Detecting industrial safety risks in seconds, not minutes, is what keeps workers safe on an active plant floor. This is what Tata Elxsi set out to deliver by building IRIS, a real-time industrial safety platform on AWS.
In this post, we show how Tata Elxsi built IRIS (Industrial Real-Time Intelligence System). We cover the architecture decisions, the implementation approach, and the measurable results you can expect from a similar build. Whether you operate a handful of cameras or thousands across multiple sites, this blueprint provides patterns you can adapt for your organization.
Tata Elxsi is a global provider of design and technology services across industries including automotive, manufacturing, broadcast, communications, healthcare, and transportation. Its teams combine engineering depth with AI and computer vision to help enterprises modernize safety-critical physical operations. IRIS is Tata Elxsi’s industrial vision platform, built for organizations that already operate camera infrastructure but cannot yet turn those feeds into real-time, actionable intelligence.
Industrial organizations have invested heavily in automated safety over the past decade. Manufacturing plants, warehouses, logistics hubs, and chemical facilities operate hundreds to thousands of cameras. These cover production lines, hazardous zones, vehicle corridors, loading areas, and restricted-access locations. Yet most of this footage is recorded and rarely acted on in real time. Safety teams face a common set of constraints:
These aren’t failures of any single tool. They were signals that safety monitoring needs to evolve from passive recording to continuous, automated detection that scales with the number of cameras.
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