Physical AI: Bringing Intelligence to the Edge of Action

 
At GlobalLogic, we’re building systems that don’t just observe the physical world; they interact with it in increasingly intelligent ways. That means combining sensor data with structured knowledge, embedded reasoning, and closed-loop feedback.

Physical AI is expanding rapidly in fields like healthcare, where intra-surgical AI can support physicians with real-time image analysis, enabling more confident decisions, faster interventions, and better outcomes. These are high-consequence environments where latency and accuracy matter, and where edge-deployed intelligence is already reshaping what’s possible.

In one industrial use case, we helped enable real-time decisioning on component health (not in a data center but on the factory floor) using Agentic AI models engineered for low-latency environments and optimized for embedded compute constraints. In another, we worked with a mobility client to transform telematics into predictive maintenance signals, with agents that adapt routes and schedules autonomously.

Across industries, we see the same evolution: Physical AI empowers systems to reason and respond at the source, transforming raw telemetry into coordinated, contextual action.

But it’s not just about faster decisions. It’s about better ones, grounded in verifiable facts. As Yuriy Yuzifovich, our CTO, shared in a recent CIO.com article on Industrial AI, even systems without proper knowledge grounding can hallucinate confidently — generating plausible but false answers — in high-stakes environments.

Recommended reading: Industrial AI — Where knowledge (management) is power, at CIO.com

For example, a missing data point in an equipment manual once caused a GenAI assistant to suggest WD-40 instead of the required industrial grease. This is why knowledge-first design isn’t just a feature; it’s a safety requirement.

For AI to operate safely in physical systems, from surgical suites to rail infrastructure, it must reason reliably, not improvise. That’s why we build Physical AI with structured knowledge, embedded logic, and real-time guardrails. It’s not just about latency. It’s about trust, and the deep engineering disciplines required to ensure it. Our strength in embedded systems, particularly across Europe, uniquely positions us to deliver that trust at scale.

Physical AI isn’t a trend. It’s the new baseline for autonomy in real-world systems, from hospitals and factories to mobility platforms and smart infrastructure. It enables the Agentic Enterprise: a system in which intelligent agents coordinate actions across both digital and physical domains, learning continuously and operating safely at the edge.

Ready to go from dashboards to action? Learn how we design, deploy, and govern intelligent systems that operate at the edge — safely and at scale.

Download our executive brief on Agentic AI in the Enterprise

Or, schedule a 90-minute opportunity workshop with our team to identify where Physical AI can unlock value for your operations.

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