Trust & Disclosure

How We Use AI

We use AI on your matters the way you wish every firm did: on our own hardware, under a named lawyer's signature, with every citation machine-verified — and we can prove all three.

Where your information lives

Privileged matter work runs on computers we own. Our AI stack is self-hosted open-source software (LQ.AI, Apache-2.0 — yes, you can read the code) running open-weight models on firm hardware. For privileged work, nothing leaves our perimeter: no cloud AI provider receives your documents, and there is nothing to “opt out” of because no third party is involved.

A hard technical floor, not a policy promise. Our gateway enforces a per-matter confidentiality tier: work marked privileged is refused routing to any external service — HTTP 403, logged. Policy is what we promise; architecture is what we can't accidentally break.

Consumer AI tools are banned for client work — by that same architecture and by written protocol. (Independent research found 17 of 20 consumer chatbots leaking data to third parties; we treat that as disqualifying, not as a settings problem.)

Where we use advanced cloud AI at all (abstract legal research, never client facts), it runs under a written Clean-Room Protocol: no client identifiers or identifying fact patterns, ever.

How we keep the AI honest

Every citation is verified character-for-character against the source document before a human ever relies on it; unverified citations are flagged red, not smoothed over. Your deliverables can include the verification log.

We benchmark before we trust. Our review tooling is tested against a 50-document gold corpus with known defects; we know its measured recall and its failure modes, and our lawyer review is calibrated to them. When we upgrade models, we re-run the benchmark first — upgrades are measured, not assumed.

A licensed lawyer signs everything. AI does first-pass work; accountability never moves. This is also our regulatory posture under California's emerging AI ethics rules — our verification logs are built to satisfy them.

What this means for you

Fixed prices, faster turnarounds

AI efficiency shows up in your invoice, not just our margin.

EU/Spain matters

The same architecture satisfies GDPR residency and professional-secrecy duties structurally — your data can be processed entirely within our EU footprint on request.

Auditable on request

Engagement clients may request our AI-use summary for a matter — which systems touched it, at which confidentiality tier, with the citation-verification record.

The disclosure you should expect from any firm

Ask your law firms these four questions. Our answers:

1. Which AI vendors receive our documents?

For privileged work: none.

2. Can you prove it?

Yes — routing logs, per matter.

3. How do you catch AI errors?

Machine-verified citations + benchmarked recall + lawyer sign-off.

4. Who is accountable?

The signing attorney. Always.

Open source & attribution

Our AI stack's open-source foundation, LQ.AI (Apache-2.0), is authored by Kevin Keller and the LegalQuants community; we contribute back. Related: engagement terms.