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.
