Will an AI be giving me legal advice?

No. Agentic AI does the preparatory work (reading, research, first drafts) at a speed and depth no human team can match. The advice itself comes from a qualified lawyer who has reviewed that work, formed their own view, and is professionally accountable for what you receive.

Is my confidential information used to train AI models?

No. Client material is processed in environments we control, under terms that prohibit training on it. Confidentiality and legal professional privilege are not weakened because a machine assisted with the work; the same duties apply to every tool we use.

What about AI making things up?

Invented citations and confident errors are real failure modes of these systems, which is why no AI output is relied on unverified. Citations are checked against the primary source and drafts are read in full by the signing lawyer. The publicised cases of fabricated authorities involve practitioners filing unreviewed output; our process exists so that cannot happen here.

Is this allowed under the rules that govern lawyers?

Yes. The professional conduct rules require lawyers to act competently and diligently and to supervise work done on a client's behalf; they do not prescribe the tools. Australian courts and regulators have issued guidance on the use of generative AI in legal practice, and the consistent theme is that responsibility stays with the practitioner. That is exactly how we operate.

Why does this matter to me as a client?

Speed, coverage and price. Work that once took a week of billable reading happens in hours. We can calibrate our engagement's level of labour to suit your preferences, instead of just assuming you require manual human oversight for every step (for instance, where business risks are structurally lower). It also means fixed fees become easier to offer on a wider range of legal matters, because our costs do not scale with the hours a matter consumes.

What models do you use?

We primarily use models from Anthropic, Google, Cohere, Mistral and Liquid AI for agentic orchestration. We also situationally deploy custom pipelines with many open weight models from Nvidia, Moonshot, Deepseek, Alibaba, Minimax, Z.ai. We know the industry extremely well and deployments are conducted based on the appropriate balance of capability, data sensitivity and cost.

How do you manage model deployment security?

The same as any other deployment of a technology system: by ensuring we've appropriately mapped the supply chain obligations that are involved in the delivery of the model, and that we understand the data flow and security configuration of the environment that it's running in. Many AI tasks don't need frontier level intelligence, and in those cases we can run local AI on hardware we own to maximise security even further.

What it means to be an
AI-Native law firm

Artificer was built on AI from its first day, not retrofitted from disparate systems bolting on AI add-ons. Let us elaborate a bit further on how an AI-Native law practice actually divides the work between agentic AI and the human touch.

See the division of labour Talk to a human

What AI-native means

An AI-enabled firm buys tools and fits them into workflows designed for paper. An AI-native firm starts the other way around; the practice was designed from day one on the assumption that capable AI would carry the heavy lifting, and every workflow (intake, research, drafting, review) was built on that foundation.

Much of that AI is agentic. An agent is software that can plan and carry out a multi-step task (reading a contract stack, assembling a research file, preparing a first draft) and report back, rather than a chat window waiting for a prompt. Our practice runs on them, and our lawyers supervise them.

What it changes for you

Speed and coverage. Work that once consumed a week of billable reading happens in hours, and nothing gets skimmed; reading everything no longer costs more than reading some of it.

It also changes the economics. Because our costs do not scale with the hours a matter consumes, fixed fees are the default rather than the exception, and our lawyers spend their time on the part you are actually paying for: judgment.

Intake

Intake & scoping.

You brief a lawyer, not a chatbot. While you talk, agents assemble the matter file and surface the relevant background, so the first call ends with a scope instead of a promise to look into it.
Scoping is also where the division of labour is set. The lawyer decides what the agents will carry on this particular matter and what stays in human hands, and the fixed fee you receive reflects that plan rather than an hourly guess.
Research

Research & assembly.

Agents read the contract stack, the legislation and the case law in parallel, and return cited positions rather than findings taken on trust. A lawyer interrogates the result against the sources before it goes anywhere near advice.
The difference is coverage. Where a traditional team might start by slowing ingesting documents based on percieved importance to the case, the agents can read everything and rank what they find, so the lawyer can work efficiently across a wider body of work.
Drafting

Drafting & review.

First drafts come from agents working against our precedents and playbooks, which keeps them consistent and fast. The lawyer who will sign the document then rebuilds it where it matters.
Because a draft costs minutes rather than days, you see options instead of a single take. Alternative positions can be drafted, compared and discarded before the first version ever reaches you.
Sign-off

Judgment & sign-off.

Advice, strategy and anything that leaves the practice stays human. A qualified lawyer has read it, tested it and put their name to it; that is not a courtesy, it is the product.
Nothing in this stage is delegated. The call on what to recommend, what to concede and what to press is made by the person who answers for it, with the preparation behind them rather than between them and you.

