Credo’s mission is to transform connectivity at scale through fast, reliable, and energy-efficient system solutions. Our high-speed copper and optical interconnect products deliver industry-leading power and performance to meet the ever-expanding data infrastructure demands of AI.

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ZeroFlap Optical Transceivers

Credo at OFC 2026

Credo debuted its expanded optical portfolio at the 2026 Optical Fiber Communication Conference and Exhibition (OFC) in Los Angeles, highlighting the significant role that high-speed optical connectivity has on enabling next-generation, high-bandwidth, AI-driven infrastructure. The company’s demonstrations—spanning 400G and 800G ZeroFlap optical transceivers, 800G and 1.6T optical DSPs, and their role in back-end networks—underscore the importance of scalability, energy-efficient data movement, and real-time telemetry for increasingly complex AI scaleout fabrics.

ZeroFlap Optical Transceivers

Credo Introduces Robin 800G Optical DSP Family Tailored for Next Wave of AI Applications

The Robin optical DSP family is designed to meet the growing performance, power efficiency, and scalability demands of AI-driven data center networks. Built on Credo’s advanced sixth-generation DSP architecture, the Robin 800G and 400G devices deliver enhanced signal integrity, reduced power consumption, and flexible deployment options, enabling hyperscale operators and system vendors to accelerate AI infrastructure deployments.

ZeroFlap Optical Transceivers

Credo Launches 800G ZeroFlap Optical Transceivers Engineered for AI Networks

Credo’s ZF optical transceivers address persistent connectivity issues—most notably link flaps—that undermine AI cluster performance and deployment efficiency.

ZeroFlap Optical Transceivers

ZeroFlap Optical Transceivers

The ZF optical transceiver product portfolio is designed to enable better management and mitigation of optical link flaps — an issue whereby a link will repeatedly connect and disconnect in quick succession — providing a new level of network stability and productivity to AI backend networks.

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