Everyone crossed a border at once

Harvey reports 700 clients across 63 countries. Legora serves 800 firms in 16 countries and is building Arabic capability with Al Tamimi. The pattern across the leading platforms is the same: non-English expansion, agentic autonomy, data moats, certification, and a shift from efficiency claims to quality claims. All of them are expanding into legal systems their products were never built or tested in.

Five initiatives, one dependency

Non-English expansion. Every new market represents a new legal system and a language the product was never validated in.

Agentic autonomy. An agent running a multi jurisdiction task unsupervised compounds a wrong equivalence at machine speed, with no human checkpoint between the almost right answer and the outcome.

Data moats. The leading platforms are already buying data: Clio acquired vLex, Harvey acquired Hexus, Legora acquired Walter AI, Thomson Reuters acquired Noetica. The question is which data, not whether to buy it.

Certification and governance. EU AI Act documentation and data governance duties are phasing in. Provenance stops being a virtue and becomes a requirement procurement has to satisfy.

Efficiency to quality. Quality is the next axis of competition, and it is the one that cannot be bought off the shelf.

Not one of these five is served by a better model alone.

The layer underneath

Every one of those initiatives depends on comparative legal data that, until recently, existed in no training corpus. TransLegal licenses such data as a layer beneath your model or product: legal concepts mapped across jurisdictions, non-equivalence explicit and machine readable, produced with named experts and owned outright.

Complementary to every model, competitive with none. And for a platform weighing the frontier models’ move into legal, data they do not have is the defence.

Founded 1989 · 20+ university law faculties · hundreds of lawyer-linguists · 65+ jurisdictional datasets

Read what the data records

Our data demo illustrates the comparative layer term by term, and what our data could add to your product.

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Better answers are a time saving. Quality converts into the efficiency metric the market already buys on.