Your data. Your hardware. Your AI.
Inference Point helps businesses run language models privately — on-premises or in infrastructure you control — without sending a single customer record to a third-party API.
What we build
Private LLM deployment
Production inference on your own GPUs — model selection, quantization, serving stack, and monitoring. Open-weight models tuned to your workload, from a single workstation to a cluster.
AI that reads your business
Retrieval over your documents, assistants wired into your existing tools, and automation for the workflows that eat your team's hours — all running inside your network boundary.
Right-sized GPU infrastructure
Honest sizing before you buy. We benchmark your actual workload, then spec hardware and serving configuration to match — including when the answer is "smaller than you think."
Most AI consultants demo on someone else's cloud. We run production inference on our own metal — multi-GPU serving, Kubernetes, quantized open-weight models — and we build yours the same way: measured, monitored, and owned by you.
How an engagement runs
Assess
A short discovery: your data, your constraints, and where a model actually earns its keep. You get a written plan with hardware and cost estimates — useful even if you build it yourself.
Pilot
A working deployment on real workloads, with measured latency, quality, and cost per query. Decisions come from numbers, not vendor slides.
Hand off
Documentation, monitoring, and training so your team runs it without us. We design ourselves out of the loop — that's the point of owning your stack.
Tell us what you'd automate if privacy weren't the obstacle.
We'll reply with an honest read on whether self-hosted AI fits — and what it would take. No retainer required to ask.