A sovereign, self-healing Linux kernel intelligence grid designed to replace legacy task management with real-time AI-driven kernel optimization.
Traditional OS schedulers are deterministic, static, and blind to intent. They struggle with context switching overhead and resource thrashing in modern agentic workloads.
ZYO replaces the standard CFS with an Agentic OS Architecture. It treats every system call as a decision point for a local, high-speed inference engine, predicting resource needs before they manifest.
ZYO analyzes instruction streams to pre-allocate cache lines and memory segments before the process even enters the runqueue.
Automated detection and repair of kernel panics and deadlocks via eBPF injection, maintaining 100% uptime.
Ingests 1.2M metrics/sec across the entire hardware stack, from L1 cache hits to fan RPMs, feeding the scheduler brain.
The “Packet Vaporizer.” Ring-0 firewalling that drops malicious traffic in the NIC before the kernel even sees the interrupt.
Micro-scheduling logic that prioritizes low-latency audio and UI threads by predicting human interaction patterns.
Eliminates mutex contention using a lock-free transactional memory manager optimized for multi-core sovereign grids.
Real-time eBPF probes collect instruction cycles, IRQ frequency, and thermal data across all cores.
Local Ollama instance handles strategic policy, while a LibTorch C++ core executes nanosecond-level tactical shifts.
Direct injection of task priorities and firewall rules into the Ring-0 execution context.
ZYO is designed for environments where privacy isn’t just a feature—it’s a requirement. All AI inference is performed locally. No data leaves your machine. No telemetry is shared. Even the LLM weights are stored in encrypted local volumes.
Embedded Llama-3 (8B) quantized for CPU-only inference with zero latency penalty.
Update kernel modules and models via authenticated physical storage keys.