Hero offer
Private LLM Platforms
We deploy production-grade LLMs on your infrastructure using vLLM or TGI, behind your auth, observability, and audit stack. Models, prompts, and completions never leave your perimeter.
Zero data egress
How to deploy a private LLM on your own infrastructure
Five-step process to take a production LLM from selection to deployment on your AWS, Azure, GCP, or on-premise GPU infrastructure.
Choose your model
Benchmark Llama 3.x, Mistral, Qwen, and DeepSeek on your task. Pick based on quality, latency, GPU budget, and context length.
Size your GPU infrastructure
Calculate VRAM and throughput requirements. Provision A100, H100, or MI300X capacity in the region matching your data residency.
Deploy with vLLM or TGI
Containerize and deploy the serving runtime. Configure autoscaling, request queueing, and KV-cache settings for your workload.
Wire in auth and observability
Integrate with your identity provider for request auth. Send logs and metrics to your observability stack.
Run evals on every update
Build a task-specific evaluation pipeline. Run it on every model and prompt change so quality regressions get caught before production.
Common questions
Frequently asked questions
- Which open-source LLMs do you deploy?
- Most often Llama 3.x, Mistral, Qwen, and DeepSeek. We pick the model after benchmarking on your task and constraints (latency, GPU budget, context length).
- What infrastructure do you deploy on?
- Your AWS, Azure, GCP, or on-premise GPU clusters. We use vLLM or Hugging Face TGI as the serving runtime, behind your existing authentication and observability stack.
- How do you handle evaluations?
- We build a task-specific evaluation suite during the Strategize phase. The eval pipeline runs on every model update so you can measure regressions before they hit production.
- What about data egress?
- Zero. Prompts, completions, and logs stay inside your perimeter. The model never calls home.
- Can you run private LLMs in air-gapped environments?
- Yes. We've designed deployments for air-gapped environments where the model and serving infrastructure run with no internet access at all.
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