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    SymphonyAI Unveils IRIS Foundry: A Game-Changing Industrial Data Ops Platform

    ManufacturingNews

    SymphonyAI Unveils IRIS Foundry: A Game-Changing Industrial Data Ops Platform

    The platform is designed to enhance process efficiency, minimize unscheduled asset downtime, and bolster connected worker capabilities.

    Last updated

    SymphonyAI, a frontrunner in predictive and generative enterprise AI SaaS, has introduced IRIS Foundry, an industrial data operations platform aimed at revolutionizing the creation of digital industrial applications. The platform is designed to enhance process efficiency, minimize unscheduled asset downtime, and bolster connected worker capabilities.

    Addressing Industry Challenges

    Manufacturers face significant hurdles in bridging data silos across their operations, businesses, and enterprises. The absence of a scalable approach to contextualize industrial data for insights and decision-making has hindered revenue growth, productivity, and knowledge sharing. According to sources, 86% of manufacturing executives believe smart factory solutions will be the primary drivers of competitiveness in the next five years.

    Customer Testimonial

    Ben Engels, Reliability Manager for Nippon Gasses, emphasized the critical importance of safe and reliable operations. He praised the proactive anomaly detection and prevention capabilities enabled by SymphonyAI's predictive AI models, expressing excitement about the release of IRIS Foundry and its potential to expand benefits across equipment and sites.

    Foundational Components

    IRIS Foundry provides essential building blocks for industrial data management and governance, facilitating the deployment of AI-embedded manufacturing solutions at an enterprise scale. The platform offers pre-built connectors to extract data from IT, OT, and enterprise sources into polyglot dataops storage, ensuring versatile handling and integration. Data is organized into a structured asset hierarchy using AI-powered P&ID ingestion or existing asset historian frameworks, resulting in a dynamic industrial knowledge graph.