# Amazon — How Tata Elxsi detects industrial safety risks in seconds on AWS

- Company: Amazon (amazon.com)
- Announced: 2026-09-22T15:19:54+00:00
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://aws.amazon.com/blogs/machine-learning/how-tata-elxsi-detects-industrial-safety-risks-in-seconds-on-aws/
- Record: https://forck.live/items/13078-how-tata-elxsi-detects-industrial-safety-risks-in-seconds-on-aws
- Subject: Bedrock / Nova

Tata Elxsi's case study documents how the company built IRIS, a real-time industrial safety platform on AWS that uses computer vision to detect unsafe conditions in manufacturing and warehouse environments. The platform processes video at the edge using AWS IoT Greengrass and GPU-equipped servers, streams safety-relevant metadata through Amazon Kinesis Data Streams, and reduces cloud-bound frame volume by 70–80 percent through edge filtering.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/how-tata-elxsi-detects-industrial-safety-risks-in-seconds-on-aws/:

> The design goal for IRIS was to analyze video as it's produced, detect unsafe conditions automatically, and generate actionable alerts in near real time, without streaming raw video to the cloud.

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