Use caseLegal·14 Apr 2026·5 min read

Contract intelligence that a lawyer will actually sign off on

Extraction is the easy half. The half that matters is a citation for every clause, a confidence you can act on, and a reviewer queue that gets shorter over time.

Review time per contract: −67%
Clause recall: 97.2%
Cited answers: 100%

Measured against a baseline captured before the work started. One engagement, not a forecast for another business. See the methodology note below.

Legal teams do not have a document-processing problem. They have a liability problem. An extraction that is 95% right and cannot tell you which 5% it got wrong is not a time saving. It is a new review task.

The pattern we deploy

Layout-aware parsing first: clause boundaries, defined terms and cross-references survive the trip out of the PDF.
Every extracted field carries a span citation back to the page and line it came from. One click jumps there.
Calibrated confidence, not model logprobs. Anything below threshold routes to review rather than being asserted.
The reviewer's corrections become the eval set, so the threshold moves in the right direction each quarter.

Where it pays off

Diligence rooms, renewal and obligation tracking, and any portfolio where the same twelve clauses decide most of the risk. It pays off worst on bespoke, heavily-negotiated one-offs. Those are still a lawyer's job, and should be.

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Methodology and privacy

Clients are described rather than named. Where a quote appears it is attributed to a role and published with approval.
Figures come from a single engagement and are not a forecast of what a different business would see. Volume, data quality and process maturity move them more than the technology does.
Baselines were captured before the work started. The measurement window and sample for any figure on this page are available on request.
Where a number is illustrative rather than measured, it is labelled as such in the text.

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