Case study

Lease abstraction at deal-team speed.

We compressed a 6-day legal lease abstraction cycle into a same-day workflow, by automating the extract-review-route pattern with a human-in-the-loop interface.

Industry
Commercial real estate
Discipline
Build
Engagement
Document workflows · Lease abstraction
Outcomes

Numbers we agreed to move.

Cycle time
−83%
From 6 days median to under a day, holding accuracy at parity with manual review.
Reviewer throughput
+3.4×
Number of leases per reviewer per week, post-rollout.

The challenge

Lease abstraction was the bottleneck on every deal. Reviewers were doing first-pass extraction by hand, then second-pass review for accuracy — a pattern that scaled with headcount and nothing else.

What we did

We mapped the extract-review-route pattern, then shipped a focused tool: model does the first pass with confidence scores, reviewers see only the fields below a threshold, every override trains the model. No "AI assistant" panel grafted onto the side of an existing tool.

Where it landed

Reviewers stopped doing first-pass extraction entirely. The system handles 96% of fields above confidence threshold; the remaining 4% surface as a focused review queue with full source citations.

"We didn't think we were going to like it. Two months in, we won't ship without it."