Law

Law is the domain everyone assumes is closed by attorney-client privilege, and the assumption is wrong in a specific and exploitable way.

The scarce input is not the client's file. Court filings, appellate opinions, SEC filings and published commercial contracts are all public. What is scarce is the lawyer's judgement about them — the redline rationale, the "this clause is a landmine" reflex, the strategic read of an opponent's brief, the issue a second-year misses and a partner sees in eight seconds. That judgement is unencumbered by privilege because the underlying documents are already published. It is the cleanest legal workaround in this atlas, and it is why a domain that looks foreclosed is in fact open.

The pool is the largest here: 1.37 million licensed US lawyers in 2025, up from 1.35M in 2024 — the first year-over-year rise since 2020 — with New York at 190,015, California 181,048 and Texas 99,867 (ABA Journal). And unlike most niches on this site, there is already an observed clearing price: Mercor advertises law experts at $55–$150+/hr, with senior corporate/M&A, litigation and in-house counsel roles at $140–160/hr and mid-level at $80–120/hr (Mercor). You are not guessing what a lawyer costs. Someone is already paying it.

No law-only expert-data company exists. That is a [NOTHING FOUND] across legal-tech funding news, RL-environment directories and Mercor-competitor lists — every result is an application (Harvey, Midpage, Legora, Alexi, CoCounsel, Darrow) or a corpus deal, like Clio buying vLex for $1B (TechCrunch).

#What the data actually is

Drafting, and only drafting, is the open position. LegalBench is 162 tasks across six reasoning types built by ~40 lawyers and computational practitioners at Stanford, and it is mature and widely reported (arXiv 2308.11462). LegalBench-RAG adds 6,858 expert-annotated query-answer pairs for the retrieval component. Both are classification-heavy. PLawBench — 850 questions with roughly 12,500 rubric items — reports that none of ten evaluated frontier LLMs achieves strong performance (Kili survey).

What does not exist anywhere: an open benchmark for litigation drafting, contract redlining or discovery strategy. A public, rubric-graded drafting benchmark built by 200 practising litigators is an unclaimed marketing weapon — proof scores 4 on that vacancy — and the tasks that fill it are the product:

• Redline rationales. Two versions of a public commercial contract plus a lawyer's paragraph on why each change was made and what it costs the other side.
• Adversarial reads. Give a litigator an opponent's filed brief from PACER and pay for the response outline, ranked by what they would actually argue first.
• Issue-spotting under time pressure. The APEX shape — Mercor spent over $500,000 building 200 professional tasks with graders from Latham & Watkins among others (TIME).
• Disagreement. Two senior litigators reaching opposite strategic conclusions on the same record is signal, not noise — the same argument Contra Labs makes about designers, and it prices better than consensus.

#Is anyone buying

Indirectly, and unambiguously enough to score budget 3 rather than 2.

Mercor's rate card is a live transaction, not a projection: tasks listed include evaluating model outputs on contract analysis, litigation strategy, regulatory interpretation and due diligence, creating gold-standard analyses, and building ambiguous test scenarios (Mercor). Somebody is paying Mercor's ~35% on top of $140–160/hr, and Mercor's customers are OpenAI, Google DeepMind and Meta (Value Add VC) — a $2B annualised gross revenue run-rate, which is gross payment volume, not net revenue.

OpenAI also runs a legal vertical product team — Forward Deployed Engineer (Legal) in NYC and SF, Product Manager, Legal, and a Founding Full Stack Software Engineer, Legal (OpenAI careers). A vertical product team needs vertical evals.

#Getting the experts

Reach scores 5. State bar member directories and licence-lookup registers are public, verifiable and jurisdiction-tagged — the cleanest credential filter of any domain in this atlas after NASBA's CPA register (Accounting, audit and tax).

Beyond the registers: ABA sections (Litigation, Business Law, Science & Technology Law); CLE providers Lawline and PLI, whose attendee lists are the AI-curious segment; CLOC and the legal-ops communities; contract-lawyer marketplaces — Lawtrades, Axiom, Hire an Esquire — where lawyers already sell hours by the project, which halves the behavioural change you are asking for; r/Lawyertalk and r/biglaw; Above the Law, LawNext and Artificial Lawyer, the publications the AI-interested legal audience reads; law school alumni networks; and judicial clerkship alumni lists, which are a precision instrument for written-reasoning quality.

#What it costs to run

Cost scores 3 — the middle of the set, and the arbitrage is subtler than it looks. BLS puts lawyers at a median $159,670/yr ($76.76/hr) across 863,700 jobs (BLS). BigLaw billing rates run many multiples of $160/hr, but the lawyer sees a fraction of that, and an associate's marginal evening hour is genuinely available at $150.

Law is the domain with the widest gap between the billing rate (intimidating, and the reason founders talk themselves out of it) and the acquisition cost (reasonable). At $150/hr in and a sell price in the $250–350/hr range, the spread is workable but it is not accounting's spread. You need volume or you need a benchmark that lets you price on outcome rather than hours; see Pricing and the contract.

#Who is already there

Nobody in the data-supply position. Vals AI occupies the benchmark layer for law as one of four verticals. Everything else is an application company that consumes legal judgement internally rather than selling it. Room scores 4 rather than 5 only because Vals could extend downward into supply with one hire.

Defense scores 4. Privilege keeps the raw material permanently out of anyone's reach, including yours and including a horizontal's, so the only route in is the one you have built; and statutes, rules and case law change continuously, so a 2026 dataset is stale by 2029 whether or not anyone competes with you.

#What would kill it

#The first ninety days here

Pick one jurisdiction and one document type. Delaware corporate, or SDNY commercial litigation. Pull 60–100 lawyers from the state bar register cross-referenced against Lawtrades and clerkship alumni lists. Pay $150/hr and state in the first sentence of the screen that no client material is ever accepted — that single line does more for conversion here than any rate.

Build the drafting benchmark first: 200 redline-and-rationale tasks over public contracts and public filings, three graders each, blind, weighted like VLAIR was. Publish it. Then sell the dataset underneath it to the people who read it. That sequencing — benchmark as the sales motion — is the whole argument in The specialist wedge, and law sits on the good side of the trade it describes: empty benchmark, unproven budget.

#Where the record is thin

Mercor's $140–160/hr band comes from its own recruiting page; nobody has confirmed what the labs pay Mercor for it, so the sell-side price is unknown and the take rate is inferred.

PLawBench's "none of ten achieves strong performance" reaches us through a survey article rather than the paper. No lab job posting anywhere hires lawyers to make data, so every demand claim is an inference from an intermediary's rate card and a product team's headcount. And the privilege workaround, though clean, is untested — no bar has ruled on whether paid judgement about public documents creates any duty at all.