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Unlocking transceiver savings at scale for AI data centers

How AI leaders reduced hidden waste and improved decisions with validation and analytics

Are your “failed” optics really failing? 

AI data centers rely on thousands of high-performance transceivers—but many are sidelined as “failed” without structured validation. In two large-scale deployments, one hyperscaler and one financial institution respectively uncovered a gap between suspected failures and real defects, driving unnecessary spend and lost capacity. This success story shows how validation and analytics helped them clarify what was truly defective, recover usable optics and strengthen decisions for upcoming AI builds. 

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Key takeaways

Reveal which “failed” transceivers are actually healthy and return them safely to service.

Use validation data to focus warranty claims on real defects and support vendor discussions. 

Turn reporting and analytics into better planning for upcoming AI data-center builds. 

Download the full success story

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