within a unified engineering ecosystem. No more staged design document handovers and coordination bottlenecks.

Improve collaboration, reduce rework, and ensure every discipline works from accurate, connected data throughout the entire design and execution process.

Precisely measure and analyze key performance indicators (KPIs), coupled with the intelligent calibration of set points.

Evaluate metrics such as OEE, throughput, yield, cycle time, and energy consumption to understand how efficiently a process is operating and establish optimal values for process control variables.

Continuously monitor performance against real-time, adaptive benchmarks informed by predictive analytics and process intelligence to drive maximum efficiency, product quality, and energy optimization.

Go beyond simply cutting energy usage to minimize energy consumption and maximize energy efficiency within facilities and processes.

Continuously monitor energy flows using data analytics and operational adjustments to ensure that every unit of energy consumed delivers the maximum possible output while reducing waste.

Identify asset inefficiencies to lower operational costs, reduce environmental impact, enhance sustainability, and improve the overall competitiveness of industrial operations.

Monitor and document the entire journey of products or materials throughout the supply chain, from sourcing, production, distribution, and the end user.

Aggregate product item or batch details from various touchpoints using scanners, sensors, and integrated systems to optimize inventory management, operational efficiency, and provide an auditable history.

Ensure product authenticity, improve quality control, and enhance supply chain visibility to expedite targeted product recalls and regulatory compliance.

Monitor and measure critical performance impacts across greenhouse gas emissions, energy consumption, waste generation, and health and safety.

Effective ESG management that leverages data collection and analytics tools can streamline reporting, identify areas for improvement, and communicate progress to stakeholders.

Demonstrate a commitment to sustainable and responsible operations, enhancing brand reputation, mitigating risks, and driving long-term value.