01
vLLM as the engine
Paged attention, continuous batching, tensor parallelism. The serving stack that powers most production open-weight deployments today.
★ On-premise LLMDirect LLM · no framework8-week engagement
ON-PREMISE · PRIVATE LLM DEPLOYMENTRun your own weights. Your VPC. Your call.
Self-hosted inference on Llama, Mistral, Qwen, or your fine-tuned variant. vLLM + Triton for production throughput. GPU sizing that doesn't melt your finance team. Air-gapped deployments where the contract requires it.
PythonvLLMTritonKubernetes
Cycle
8 weeks · weights to live
Stack
vLLM · Triton · Kubernetes
Output
Inference cluster + autoscaler + dashboards
Compliance
Air-gap-capable, data never leaves
[WHY THIS EXISTS]
Some data cannot leave the building.
Healthcare records. Defense workloads. Regulated finance. The hosted-API answer doesn't exist for these problems. You need the weights in your VPC, the GPUs under your control, and a deployment your security team can audit end-to-end.
- Frontier-grade open weights (Llama 3, Qwen 2.5, Mistral Large) on your hardware
- Latency-aware request batching for production throughput
- GPU autoscaling tied to actual demand, not vendor minimums
- Air-gapped deployment patterns where the contract requires it
[HOW WE BUILD IT]
Boring infra. Frontier models.
02
Triton for orchestration
NVIDIA Triton Inference Server in front of vLLM. Model routing, ensembles, dynamic batching, metrics. Kubernetes-native.
03
Right-sized cluster
We benchmark your actual traffic before quoting GPU hours. A100/H100/L40S — whichever matches the latency, throughput, and budget targets.
04
Observability + cost
Prometheus + Grafana for inference metrics. Per-tenant cost rollups. Token-per-second SLOs. The same dashboards your ops team already runs.
[OUTCOMES AT HANDOFF]
What's live at week eight.
0 bytes
Of prompt data leaving your VPC
~200 tok/s
Sustained throughput on H100s
<1.5s
P95 latency on 7B-class models
100%
Source ownership of the deployment
[ALSO WORTH READING]
Related LLM engagements.
DIRECT LLM · APPLIED KBring the problem.
Bring the problem.
We’ll bring the build.
Eight weeks, fixed price, eval suite at handoff. Direct LLM engineering on top of the K-Framework. Two Q3 slots remain.