The legal AI conversation has, understandably, been dominated by models.

Which model reasons better? Which has the larger context window? Which performs best on legal benchmarks? Which is fastest? These are important questions. But as legal AI moves from experimentation into everyday professional work, another question may become more important: what is the AI actually working with?

For legal work, intelligence without reliable information has obvious limits. A model may be extremely capable at reasoning across documents, but if the underlying legal material is incomplete, outdated, poorly structured or difficult to verify, the quality of the model can only take the lawyer so far.

This suggests that one of the most important competitive advantages in legal AI may not sit in the model layer at all. It may sit in the data layer.

Legal data is not simply a collection of documents

At first glance, the raw material of legal research appears straightforward: judgments, legislation, regulations and other legal materials. But a useful legal information system is more than a repository.

A judgment cites earlier judgments. Later courts interpret, distinguish, follow or overrule it. A statutory provision is amended. An Act is repealed. A notification changes how a provision operates. Different authorities acquire different significance depending on the court, jurisdiction, issue and point in time.…

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