AI without sending a single prompt to a third party. We deploy open models — Llama, Mistral, Qwen — on your servers, private cloud or on-prem hardware, expose them through an OpenAI-compatible API, and manage the whole stack: hardware sizing, quantization, upgrades and monitoring. Your prompts, documents and customer data stay inside your network.
From model selection to GPU tuning to the API your apps call — we run it so your team just builds on it.
We match an open model — Llama, Mistral, Qwen, DeepSeek — to your task and hardware budget, and are honest about what a self-hosted model can and can't do versus a frontier API.
vLLM, Ollama or TGI on your dedicated servers, private cloud or on-prem GPUs — installed, configured and load-tested as code, so the setup is reproducible.
AWQ/GGUF quantization, batching and KV-cache tuning so the model fits the GPUs you have — often cutting hardware requirements sharply with minimal quality loss.
Vector store, ingestion pipeline and retrieval wired to your wikis, tickets and files — so the model answers from your knowledge, with sources, not from guesswork.
TLS, API keys, per-team rate limits and network isolation. The endpoint is private by construction — nothing is reachable from the public internet unless you want it to be.
Model and runtime upgrades, GPU utilization and latency dashboards, and alerting — treated like any production service, not a science experiment.
Point your existing OpenAI-SDK code at your own endpoint and it just works — same API shape, but every token is processed on hardware you control.
Any open-weight model — Llama 3.x, Mistral, Qwen, DeepSeek, Gemma and others — served via vLLM, Ollama or TGI. We help you pick the smallest model that actually handles your workload.
Not necessarily. We can deploy on GPUs you already own, spec a server for you to buy, or set up rented GPU capacity in a private cloud — whichever fits your budget and privacy requirements.
For focused workloads — internal assistants, document Q&A, extraction, summarization — a well-chosen open model with RAG is usually more than good enough. For frontier-level reasoning we'll tell you honestly, and can architect a hybrid setup that keeps sensitive data local.
On your servers, your private cloud, or on-prem — your choice. The endpoint is private, TLS-secured and access-controlled; only the people and apps you authorize can reach it.
Book a free 15-minute call or request a quote. Tell us what you want the model to do and what hardware you have — we'll map the fastest path to a private, production-ready deployment.
Architecture → implementation → proof → runbook · senior US engineers · $1M insured
OOM-killed inference server, a runaway GPU bill, or a queue that's backed up — emergency support is our entry tier. Start an urgent request and a senior engineer digs in the same day.