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2026 Interop Tokyo 1 illustration related to Join Us at Interop Japan 2026
Events
May 26, 2026

Join Us at Interop Japan 2026

As AI models continue to scale, GPU memory and storage performance are becoming critical challenges in modern inference infrastructure.

KV cache offload to NVMe is no longer optional for many production AI environments — but without the right storage architecture, it can introduce additional latency, bottlenecks, and performance instability.

That’s where SupremeRAID™ AE and SupremeRAID™ HE come in.

SupremeRAID™ AE is designed for AI and GPU servers, enabling high-performance KV cache offload to local NVMe with near-native NVMe performance and enterprise-grade data protection.

SupremeRAID™ HE extends this performance to AI data centers and HPC clusters, delivering high-availability RAID for shared NVMe storage environments while supporting scalable, resilient infrastructure for large-scale AI workloads.

Together, SupremeRAID™ AE and HE help AI infrastructure overcome storage bottlenecks — from single GPU servers to rack-scale AI deployments.

At Interop Japan(株)ナノオプト・メディア 2026, we’re excited to showcase how Graid Technology enables high-performance, highly reliable AI storage for the next generation of inference infrastructure. See you in Tokyo! 🇯🇵🚀

📍 Booth 5U12-5 | June 10-12 | MAKUHARI MESSE, Tokyo

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News & Resources

Join Graid Technology at OEC booth A7-5 during Japan IT Week Autumn 2026, October 21–23, to explore SupremeRAID™ AE with OEC’s server solutions and SupremeStore for high-performance AI and HPC storage.
Defense systems at the rugged edge need compact servers that can protect and process mission data in extreme conditions. See how Trenton Systems uses VROC™ by Graid Technology and SupremeRAID™ in its U.S.-built TRS14-18.5 1U server to combine resilient boot storage with GPU-accelerated data protection.
Graid Technology will showcase SupremeRAID™ AE and Supreme JBOF at Cypher 2026 in Bengaluru, October 7–9. Explore GPU-accelerated NVMe storage and protected KV cache offloading for AI workloads from server to edge.