AI for law firms: an answerable brief bank, then a private copilot

Client: an established Caribbean law firm founded in 1992. The firm remains anonymous here. Axys may reference the engagement in its portfolio, but we do not name the client or publish its confidential material without explicit approval.

What lawyers on the ground actually say

Ask a practicing lawyer about firm AI and you do not hear “legal knowledge base.” You hear three things.

First: I will get sanctioned for a fake cite. That is not a 2023 news cycle. In 2026, Kansas counsel were publicly admonished for ChatGPT citations nobody checked. A California dog-custody appeal picked up a fake Supreme Court case that started as a Reddit post. A Sixth Circuit panel sanctioned counsel over a brief whose file name was “CoCounsel Skill Results.” Even a Westlaw-grounded tool invented quotations. The street rule is not “buy a safer logo.” It is check every cite.

Second: we paid for it and nobody uses it. On LinkedIn, the legal-AI seats are a press release. On Reddit they are “no value add compared to a $20 ChatGPT” and “the only thing it does well is summarizing.” One reported r/legaltech line: the associates hated Harvey, the partners bought it because they think it’s magic. An appellate solo cancelled CoCounsel after 90 days — “not worth $500 a month on top of Westlaw” — after a memo cited a California case the Supreme Court had already reversed. Associates who hit one confident error stop opening the tab.

Third: how did we handle this last time? The brief bank is in iManage, a shared drive, someone’s inbox. The expensive tools search a vendor database. They do not search that firm’s last ten years. When the person who knows where the memo lives leaves, the memo leaves with them.

This case is those three sentences, built in order, for one 30+ year Caribbean practice. See also AI for law firms if you want the offer without the engagement diary.

The job they actually want

Not a better Westlaw. A safe place to put the firm’s own files into an LLM. First-pass review and issue-spotting a human still checks. Answers from the brief bank, not from the open web. Something that can live next to Word and the DMS, not another portal partners announce and associates ignore.

The brief-bank problem is worse than “search is bad.” Knowledge managers say files often never enter the DMS until the matter closes — years later. So “just connect Harvey to iManage” is a fantasy if the work product is still in an inbox. That is why this engagement starts with a corpus assessment, not a copilot demo.

Privilege is the other half. Carolyn Elefant’s rule of thumb: treat consumer ChatGPT like posting to a listserv. Courts are already saying the quiet part. In Heppner (S.D.N.Y., Feb 2026) Judge Rakoff wrote he was “not seeing remotely any basis for any claim of attorney-client privilege” once the client had pasted the matter into an AI chatbot. A free tab is not a place for client files. ChatGPT is fine for marketing and a first-draft email. It is not a research database and it is not the firm’s archive.

The local rule is no longer optional. Trinidad and Tobago’s Practice Direction on generative AI, in force from 8 July 2026, requires a certificate naming the tool if AI touched a court document, independent verification of every authority, and a ban on AI-generated affidavits and witness statements. Caribbean counsel who file here cannot treat “the model said so” as a workflow. Judiciary media release.

Why we refused “just turn on a copilot”

A copilot that drafts from the open web, or from an unreviewed dump of PDFs, will sound fluent and still be wrong. That is how firms get sanctioned. A copilot that can see every matter, with no walls, will leak. A copilot that cannot see the brief bank will invent one.

So we refused the usual sequence. We did not start with a teammate. We made the expertise legible, then findable, then — only then — draftable, with a lawyer still in the chair. Firms that care about control are making the same bet in public (building on their own stack, their own guardrails, their own judgement). The Reddit version is cruder and true enough: attach your own archive, get a zero-retention deal, do not outsource the walls.

Adams & Adams said the quiet part on the record: even in a commercial department, “AI has to be babysat.” That is not a slur. It is the operating model. We are building a copilot you can babysit — not one you file.

The sequence: tool, then system, then teammate

Each phase creates the next. A babysat copilot is unsafe on an unstructured archive. A brief bank cannot compound if the public and private information architecture is a mess. The order is the product.

