Early Access · SDK Module

Run More. Spend Less.

The local inference engine, tuned to your hardware — not the other way around. Rust + CUDA, NCI-MoE research inside, 57× KV-cache compression: AI processing that stays on your infrastructure, at a fraction of the cost.

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Platform module of the AIvantGuard SDK — tier-based licensing, adopted with a deployment.

Capabilities

FlashInfer MLA decode

sm121-native attention with 57× KV-cache compression — more context, less memory.

Hardware-tuned deployments

Rust + CUDA optimized for the GPUs you actually own — no competitor tunes to customer hardware.

NVFP4 quantization

Modern numeric formats — more model per GPU, at serving-grade quality.

NCI-MoE architecture

Mixture-of-Experts research (published on Zenodo) — only the relevant experts load.

Rust foundation

Memory-safe, ~17,000 lines across 10 crates. Built for production, not demos.

Self-learning from usage

The engine improves with your workloads — deployment profiles sharpen over time.

Roadmap

Live today

DeepSeek V4 support

Serving current frontier-class models on your own metal.

Next

Kimi K3 support

The next model generation, tuned in.

Then

Self-learning from usage

Deployment profiles that optimize themselves from real traffic.

Long term

Commercial availability

GA as the inference engine of the sovereign stack.

Who it is for

SMBs without an AI hardware team

We bring the tuning expertise — you bring the GPUs you already have.

Large-scale providers

Inference cost curves that actually bend — at serving-grade reliability.

AI sovereignty programs

Independence from foreign inference vendors — models on your metal, under your law.

Production that never stops. Operations that cost less.