For the enterprise
Enterprise AI that tells you when it doesn’t know.
A regulated, audited, sovereign estate cannot run AI that is confidently wrong. Cornerstone answers from your organisation’s own cited facts, declines when the answer is not there, and runs inside your boundary — hosted, in your cloud, or on your own hardware.
What changes for you
Four things move.
Risk
The confidently wrong answer stops reaching the work
A rule scoped to one region cannot come back as though it applied everywhere. When the answer is not in your knowledge it can say so — the only one of seven methods we benchmarked that could.
Audit
Have the evidence before the auditor asks
Every answer carries who wrote it, when, and where it applies. When a fact turns out to be wrong, you can find every decision that rested on it instead of reconstructing the trail by hand.
Capacity
Do more inside the same AI budget
Cost per question holds inside a narrow band so finance can forecast it, and the same spend reaches further as the knowledge grows rather than climbing with it.
Scale
Individuals get faster, and so does the organisation
What one person verifies once becomes a fact every team’s AI reads from. The bottleneck moves out of people’s heads and into infrastructure the whole organisation relies on.
How you get it
Three steps, in the order they happen.
01
Your people keep the AI they already use
Workbench Agent connects Claude, ChatGPT or Gemini to your knowledge on each person’s own workstation. Or run Workbench, our full interface, under your own name and on your own API key.
02
Deployed where your policy says
Hosted by us, in your own cloud, or on your own hardware. Every part of the platform deploys inside your boundary, so an air-gappable estate is available end to end rather than at one step.
03
One team first, then the estate
Start with one team, directly with us, and widen from there. Or bring your consultancy — the platform is built to be implemented by a partner, and the rounding-up of an estate is a job they know.
Sovereignty
Your knowledge stays yours.
For a regulated European enterprise this is not a preference, it is the condition of being allowed to use any of this at all. The same product in all three deployments; what changes is whose boundary it sits inside.
Bring your own model
No token markup, and no dependency on ours. Inference stays your contract with your provider.
Encryption and classification always on
Classification is how the access system works. There is no edition without it.
Air-gappable
Every part of the platform deploys inside your boundary, so nothing needs to leave the building.
Proof
Seven methods. Same documents. Same model.
We wrote the benchmark and we built the product, so it is measured on our own corpus and we say so. Eight tasks is a small sample. What it shows is that the methods fail differently, and that only one of them can decline — and that is the failure that reaches a regulator.
See the full benchmark →96.7%
found the right document, against 85% for the best alternative
1 of 7
the only method tested that could say when the answer was not there
8
the questions it got wrong, out of 49 it could not answer — published, not hidden
What it costs
Scoped per deployment.
Enterprise includes Validator and Habitat, single sign-on, role-based access and classification, and named support with an SLA. The number depends on how and where it runs, which is why it is a conversation rather than a card.
See what is in each tier →Bring your security team.
The questions they ask are the ones this was built around. Twenty minutes with a founder, and a straight answer on whether it fits — before anyone talks about a contract.