Manufacturers have invested heavily in sensors, platforms, and cloud infrastructure. Yet on most shop floors, the same problem persists: critical decisions are still made with delayed, fragmented, or context-poor data.

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Physical AI is not about deploying isolated automation. It is about building adaptive systems that learn, act, and improve in real-world manufacturing environments. And that requires getting the data backbone right.

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Without a Unified Namespace, AI models remain disconnected from the physical world they are meant to optimize. At scale, this disconnect doesn't just slow AI adoption — it introduces operational, compliance, and decision risk that compounds over time.

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The good news? Forward-looking manufacturers are already proving this can be solved. By establishing a single trusted operational truth across plants and sites, leaders are moving AI from dashboards and pilots into decisions that actually matter on the floor.

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In this exclusive webinar, brought to you in partnership with Cognizant and AWS, our expert panel will explore how manufacturers are building the real-time intelligence backbone that makes Physical AI work — and what it takes to scale it without ripping out brownfield systems.

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Manufacturers who have successfully operationalized Physical AI are reporting measurable results — reduced unplanned downtime, lower operating costs, faster time-to-decision, and AI deployments that scale across sites rather than stalling after the pilot.

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This session focuses on what separates those outcomes from the organizations still waiting for their data to be "ready."

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Don't miss this opportunity. The manufacturers building this foundation today will be the ones setting the pace tomorrow. This is where that conversation starts