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AI for law firms

AI for law firms that works inside the matter.

Most AI for law firms is a chat window beside the real work. ModulawAI puts the AI where the work already is: research with linked citations attached to the matter, drafting as track changes in Word, one question asked across a whole bundle, and agents that check deadlines when nobody is looking. All of it under rules the firm sets, with an audit trail on every action.

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Where AI earns its place

Four jobs, done in the file rather than beside it.

A firm does not need AI in general. It needs the reading, drafting, checking and chasing done faster without a second system to copy the result into. These are the four places the time actually goes.

Research with citations

Answers grounded in retrieved primary law across eight jurisdictions, every authority linked and status-checked, saved to the matter it supports. See the AI legal assistant.

Drafting in Word

Redlines arrive as native track changes and findings as comments, inside the document the associate is already working in. See the Word add-in.

Bulk document review

One question asked across two hundred contracts, answered as a grid with every cell citing its clause, exported to Excel. See AI contract review.

Agents on the caseload

Background agents flag an unactioned deadline, a clause that conflicts with an earlier one, or what moved on a matter this week, and raise it in the file. See workflows and agents.

Buying it

What separates AI a firm can demo from AI a firm can deploy.

Grounding

Does it cite, or does it remember?

A general model answers from memory and will invent a case name that sounds right. Every sanctions decision involving AI-drafted filings has come from that failure. ModulawAI retrieves the statute or judgment first, answers from the retrieved text, and links each citation, so a partner can verify a proposition in the time it takes to click. The model behind it is Claude, run through Amazon Bedrock, and it never trains on your data.

Control

Who decides what the AI is allowed to do?

In ModulawAI the firm does. Agent skills are scoped per agent, critical actions can require a named approver before they execute, role-based permissions govern who sees which matters, and every input, output and tool call is logged with a timestamp and the human who reviewed it. That is the difference between a tool an associate uses quietly and a capability the firm can stand behind in front of a client or a regulator.

Integration

Where does the output land?

If the answer is “we copy it into the practice management system”, the AI is a feature, not a foundation. ModulawAI is the practice management system: matters, calendar, time capture, billing, client portal and CRM sit in the same workspace as the AI, so research attaches to the file, the time is captured against the client, and the draft is the document in the matter. Firms that keep another system can reach ModulawAI through a scoped REST API and an MCP server. See legal AI software for the full platform.

Coverage

Which law does it actually know?

ModulawAI is explicit about it: the United States, the United Kingdom, Canada, the European Union, Nigeria, Ghana, Kenya and South Africa, each with linked primary sources. A firm with a cross-border matter runs one query and sees the comparative authority, rather than switching between a domestic database and guesswork.

Rolling it out

A four-week adoption sequence that firms actually finish.

  • Week one: research. Pick three questions the firm has already researched. Run them, check the citations against the memo, and decide whether the grounding is good enough to trust. This is the only test that matters.
  • Week two: drafting. Install the Word add-in for two fee earners. Have them redline a live agreement with it and keep the track changes on. Compare the time to the last similar draft.
  • Week three: review. Take a bundle you have already reviewed, put it through tabular review with the same questions, and reconcile the grid against your own answers.
  • Week four: agents. Turn on one background agent, deadline monitoring, with approvals required. Watch what it raises for a fortnight before widening its skills.
  • Throughout: write down the rules. Which tasks may run unattended, who approves the rest, and what the client is told. ModulawAI enforces the rules; the firm still has to set them.

Evidence

What the adoption data actually shows.

The question of whether firms will adopt AI has been settled faster than most predicted. Clio’s 2025 Legal Trends Report, published on 16 October 2025, found 79% of legal professionals using AI tools in their daily work, against 19% in 2023. The American Bar Association’s 2024 Legal Technology Survey Report, based on 512 attorneys in private practice, put firm-level adoption at 30%, up from 11% the previous year, with the gap by size stark: 46% at firms of 100 or more attorneys against 18% among solo practitioners. Over half of respondents, 54%, named saving time as the primary advantage.

On the return side, Thomson Reuters’ Future of Professionals 2025 report estimates AI will free roughly 240 hours per professional per year, up from an estimated 200 in 2024, at an average annual value of about $19,000 per professional. Clio’s data links adoption to growth rather than just efficiency: firms with wide AI adoption were nearly three times more likely to report revenue growth than firms that had not adopted it. Treat all of these as directional rather than precise. They are self-reported surveys by vendors and analysts with an interest in the answer, which is worth saying plainly on a vendor’s own website.