Phase 1 · AI as a tool — a site the engines can actually cite

Status: delivered. This was not “a nicer website,” and it is not a GEO play sold as lost-client panic. Practitioners are not describing files lost because ChatGPT failed to recommend them. They are describing a public presence that people and machines cannot parse. Phase 1 gave the firm a structured account of who it is and which articles are safe to quote. We do not claim the firm now appears in ChatGPT recommendations.

What shipped:

• A faster public foundation with clear entity and service structure — so a practice area, a bio, and an article are distinguishable to a crawler.
• Structured templates and citation-ready metadata on the pages meant to be quoted.
• A legal publishing layer for answer-first articles: the question a client actually asks, then the firm’s position, then the source. That is the format answer engines already lift from directories. The firm can now write in it.
• An editorial loop where AI accelerated research, scaffolding, and drafts, and humans kept information architecture, legal positioning, factual review, and the publish button.

This is the outward half of Ask. It is also the cheapest test of whether the firm will operate a publishing standard. Later phases depend on that habit.

Phase 2 · AI as a system — make the brief bank answerable

Status: commissioned and in progress. This is the inward problem. The job is not “add AI to the DMS.” It is: a lawyer can ask how we handled this, and get the memo, the opinion, or the template, with the source attached, inside the walls that already exist.

In practice:

• A corpus assessment: what the firm actually owns, what is current, what is privileged, what must never be ingested.
• Owners, access boundaries, versioning, and provenance — so a retrieved passage traces to a document, not to “the model.”
• A content engine that writes new public articles from approved knowledge, not from a blank prompt.
• Retrieval with citations. Same RAG pattern we use for other businesses, constrained for legal work.

This phase did not start with a PDF dump. It started with a project-specific data-handling and AI-use agreement: confidentiality, purpose limitation, provider controls, ownership, deletion, privilege, audit rights. For a law firm those controls are the system. See governance and on-premise options.

Phase 3 · AI as a teammate — a copilot you still check

Status: designed, not a production outcome. The third phase is a private copilot — research, retrieval, drafting, review — allowed to work only from the approved archive. It must keep the walls, attach the source, and leave a lawyer on anything that may be published, filed, or sent to a client.

That is Act in a legal setting: a first draft, a chronology, an intake summary, a research pack. It is not autonomous legal judgment. It is not a filing. Implementation follows the brief bank and the evaluation set. We will not describe it as live until a lawyer is using it under those gates.

What is verified today

• The relationship is an active paid engagement, not a proposal.
• The public-site and publishing layer is delivered.
• The brief bank / legal knowledge base and content engine are commercially commissioned and are the active work.
• The data-handling and AI-use framework was in place before corpus ingestion.
• The copilot’s review gates — human approval, retrieval scopes, versioning, review states, auditability — are written. They are a design, not a go-live claim.

What we are not claiming yet

No time-saved percentages. No retrieval-accuracy scores. No “the firm now appears in ChatGPT.” No revenue impact. Those need a baseline and a measured window. The plan covers site and schema health, documents ingested and residual error, retrieval accuracy on an eval set, and drafting or research time against a clock we actually ran. Whether anyone starts citing the public articles is a later measurement, not a result on this page.

Who this is for

Any expertise-led practice whose authority is trapped in a legacy site and a scattered archive, and that cannot put client material into a public model. Law is the sharpest version — especially where a court now requires you to certify the tool and verify every cite, as Trinidad and Tobago does. Accounting and advisory hit the same wall later. Regional constraints are on the Caribbean practice page. The deployment choice is cloud vs on-premise.

If the firm is still deciding where to start, the honest first step is not a copilot demo. It is a fixed-fee readiness assessment: what you actually own, what is safe to ingest, and which build is worth funding.

The reusable lesson

The moat is not the model. It is the brief bank, the walls, the review standard, and the habit of checking every cite. Make the expertise legible, then findable, then draftable. Own the layer. Babysit anything that matters.