// INDUSTRY
AI for Legal Firms
Attorney-client privilege is a property of communications, not a vendor's promise. We build private AI systems that run inside the firm's own infrastructure — so client confidences, work product, and privileged communications stay where they belong.
The privilege problem with cloud AI
Every time a lawyer pastes client information into a cloud AI service, the firm is making an argument that the information retained privilege despite being disclosed to a third party. That argument is untested in most jurisdictions, and a number of state bar opinions have already flagged it as problematic. The defensible architecture is the one where no privileged material ever leaves the firm's network.
Local AI deployment solves this cleanly: the model runs on the firm's servers, inference happens entirely inside the firm's boundary, and no data is ever sent to a third party.
What we build for law firms
Contract analysis and review
Clause extraction, comparison against playbook positions, redlines against prior versions, obligation and risk summarization. Runs on PDFs, Word documents, and scanned originals. Attorneys stay in the loop for judgment; the AI handles the extraction and the comparison. See RAG pipelines.
Case and statute research
RAG over the firm's internal knowledge base (briefs, memos, prior matters) combined with authorized external sources. Citations to the exact paragraph of the source document. The AI proposes; the attorney verifies. No hallucinated case citations in a filed brief — citation validation is enforced at the system level.
Document review and discovery
First-pass document review for responsiveness, privilege, and issue coding. Not replacing the review attorney — giving them leverage on the volume that comes out of a modern eDiscovery process. Every document's classification is explainable (with the relevant text passages highlighted); the attorney can agree, disagree, or override.
Drafting and boilerplate
Motions, letters, memos, and discovery requests drafted from firm templates and prior work product. Matching the voice and structure of the partner or practice group. The draft is a starting point; the attorney edits.
Knowledge management
Firm-internal Q&A system over memos, briefs, research archives, and precedent files. An associate asks "have we dealt with an indemnification clause like this one before?" and gets a list of prior matters with the relevant language and the outcome.
Deployment model
Most law-firm deployments we ship run on a small server rack inside the firm's office or colocation — usually one or two GPU workstations for firms under 100 attorneys, a small cluster for larger firms. No cloud dependency. No external AI vendor in the inference path. The firm owns the hardware, the model weights, the logs, and the audit trail. See our local AI deployment service and hardware guide.
What the AI won't do
- It won't give legal advice to clients — it's a tool for attorneys, not a chatbot for users.
- It won't file anything, sign anything, or send external communication without attorney review.
- It won't invent case citations — citation validation is enforced at the system level; outputs with unverifiable citations are blocked before they reach the attorney.
- It won't replace the associate-training pathway. It changes what associates do, but firms that use it as a reason to hire fewer associates tend to produce lawyers who can't function without it.
Ethics and professional responsibility
We build these systems in a way that supports your compliance with Model Rules 1.1 (competence), 1.6 (confidentiality), 5.3 (supervision of non-lawyer assistants), and 8.4 (candor). The documentation and audit trail we deliver are designed to be referenced in a professional-responsibility inquiry if one ever happens. We're not substituting for your ethics counsel — we're giving your ethics counsel something defensible to review.
Where to start
A free AI Readiness Assessment (30 minutes) surfaces the highest-ROI workflows for your practice areas. For firm-wide deployments involving IT, knowledge management, and firm-management buy-in, Tier 02 Deep Discovery ($7,500, two weeks) delivers a written implementation roadmap credited toward any build.
Frequently asked questions
Does using AI with client data waive privilege?
The safe answer: yes, it might, and state bars have started flagging it. Disclosure to a third-party vendor is disclosure, and a vendor's "we don't train on your data" contractual promise is not the same as privilege preservation. Running the AI inside the firm's own infrastructure — where no client data ever reaches an external party — avoids the question entirely. That's the architecture we default to for law firms.
Can AI hallucinate case citations?
Out of the box, yes — and this has already gotten lawyers sanctioned. The systems we build enforce citation validation: every proposed citation is verified against an authoritative source (internal precedent database or authorized legal research service) before the output is returned to the attorney. Unverifiable citations are blocked, not shipped.
What about eDiscovery? Do you build TAR systems?
We build first-pass document review workflows (responsiveness, privilege, issue coding) using LLMs. That's not the same as a certified TAR 1.0 / TAR 2.0 predictive coding platform — if your matter requires TAR in the formal sense, we'll point you at appropriate vendors. For the many matters where "intelligent assist" is what's actually needed, our LLM-based approach ships faster and produces more explainable classifications.
How is this different from Harvey or Lexis+ AI?
Those are vertical-SaaS products with strong features and a cloud hosting model. Our builds are private, on the firm's infrastructure, with the firm controlling models, prompts, and logs. For firms where the confidentiality architecture matters more than buying off-the-shelf features, we're the better fit. For firms that are comfortable with vendor-hosted and want features over control, those products are fine.
Will this replace associates?
No. It will change what junior attorneys do — less pure document review and first-pass research, more supervision, verification, and higher-leverage work — but firms that try to skip the associate-training pathway tend to produce mid-level attorneys who can't function without the tool. AI is leverage for a trained attorney. It isn't a substitute for training.
Ready to start?
Book a free 30-minute AI Readiness Assessment. No pitch deck. No retainer ask. Just a working session to map your stack and surface the two or three highest-ROI AI interventions for your situation.