AI automation for legal & law firms.

Legal is a large, tightly regulated industry running on manual labor. IBISWorld put the US law-firm market at USD 417.9 billion in 2024, up 5.8 percent, and the Canadian market at USD 21.9 billion. Growth is coming with pressure: consolidation, alternative legal service providers, and tech-driven platforms are all competing on speed and price, and clients increasingly expect the responsiveness they get from every other service they buy. The firms pulling ahead are the ones turning routine, rules-based work over to software so their lawyers spend billable time on judgment, not administration.

The economics of the billable hour explain the urgency. Clio's 2025 Legal Trends Report found the average utilization rate is just 38 percent, meaning lawyers capture only about 3.0 billable hours in an eight-hour day. Of what they do bill, the average realization rate is 88 percent and the average collection rate is 93 percent, so a meaningful slice of billed work is written down or never collected, and the median firm sits on 93 days of total lockup between doing the work and getting paid. Thomson Reuters and Clio surveys put non-billable administrative time somewhere between 28 and 48 percent of a lawyer's day. Every hour spent rekeying intake, running a conflicts check by hand, or reconstructing time entries is an hour that was never going to be invoiced.

Intake and discovery are where the leakage is most visible. Law-firm intake benchmarks show the average firm takes roughly 42 hours to respond to a web lead and that many never respond at all, while the firm that answers first tends to win the client. On the litigation side, the American Bar Association has estimated that document review alone can account for more than 80 percent of litigation spending, and industry data puts document review at 60 to 80 percent of e-discovery cost, with a human reviewer clearing on the order of 50 documents an hour. This is exactly the work AI is genuinely good at: an intake agent answers and screens leads in seconds, a conflicts agent scans your systems before a matter opens, and a document agent surfaces the relevant contracts, clauses, and passages for a lawyer to verify. Technology-assisted review has been shown to cut review effort dramatically, but the lawyer stays accountable for the result.

Confidentiality and competence are the gate, and they are non-negotiable. In the US, ABA Formal Opinion 512, issued in July 2024, applies the existing Model Rules to generative AI: the duty of competence under Rule 1.1 and its Comment 8 on relevant technology, confidentiality under Rule 1.6, communication with clients, supervision of nonlawyer assistance, and reasonable fees. State bars including California, Florida, and New York have issued their own guidance. In Canada, the Law Society of Ontario published its White Paper on generative AI in April 2024 and the Federation of Law Societies of Canada followed with national guidance, with all provincial law societies holding that competence, confidentiality, and supervision duties apply to AI without modification. We are a Calgary-based agency serving firms across Canada and the US, so we design for both regimes from day one: we do not send privileged data to public models that train on it, we keep the work inside tools that offer a confidentiality and data-processing agreement, we can keep Canadian client data resident in Canada, and a qualified lawyer reviews anything that touches legal advice.