A centralized dependency is a single point of failure. SigmaNex provides a sovereign, air-gapped AI foundation designed to operate independently of the global grid.
SigmaNex utilizes highly optimized quantization techniques (GGUF) to deliver Large Language Model capabilities on standard commercial hardware. The kernel operates in a strictly isolated environment with zero writes to the host filesystem.
| Inference Engine | Optimized LLM Runtime (CPU/AVX2) |
| Deployment Vector | USB 3.0+ (Live Environment) |
| Privacy Model | Air-Gapped / Zero-Trace |
| Data Persistence | Encrypted Local Storage Only |
Designed for maximizing utility on scavenged or legacy hardware in reduced-resource scenarios.
| Processor Architecture | x64 with AVX2 Support |
| Memory (RAM) | 8GB (Minimum) / 16GB (Recommended) |
| Graphics (Optional) | CUDA 11+ (For accelerated tokens/s) |
| Host OS | Windows 10/11 / Linux Kernel 5.x+ |
Complete independence from cloud API availability. The intelligence resides entirely on your local hardware.
Ephemeral session management ensures no data residue remains on the host machine after the USB key is removed.
Pre-loaded weights for specialized domains including emergency medicine, engineering, and survival logistics.
Benchmark of GGUF quantization efficiency on consumer CPUs. Establishment of hardware baselines.
Fine-tuning of 7B parameter models on specialized survival and medical corpora.
Closed-circuit testing on low-power hardware in simulated disconnected environments.
Distribution of the first stable USB image to early backers and strategic partners.
The SigmaNex codebase is open and accessible to active supporters during the Software Development Life Cycle (SDLC). Contributors and early backers will receive an exclusive discount on the retail release, communicated via secure email.