Carried by agentic AI

AI Document review at volume. Agents read full contract stacks, data rooms and disclosure sets in hours, flagging the clauses, gaps and anomalies a lawyer needs to see.
AI Legal research & monitoring. First-pass research across legislation, case law and regulator guidance, returned with citations so a lawyer verifies rather than re-derives.
AI First drafts & precedents. Initial drafts produced against our precedent bank and playbooks, consistent across every matter we run.
AI Consistency & proofing checks. Cross-references, defined terms and internal inconsistencies checked mechanically across long documents before a human reads a page.
AI Matter administration. File assembly, version control, deadline tracking and status reporting run as automated workflows rather than billable time.

Supervised & human-only

Shared Advice drafting. Agents prepare the working draft; the advice you receive has been rewritten, tested and signed by the lawyer responsible for it.
Shared Negotiation support. Positions, fallbacks and redlines are modelled by agents; the negotiation itself is run by a human who can read the room.
Never delegated
Human Legal advice & strategy. What you should do, and why, comes from a qualified lawyer who is professionally accountable for the answer.
Human Judgment calls & sign-off. No document, advice or undertaking leaves the practice without a lawyer having read it and put their name to it.
Human Courts, regulators & counterparties. Appearances, regulator engagement and anything said on your behalf are done by a human, every time.

A lawyer answers for everything

Every piece of advice, every document and every undertaking is the act of a qualified legal practitioner, carrying the same professional duties and the same professional indemnity insurance as work produced at any traditional firm. AI does not hold a practising certificate; the people who supervise it do.

Your information stays privileged

Client material is handled in environments we control, under terms that prohibit its use to train public models. Legal professional privilege and our duty of confidentiality apply to AI-assisted work exactly as they apply to any other work product.

Nothing is taken on trust

AI output is treated the way a careful partner treats the work of a capable junior: useful, fast and never relied on unverified. Citations are checked against the primary source, drafts are read in full, and the lawyer who signs has done the reading.

Will an AI be giving me legal advice?

No. Agentic AI does the preparatory work (reading, research, first drafts) at a speed and depth no human team can match. The advice itself comes from a qualified lawyer who has reviewed that work, formed their own view, and is professionally accountable for what you receive.
Is my confidential information used to train AI models?

No. Client material is processed in environments we control, under terms that prohibit training on it. Confidentiality and legal professional privilege are not weakened because a machine assisted with the work; the same duties apply to every tool we use.
What about AI making things up?

Invented citations and confident errors are real failure modes of these systems, which is why no AI output is relied on unverified. Citations are checked against the primary source and drafts are read in full by the signing lawyer. The publicised cases of fabricated authorities involve practitioners filing unreviewed output; our process exists so that cannot happen here.
Is this allowed under the rules that govern lawyers?

Yes. The professional conduct rules require lawyers to act competently and diligently and to supervise work done on a client's behalf; they do not prescribe the tools. Australian courts and regulators have issued guidance on the use of generative AI in legal practice, and the consistent theme is that responsibility stays with the practitioner. That is exactly how we operate.
Why does this matter to me as a client?

Speed, coverage and price. Work that once took a week of billable reading happens in hours. We can calibrate our engagement's level of labour to suit your preferences, instead of just assuming you require manual human oversight for every step (for instance, where business risks are structurally lower). It also means fixed fees become easier to offer on a wider range of legal matters, because our costs do not scale with the hours a matter consumes.
What models do you use?

We primarily use models from Anthropic, Google, Cohere, Mistral and Liquid AI for agentic orchestration. We also situationally deploy custom pipelines with many open weight models from Nvidia, Moonshot, Deepseek, Alibaba, Minimax, Z.ai. We know the industry extremely well and deployments are conducted based on the appropriate balance of capability, data sensitivity and cost.
How do you manage model deployment security?

The same as any other deployment of a technology system: by ensuring we've appropriately mapped the supply chain obligations that are involved in the delivery of the model, and that we understand the data flow and security configuration of the environment that it's running in. Many AI tasks don't need frontier level intelligence, and in those cases we can run local AI on hardware we own to maximise security even further.

Brief us in plain English

Tell us what is going on; no legal framing needed. We scope it with our digital-first intake and come back quickly.

Fixed, fast pricing

Once we agree to help, you receive an online Statement of Work with fixed estimates before any work begins.

Work begins at pace

Agents stand the matter up immediately and a lawyer directs it from the first day. You see progress in days, not billing cycles.

What it means to be an
AI-Native law firm