Start a project
The problem

Public AI tools and attorney-client privilege are a bad mix.

Most "AI for lawyers" SaaS products send work product through public LLM APIs whose data-handling terms don't match what your engagement letter promises. Some bar associations have started issuing guidance specifically on this. The convenience trade-off — getting AI assistance at the cost of confidentiality you can't fully audit — is one most thoughtful practitioners aren't willing to make.

Privilege exposure

Sending client communications through public LLM APIs may waive privilege in ways that aren't apparent until discovery.

Bar guidance is moving

Multiple state bars have begun issuing AI-specific advisory opinions. The compliance ground is shifting under SaaS tools faster than they can update.

Engagement letter mismatch

Most engagement letters promise confidentiality your AI vendor's TOS doesn't actually preserve.

Use cases

Three places we typically start.

Every engagement begins with a conversation about your specific bottleneck — but these are the patterns we see most often. Each is a fixed-scope, fixed-fee engagement, typically 4-8 weeks.

Use case 1

Intake and conflict-check automation

AI agent that handles initial inbound inquiries, runs structured conflict checks against your matter database, drafts the engagement letter when a matter clears. Saves 5-10 hours per week of attorney time on intake calls that should never have been attorney time.

Use case 2

Document drafting copilot

Reads your firm's precedent library, drafts initial versions of routine documents (NDAs, engagement letters, demand letters, simple motions) following your firm's style. Cuts first-draft time by 60-70% — review still needed, but the blank-page problem is gone.

Use case 3

Research and citation assistant

Reviews case law and statutes against a research question, surfaces relevant authority with proper Bluebook citations, flags negative treatment. Faster than associates and Westlaw combined for the first pass — attorneys still validate before relying.

How it works

From first call to deployed system in 4-8 weeks.

Step 1

Bottleneck conversation

30-minute call to understand the specific workflow you want to automate. We tell you whether AI is the right answer — sometimes it isn't, and we say so.

Step 2

Fixed-scope engagement letter

Engagement letter with fixed scope, fixed fee, fixed timeline. No hourly billing, no scope creep, no surprises. Typical range $15K–$35K depending on complexity.

Step 3

Deploy in your environment

System runs in your infrastructure, on your data, behind your access controls. We hand off documentation, training, and a runbook for your team to maintain it.

Curious whether your bottleneck fits?

30-minute call, no pitch. We'll tell you honestly whether what you're describing is a good fit for a fixed-scope AI engagement — or whether you're better off with a different solution entirely.