The risk record, which is the other half of the story

Damien Charlotin’s AI Hallucination Cases database, a public tracker of court decisions involving fabricated AI-generated content, recorded 2,041 cases as at 14 September 2026, spanning more than 40 jurisdictions, with 1,395 in the United States, 217 in Canada and 111 in Australia. The originating case remains Mata v Avianca, Inc., 678 F. Supp. 3d 443 (S.D.N.Y. 2023), in which the court sanctioned two attorneys and their firm $5,000 in June 2023 after six fabricated decisions were cited in a brief. In England and Wales the Divisional Court addressed the same problem in Ayinde v London Borough of Haringey and Al-Haroun v Qatar National Bank [2025] EWHC 1383 (Admin), handed down 6 June 2025, where grounds for judicial review cited five non-existent authorities, wasted costs orders of £2,000 plus VAT were made against each of two lawyers, and both were ordered to report themselves to their regulator.

Every one of those failures has the same cause: an answer produced from a model’s memory rather than from a retrieved source, and filed without the citation being opened. It is a procurement question before it is a training question, which is why the grounding test on this page comes before the feature list.

The use case buyers do not think to ask for: building the tool itself

Every firm has a short list of small tools it never got built. A calculator for the way this practice actually quotes. An intake form that asks the six questions the clerks always have to chase. A limitation period checker. A scenario model to put in front of a client in a settlement meeting. A dashboard showing which matters have gone quiet. Each one is a week of somebody’s time, which means none of them exists, and the work is done in a spreadsheet that one person understands.

The category’s answer to this is workflow automation, and it is a good answer as far as it goes. Harvey’s Agent Builder and Legora’s Workflows let a firm assemble multi-step processes in natural language, and Harvey reported more than 25,000 customer built workflows by February 2026 (harvey.ai). They are pipelines: documents go in, and documents, tables and answers come out. None of them gives you a running application.

ModulawAI includes Canvas, an interactive artifact builder that turns a plain description into working software. Describe the calculator, the form, the checker or the dashboard in ordinary words, and you get a real page you can open and use, usually in a few minutes, without writing code or raising a development request. The nearest equivalents are general assistants rather than legal products: Claude Artifacts and ChatGPT Canvas do this well, and neither knows your matters, your precedent library or the jurisdictions you practise in.

Two limits belong next to that claim. Canvas apps run in a sealed sandbox on an opaque origin with no network access at all, which is a deliberate security decision: the app cannot reach your matter file, your firm’s data, your cookies or any outside service, so whatever it needs is typed in. And they are internal tools today. Publishing one to a public address for clients to use is on the roadmap and is not shipped. Judge it as a way to get bespoke software in an afternoon rather than never, not as a replacement for anything you buy.

What the regulators require

  • United States. ABA Formal Opinion 512, issued 29 July 2024, is the first formal ethics guidance on generative AI. It requires lawyers to understand the benefits and risks of the tools they use, to assess before entering client information whether that information could be disclosed to or accessed by others, to ensure time billed reflects time actually spent when using AI, and to supervise non-lawyers and third parties using these tools. It also says the cost of accessing a generative AI tool is overhead and should not be billed to the client as a disbursement.
  • England and Wales. The SRA’s warning notice on the misuse of AI, published 17 August 2026, states that solicitors remain accountable for all work and advice delivered to clients whether or not AI has been used in its preparation, that reliance on an AI output would not be a suitable defence, and that client information should only be entered into AI systems where appropriate contractual, technical and organisational safeguards are in place. Failing to have proper regard to the notice puts a solicitor at risk of disciplinary action.
  • Both. The common thread is verification, supervision and confidentiality. None of that is satisfied by a tool that cannot show where an answer came from, cannot restrict who sees which matter, and cannot produce a log of who reviewed what.

Sources

FAQ

Questions, addressed.

What can AI actually do for a law firm today?

Four things reliably: legal research with cited authorities, first-draft and redline work in Word, extraction and comparison across large document sets, and monitoring of deadlines and matter activity. Each of those is measurable against work the firm has already done, which is how a firm should evaluate any vendor.

Is AI for law firms safe to use with client data?

It depends on the vendor. In ModulawAI, client data is encrypted in transit and at rest, held in AWS data centres, and never used to train models. Access is role-based, and every AI action is logged with the human who reviewed it. Firms should ask any vendor those four questions before uploading a single file.

Does the AI replace associates?

No. It removes the parts of associate work that were never legal judgement: the finding, the first read, the reformatting, the chasing. The judgement about what to argue and what to advise stays with the lawyer, which is why every output in ModulawAI is reviewable, citable and attributable.

How is AI for law firms priced?

ModulawAI is priced per seat with usage-based credits, so a two-partner firm and a two-hundred-lawyer firm pay for what they use. See pricing.

Can a small firm use the same AI as a large one?

Yes. ModulawAI serves solo practitioners through to enterprise firms with departments and delegated authority. The AI capability is the same at every tier; what changes is the permission and approval structure around it.

Related

Keep reading.

Test it on work you have already done.

Book a demo and bring a research memo, a redlined draft, or a bundle you have already reviewed.

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