Your context never leaves.
Run models beside the systems that hold your sensitive work. No training on your prompts. No third-party retention policy to interpret.
Talk through your stack ↗On-premise AI systems · San Francisco Bay Area
Private inference,
installed where
your work happens.
A production-ready language model stack for teams that need capable AI without sending every prompt, file, or customer conversation to a public endpoint.
Designed for small teams, built for real workloads
PRIVATE RUNTIME LOCAL / 01
Throughput42.8 tok/s
⌁ Oakland · 14 ms
✦ Your data stays yours
01Data
sovereignty
sovereignty
02Consistent
models
models
03Hands-on
operations
operations
For founders, studios, agencies,
and teams with something to protect.
The case for private
AI that answers
to your team.
One dependable answer.
Pin versions, prompts, and retrieval behavior. Your team gets a stable tool instead of a moving target hidden behind a SaaS update.
Our deployment approach ↗Infrastructure that earns its keep.
We size the hardware, wire the serving layer, and hand over a system your team can actually operate and understand.
Estimate a build ↗A calmer way to deploy
From blank rack
to useful system.
We combine a short discovery sprint with a focused install. You get an opinionated first system, not a months-long science project.
01
Map the work
We identify the workflows where privacy, latency, or consistency actually matter.
02
Size the machine
We match model, memory, storage, and serving throughput to your real usage.
03
Install & hand off
Your runtime, monitoring, access controls, and runbook arrive as one working system.
Start a conversation
Tell us what you
want to keep close.
Give us the rough shape of the problem. We will reply with a practical first pass on hardware, models, timeline, and budget.
↳
Usually a 20-minute call.
No pitch deck required.