Enterprise · Governance at scale

Scale without a third-party processor in the path.

At firm scale the question stops being whether the tool works and becomes who governs it, who reviews the output, and what happens when it is wrong.

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What governance at scale needs

Reach is easy to demonstrate. These are the things that are not.

Matter-level rules, enforced

Firm-wide approval cannot answer whether a particular client agreed. Restrictions are recorded per matter and enforced before anything runs.

Evidence of performance

Acceptance and correction rates per workflow, taken from what attorneys actually decided in review — not usage counts.

An incident path

A wrong or improperly disclosed output is reportable, owned and closed — kept separate from ordinary disagreement in review.

Model provenance

Which model version produced which work product, so a change can be identified rather than discovered.

What stays true on every matter

These do not change by practice area, firm size, or the question asked.

Nothing leaves the firmNo cloud, no API call, no telemetry. The matter is read on hardware the firm owns.

Owned, not subscribedA one-time purchase. No per-seat monthly fee and no usage meter.

Citations verified on-machineAuthority is checked against a local corpus, not recalled from a model’s memory.

The entire matterFull workup across the whole file — not a chat window over one document.

Runs on your workstationA current RTX-class GPU. Designed to run with no internet connection at all.

Start with the governance conversation.

At this scale the deployment is straightforward and the governance is not. Bring risk, IT and the practice leaders who will actually use it.

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Questions firms ask

The answers below are specific to this page’s subject.

How do we deploy across offices?

Per workstation, per office. Each machine is self-contained, which is what removes the central platform as a single point of failure.

How do we know it is producing good work?

Every approve and reject in the review queue is recorded, so acceptance and correction rates per workflow are measurable. That is a stronger measure than usage, which cannot distinguish good work from repeated attempts.

What about firms with existing enterprise AI agreements?

Many will run both. The distinction is per matter: material that cannot be disclosed to a processor runs here.

Is there a central administration console?

Deliberately not one that reaches into matters. Governance is recorded and enforced locally; a central console with access to every matter would reintroduce exactly the risk this architecture removes.

Other pages covering the same ground from a different angle.

On-premise AI for mid-size law firms On-premise legal AI platform Air-gapped AI for law firm data security Confidential legal AI (ABA 1.6) Multi-jurisdiction legal AI (federal + 50 states) In-house legal team private AI

See it run on a real matter.

A briefing walks the whole path — intake, workup, the Adjudicator's pass, and the work product that comes out the other side.