AI for law firms and professional services

Legal

Who we work with in professional services

We will say the uncomfortable part first: we do not have a published law-firm case study yet. What we bring is production AI in regulated settings — HIPAA-compliant work for healthcare, governed assistants for real estate and insurance — and a way of building that maps directly onto professional responsibility: the assistant answers only from approved sources, cites them, refuses what it should, logs everything, and a professional reviews output before a client sees it. If that is the standard you need, the pilot below is designed to prove it on your own matters in four to six weeks.

• Small and mid-size law firms losing intake leads to slow callbacks and manual conflict checks
• Litigation and transactional practices with document volumes that outgrew the associates assigned to them
• Accounting, consulting, and engineering firms with the same knowledge-retrieval problem under a different name
• Firms whose clients or malpractice carriers require data to stay private

AI use cases for law firms

• Client intake and conflict checks from $6k
  Collects matter details on your site or by phone, runs a preliminary conflict search against your records, and schedules the consult — with attorney review before engagement.
• Matter and precedent knowledge assistant from $8k
  Answers "how did we handle this before" from your own briefs, memos, and templates, with citations to the source document.
• Document review support from $10k
  First-pass classification, clause extraction, and issue flagging across discovery or diligence sets for associate review.
• Drafting support in your DMS from $10k
  First drafts from your templates and prior work product, inside iManage, NetDocuments, or Clio, never sent without review.
• Client status and billing assistant from $5k
  Answers status, invoice, and scheduling questions from your practice management data; routes substantive questions to the team.
• Private deployment from $15k
  Models and data in your cloud tenant or on-premise, with no training on your data and full audit logs — for firms whose clients require it.

Confidentiality, privilege, and professional responsibility

Legal AI is governed by duties of competence, confidentiality, and supervision, and by your malpractice carrier's questions. We design for all three: data processing agreements with every provider, no training on your data, private deployment where required, source citations on every answer, explicit refusal boundaries, immutable logs, and human review gates before anything leaves the firm. The on-premise versus cloud trade-offs are laid out in private AI: on-premise vs cloud LLMs; how to vet any AI vendor is in how to evaluate an AI development company.

A four-to-six-week pilot

We start with one workflow — usually intake or a knowledge assistant on a defined practice area — on a scoped set of matters, in draft-and-review mode. We measure accuracy against attorney judgments, time saved, and refusal behaviour, and you decide whether to expand. Pilots run $6k–$15k with a written fixed quote and are structured so nothing reaches a client without professional review.

What legal AI costs in 2026

Intake and conflict-check assistants $6k–$12k; knowledge assistants $8k–$20k depending on document volume and cleanup; document review support $10k–$30k; drafting support $10k–$25k; private deployment adds $15k–$40k plus infrastructure. Running costs are typically $300–$1,500 a month. Detail in the AI agent cost guide and RAG vs fine-tuning.

Where we work with law and professional services firms

We deliver on Pacific hours from our California base and meet in person across Los Angeles, Orange County, San Diego, Sacramento, and the Bay Area; East Coast and international clients work with us remotely on US contracts with full IP assignment. Professional services and legal are among the industries we serve most in Glendale, Pasadena, and Los Angeles.