From a single model on your workstation to a multi-GPU inference cluster — on-site or remote, we handle the full stack. You get a running system, not a tutorial.
For organisations that need physical access, hands-on setup, or simply prefer someone in the room. We travel nationwide to deploy directly on your hardware.
Everything delivered over SSH and screenshare. Faster to schedule, identical outcome. Most deployments complete in a single session — you're running by end of day.
Every engagement starts with understanding your use case and hardware. We deploy the right tool for the job — not whatever's trending. Each service is available on-site or remotely.
Full-stack installation of open-weight language models on your hardware. Model selection, quantization tuning, inference server setup, and an OpenAI-compatible API layer — done and tested before handover.
Connect your local LLM to your documents, databases, or knowledge bases. A full Retrieval-Augmented Generation pipeline — vector DB, embeddings, ingestion, and query interface — entirely on-premise.
Custom LoRA / QLoRA fine-tuning on your own data. Adapt a general model to your domain — legal, medical, customer support, code — with targeted training that never leaves your infrastructure.
Turn your local LLM into an autonomous agent. Tool calling, multi-step reasoning, memory systems — all orchestrated on-premise with open-source frameworks and your existing APIs.
Whether you're on-site or remote, the process is the same. We've run enough deployments to know exactly where things go wrong — and how to skip those parts entirely.
30 minutes. Use case, hardware specs, any existing stack. We scope exactly what's needed — no upsell.
GPU, VRAM, RAM, storage profile. We match your hardware to the right model and quantization level.
Model pull, server config, API layer, monitoring. We do it live — you watch or we walk you through.
Throughput benchmarks, TTFT measurements, endpoint verification. We don't leave until it's confirmed working.
Full documentation, runbooks, and a recorded session. Your team can manage it — or we handle ongoing support.
One model, one machine, fully working. Good for individuals and small teams trying local LLMs for the first time.
Complete deployment with RAG, monitoring, and full handover. For teams ready to run AI in production.
Retained support for teams who want someone on call. Model updates, troubleshooting, and new feature deployments as needed.
On-site or remote, one machine or a cluster — start with a quick message. We'll come back with a clear scope and timeline.