Binary Innovations
Efficient
Reduce memory and IPC overhead in multi-tenant GPU environments.
Secure, low-level middleware built for the realities of parallel GPU workloads.
Reduce memory and IPC overhead in multi-tenant GPU environments.
Harden low-level data pathways against cross-tenant leakage.
Designed specifically for the constraints of parallel AI workloads, not adapted from general-purpose systems.
Modern operating system architectures and traditional Linux kernel subsystems were not originally designed for massive, parallel AI workloads.
Excessive context-switching, inefficient memory allocators, and IPC bottlenecks lead to compute loss and security vulnerabilities across multi-tenant GPU environments.
We build systems-level software, secure kernel modules, and optimized C/C++ middleware layers to streamline memory access, secure low-level data pathways, and optimize hardware resource utilization for enterprise AI workloads.
We're an early-stage team currently in research and development. Technical writeups, benchmarks, and open documentation will be published here as they're ready.
R&D — pre-releaseWe'd like to hear what's breaking at the systems level.
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