Run powerful AI on
your own infrastructure
For teams that can't — or won't — pipe their data through a third-party AI API. I design and deploy private LLM inference: on-prem or in your own cloud, your data never leaving your boundary.
The assistant can answer questions about a private deployment and take your details.
Why teams self-host
There are three reasons companies move inference off a public API. Usually it's one of them sharply — sometimes all three.
Compliance & data residency
Customer data that legally can't leave your infrastructure — GDPR, healthcare, legal, fintech. Self-hosted inference keeps every token inside your boundary, with an auditable data path.
Cost at scale
Per-token API pricing is fine until volume makes it the largest line item. Owned or rented GPUs flip the economics past a break-even point — the question is where that point is for you, and I'll model it honestly.
Latency & control
No rate limits, no surprise deprecations, no noisy-neighbour latency. Predictable performance you tune, and a model that doesn't change underneath you unless you change it.
What I actually do
Not advice — a working deployment. From model selection to a system your team can run without me.
Model & hardware sizing
Which open model fits your task and your constraints, quantization strategy, and the GPU/VRAM footprint to run it at your throughput target — sized to real numbers, not guesses.
Production inference serving
vLLM (or the right server for the workload), batching and concurrency tuned for your traffic, deployed on-prem or in your private cloud. Built to be operated, not babysat.
Private RAG & assistants
Retrieval and assistant layers over your own documents, where the embeddings, the vector store, and the model all stay inside your boundary.
Honest build-vs-buy call
If a hosted API is genuinely the right answer for you, I'll say so and tell you why. The break-even math comes before the build.
Is self-hosting right for you?
Tell me the workload, the data involved, and the constraint that's pushing you off a public API. You'll get a straight answer on whether self-hosting is worth it for your case — and what it would take.