AI consulting · Legal
AI consulting for law firms and in-house legal teams
Native helps law firms and in-house legal departments put AI agents into the operational work around legal practice: intake, conflict checks, document review, first-pass contract work and billing. Lawyers keep every judgement and every word of advice. The first agent typically runs in production within weeks, inside the systems the firm already uses.
Featuring insights fromShaun Devan · Founder & CEOUpdated · 3 min read
Where AI has an impact in legal
Matter intake
Inquiries turned into a complete intake record with parties, facts and documents attached.
Conflict checks
Every party and affiliate searched, with near matches explained for the conflicts team.
Contract playbook review
Counterparty drafts compared against the firm's or company's standard positions, deviation by deviation.
Document review
Large sets sorted and summarised with page citations, ahead of lawyer review.
Due diligence
Data rooms read and key terms extracted into a findings table for the deal team.
Billing guideline checks
Time entries checked against each client's outside counsel guidelines before the invoice goes.
Knowledge search
Precedents, past advice and templates found by what they say, not by file name.
Legal department triage
Requests from the business sorted, answered from policy where possible and routed to the right lawyer.
Where AI helps a legal practice, and where it does not
Most hours lost in a law firm are not spent on legal reasoning. They go on opening matters, running conflicts, collecting documents, comparing a counterparty's draft against the firm's standard positions, and rewriting time entries so they pass a client's billing guidelines. That work follows rules the firm already has, which makes it the right place for agents.
Agents do not give legal advice and never act for a client on their own. They read, check, compare and draft, and a lawyer reviews and decides. Native builds the systems; the legal judgement stays with your lawyers.
What agents prepare, and what lawyers decide
| Work | Agent | Lawyer or staff |
|---|---|---|
| New matter intake | Collects the facts, parties and documents and drafts the intake record | Accepts the matter |
| Conflict checks | Searches every party and related entity, with near matches explained | Clears or escalates |
| Contract first pass | Compares the draft against your playbook and marks every deviation | Negotiates and signs off |
| Document review | Sorts, tags and summarises large sets, citing the page for every point | Makes the privilege and relevance calls |
| Billing review | Checks time entries against each client's guidelines before invoices go out | Approves the bill |
Confidentiality and professional duties
Client confidentiality and privilege shape every design choice. Documents stay in the firm's own document management system and accounts, agents see only the matters they are working on, and nothing is used to train a model. The ABA's Formal Opinion 512 sets out what lawyers owe clients when they use generative AI, including competence, confidentiality and reasonable fees, and the workflows are built so the firm can meet it.
Every agent output carries its source: the clause it compared, the page it summarised, the guideline it applied. A lawyer can check any point in seconds, which is what makes the work usable.
The systems we work with
Agents work inside the practice and document systems you already run, such as iManage, NetDocuments, Clio, Intapp, Aderant, Elite 3E and Relativity, and with LEDES e-billing for corporate clients. In-house teams usually add a contract lifecycle tool and an intake form or shared inbox, and the agents read from those too.
We start with one high-volume workflow, often intake and conflicts or billing review, and map how it runs today. That agent is live within weeks. Within months the practice support, finance and knowledge teams work with agents every day, and your staff are trained to maintain the playbooks the agents follow.
How to measure the impact
- Time from first contact to an opened, conflict-cleared matter
- Contract turnaround on standard agreements
- Invoice rejections and write-downs from billing guideline breaches
- Lawyer hours spent on non-billable admin
- Review hours per thousand documents
Case study · A mid-sized commercial law firm
A commercial law firm cut the time to open a matter and stopped losing fees to billing rejections.
Native helped a mid-sized commercial firm put agents on new matter intake, conflict checks and pre-bill review. Matters open in a day instead of most of a week, and invoices go out already checked against each client's billing guidelines.
The challenge
Intake ran through email and a shared spreadsheet, and the conflicts team re-keyed every party by hand. Several corporate clients rejected invoices over time entries that broke their billing rules, and partners spent evenings rewriting narratives before each bill run.What we built
- An intake agent that turns each inquiry into a complete record, runs every party through the conflicts database and explains near matches for the conflicts team to clear.
- A pre-bill agent that checks every time entry against the client's guidelines and drafts a compliant narrative for the timekeeper to accept.
- A record of every check, so the firm can show any client how an entry was reviewed.
The result
New matters opened faster, the conflicts team stopped re-keying, and partners got their evenings back at the end of each billing cycle.Frequently asked questions
How are law firms using AI?
For the operational work around practice: intake, conflict checks, document review, contract comparison against a playbook, due diligence and billing review. Lawyers review the output and make every legal judgement.
Can AI give legal advice?
No. Agents prepare and check work for lawyers; they do not advise clients. Every output goes to a lawyer, with the source of each point cited so it can be verified.
Is it safe to use AI with confidential client documents?
It can be, when documents stay in the firm's own systems and accounts, each agent sees only the matters it works on, nothing is used to train a model, and every action is logged.
What should a law firm automate first with AI?
Usually intake and conflicts, or pre-bill review. Both are high volume, follow written rules and show their impact within weeks without touching legal judgement.
What ethics rules apply to lawyers using AI?
In the US, the ABA's Formal Opinion 512 covers competence, confidentiality, supervision, communication and fees when lawyers use generative AI, and many state bars have issued their own guidance.