Mind Enterprise brings deterministic, on-premises inference to the work that can’t leave the room: your models, your silicon, your walls, your rules. No pricing page here, on purpose — serious deployments start as conversations.
We don’t ask you to trust a datasheet. Each of these is observable behavior you can measure in your own environment before a single contract is signed.
Prompts, outputs, and models live and die inside your perimeter. Mind has no server side — there is no vendor endpoint for your data to reach, which simplifies more compliance conversations than any certification can. Fully operational with the network cable unplugged.
On a given machine, identical input under identical settings produces identical output, token for token, run after run. Results that mattered last quarter can be reproduced exactly for review, audit, or dispute — a property most inference services cannot offer at any price.
Mind runs on the x86 servers and workstations your procurement team already knows how to buy, at prices that don’t require a capacity-planning committee. No accelerator queue, no per-token invoice — the cost curve is hardware you own plus a license, and it stays flat while your usage doesn’t.
Every performance figure we publish carries machine, commit, build, and environment in an append-only ledger — and we hand you the methodology to reproduce every number independently. If our claims don’t survive your hardware, we’d rather know before you sign than after.
If your industry has a regulator, a classification level, or a client agreement that decides where data may live, you already know whether this page is for you.
Draft, review, and analyze inside the firm’s walls. No third party ever holds a copy of the matter.
Clinical and administrative work on infrastructure your compliance team already governs.
Deterministic output means a result can be re-derived exactly when the auditor asks how you got it.
Mind doesn’t degrade without a network; it simply doesn’t notice. Built for rooms with no outside line.
Sites, vessels, and facilities far from any cloud region — inference lives with the operation, not the uplink.
The same runtime from a single analyst workstation to workstation-class servers — one behavior to validate, not five.
Today, determinism is proven per machine: each box in your rack is exactly repeatable on its own silicon. The bar we’re building toward is stricter: the same input producing the same answer on every box in the fleet — not close, identical. When that test is passed, an inference fleet stops being a service you monitor and becomes infrastructure you audit, the way regulated industries audit everything else they rely on.
We say “building toward” deliberately. That claim hasn’t been earned yet, by us or by anyone, and we don’t put unearned claims on pages like this. If your organization is the kind that finds that sentence reassuring rather than disappointing, we should talk — you’re exactly who we’re building it with.
No pricing tiers, no self-serve checkout. Enterprise deployments are engineering engagements, and they begin the way engineering does: with the actual requirements.
The workload, the models you care about, the hardware you have or plan to buy, and the constraints your regulator or clients impose. An hour of specifics beats a month of decks.
We benchmark against your hardware class and hand you the methodology to reproduce every result independently — on your machines, behind your firewall, at your pace.
A licensing and deployment plan built around your environment — sites, seats, and support structured to how your organization actually runs, not how a pricing page wishes it did.
The silicon is already on your books. The models are open. The only thing missing is the runtime — and a conversation.