Scale industrial use cases such as predictive analytics, batch optimization, energy optimization, connected worker, and predictive maintenance with an industrial data operations platform

Video Summary:

Explore how IRIS Foundry enables industrial organizations to scale AI across operations with speed, intelligence, and clarity. This video breaks down the platform’s five core pillars—including data orchestration and an AI-powered Knowledge Graph—and showcases how role-based AI copilots drive predictive actions in real time.

Discussion Breakdown:

IRIS Foundry Overview and Value Proposition:

• Introduces IRIS Foundry as a composable, AI-enabled industrial DataOps platform.
• Highlights scalability and rapid deployment capabilities built for enterprise-wide impact.

The Five Core Pillars of IRIS Foundry:

• Orchestration: Seamlessly connects IT, OT, and engineering data.
• Contextualization: Builds a unified data model across disparate systems.
• AI Knowledge Graph: Analyzes processes and assets through intelligent graph structures.
• Insight: Supports purpose-built industrial applications.
• Governance: Ensures data trust, lineage, and management at scale.

AI-Powered Knowledge Graph in Action:

• Visualizes equipment and performance metrics via Asset and Performance Cortex graphs.
• Provides real-time correlation between operational parameters and asset health.
• Enables deep analytics on both structured and unstructured industrial data.

Operationalizing Role-Based AI Co-Pilots:

• Demonstrates the industrial LLM-driven IRIS Copilot for contextual AI assistance.
• Triggers anomaly assessments, predictive analysis, and corrective actions.
• Empowers end users with hands-on tools for root-cause diagnostics and performance optimization.