Local LLM Deployment

We design and deploy fully air-gapped LLM infrastructure tailored to your compute environment. Whether you are running NVIDIA A100s in a private data center or provisioning GPU nodes in a VPC, we handle model selection, quantization, inference server configuration, and load balancing. Every deployment ships with health checks, automated failover, and documentation your ops team can actually use.

Key Capabilities

On-premise and VPC-hosted inference servers (vLLM, Ollama, TGI)
Model selection and quantization consulting (GGUF, GPTQ, AWQ)
GPU resource planning and multi-model orchestration
Docker and Kubernetes deployment manifests
Health monitoring, autoscaling, and failover configuration
Air-gapped model registry with version pinning

Typical Engagement

Typical engagement: 2–4 week architecture sprint with your infrastructure team, followed by a phased rollout. We hand off runbooks, Helm charts, and a tested deployment pipeline.

Ready to get started?

Tell us about your infrastructure and security requirements. We will scope an engagement that fits.