Your clients’ confidences never leave your building.
On-premise AI for law firms and legal teams. Drafting, research, and document analysis run on a node inside your own office — bound by your rules, your confidentiality obligations, and your approval. No cloud, no per-seat invoices, no vendor deciding what the AI will discuss.
Subscribing to cloud AI
- Client material processed on a vendor’s infrastructure
- Every attorney and paralegal is another monthly seat
- A vendor content policy can limit what the AI will do for your matter
- Audit trail belongs to the provider, not to you
Running it on your premises
- Confidential client information stays inside your control
- One flat monthly fee — unlimited users, unlimited use
- Open-weight models: no provider policy, no rate limits
- Full audit trail and approval workflow, owned by your firm
The work it does with you
Built around the way legal work actually happens — matters, engagement letters, redlines, diligence. The AI drafts and analyzes; you review and decide.
Draft from your templates
Letters, memos, and engagement letters generated on your letterhead, preserving your language and formatting.
- No invented names, dates, or facts — ever
- Editable documents delivered back to you
Research on your corpus
Ask across your own documents and get answers with citations. “Find every termination clause in the Acme agreements” — answered from your files, pointed back to the source.
- Full-text search across your matters
- Every statement tied to a source file
Matter intelligence
The AI as your file clerk: everything on a matter, timelines, latest versions, naming conventions enforced.
- “Show me everything on Matter X” in seconds
- Version tracking and matter timelines
Analyze & extract
Long documents made manageable: summaries with paragraph cites, redline comparisons, and structured extraction of counterparties, dates, amounts into a spreadsheet.
- One-page summaries with citations
- Diligence extracted to structured output
Oversight & control
You stay in charge. Partner review queues, draft-to-final approval, version control, and a complete log of what the AI did, when, and why.
- Review and approval workflow
- Immutable rules file the AI cannot change
- Audit log for accountability
Confidential by architecture
The node sits in your building. Nothing is transmitted to a third-party vendor, and air-gap installs run fully offline.
- Your network, your hardware, your control
- Air-gap capable
Your rules, loaded every session
Every session starts with your firm’s ground rules already in place — confidentiality, scope, document handling, prohibitions. The rules are a file on your node, loaded automatically, impossible for the AI to modify. No copy-paste, no remembering, no trusting the AI to behave. Upload once. Loaded forever. The AI is an associate on a strict leash: it drafts and analyzes, you decide.
Rent an AI, and it answers to someone else.
Own one, and it answers to you.
This is the whole point. When you buy AI from the cloud, you’re not just paying per seat — you’re accepting a control paradigm. Client and privileged material leaves your building, and a vendor’s content rules and its terms of use sit between you and your judgment, and you have no vote. A node in your office reverses that. Your confidential data stays in your building; your rules govern the machine; and you keep control of the judgment. It’s your hardware — bought, owned, titled to you. The machine is the tool, and the attorney is the professional.
The biggest firms are already buying their own AI
Latham & Watkins — the US’s second-largest law firm, with $8.3bn in revenue — made headlines this month for a move that sounds like a boutique’s: it bought its own Nvidia GPU servers and is fine-tuning open-weight models, keeping client data entirely within its own systems. It is the first public example of a large firm doing so.
“Sometimes we may have information that is so sensitive, client information that we really want to protect, we don’t want to put it to any cloud vendor.”— Rene Mendoza, Chief Information Officer, Latham & Watkins
Latham cites two of the same reasons we do: keeping clients’ sensitive data off any cloud vendor, and refusing to depend on a single provider — its CIO says “we are not hitching our wagon to one particular company” — plus the flexibility to choose the right model for each task.
That logic scales straight down to a small practice. You don’t need a data centre or a team of machine-learning engineers; you need a node in your office and the same principle — your clients’ confidences, your rules, and no vendor sitting between you and your judgment.