LLM Serving Professional Service

Run LLMs in your own Kubernetes cluster. Our engineers set up the serving stack with you.

We install and configure llm-d or NVIDIA Dynamo on your GPU nodes, connect it to your gateway and monitoring, measure it under load, and hand it over with runbooks.

Talk to an engineer

What we set up

  1. Inference gatewayRoutes requests by model and load
  2. Serving framework: llm-d or NVIDIA Dynamo
  3. Engine: vLLM, SGLang, TensorRT-LLM
  4. Models and KV cache
  5. GPU Operator, drivers, GPU nodesWave GPU is optional
  6. Your Kubernetes: Amazon EKS, OpenShift, on-premises

How an engagement runs

1 · Assess

Your models, GPUs, traffic, and latency targets.

2 · Install

Serving framework, engine, gateway, and monitoring.

3 · Measure

A load test that reports tokens per second, time to first token, and cost per 1M tokens.

4 · Hand over

Runbooks and training for your team.

Engagement details

Contact us for scope, length, and pricing.

Plan your LLM serving stack with us

Book a call