Memopt by Sophisticates - Zettascale Memory Fabric with a CockroachDB backbone

When I first started building Memopt, the goal was simple, to solve the GPU memory wall for a single node. But as AI models moved toward the 1-million-token horizon, I realized the real challenge wasn't just memory, it was orchestration at scale. Since the initial launch of the 6 Pillars, I’ve been heads-down executing a 10-phase roadmap to make memopt production-ready for the world’s largest clusters. Today, I’m excited to share that Phase 8 is complete. If you are running Blackwell or A100 clusters, you are likely losing 20-30% of your compute resources to memory fragmentation and KV cache redundancy. memopt reclaims that. It runs on your bare metal, with zero cloud dependency and zero "phone-home." We are currently entering Phase 9 (AMD ROCm support) and looking for two additional design partners at the 10k+ GPU scale to push the boundaries of what this fabric can do. I’ll be here all day to answer technical questions about our C++ data plane, the CockroachDB migration, or the physics of our 0.1ms memory borrowing. Let's break the memory wall together.