Legal document review · Production

Wilson Sonsini uses Lexion's NLP to eliminate manual contract information extraction and accelerate deal-making

The problem

Wilson Sonsini's legal professionals bore a gigantic burden of manually extracting information from legal documents—a fundamental industry-wide problem where highly trained attorneys end up doing manual, repeatable work.

First attempt

Wilson Sonsini tested numerous legal tech platforms and found that larger vendors required expensive planning proposals just to begin information extraction, without delivering actual results.

Workflow diagram · grounded in source
1
Legal document extraction request
trigger
“manually extracting information from legal documents”
2
NLP-based information extraction
ai_action
“robust Natural Language Processing (NLP) models already built”
3
Information delivered to stakeholders
output
“getting information in the hands of stakeholders and attorneys on the front lines—making deals close more quickly”
4
Continuous model building
feedback_loop
“We're able to keep building new models”
Reported outcome

Lexion improved process compliance for information requests, saved legal professionals time, and enabled faster deal-making by getting information to stakeholders more quickly, while continuing to add functionality without sacrificing usability.

Reported metrics
Process compliance for information requestsgone way up
Deal-making speedmaking deals close more quickly
Legal professional time savingssaving legal professionals time
Reported stack
LexionNatural Language Processing (NLP)
Source
https://www.lexion.ai/case-study/wilson-sonsini
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Lexion improved process compliance for information requests, saved legal professionals time, and enabled faster deal-making by getting information to stakeholders more quickly, while continuing to add functionality wi…

What tools did this team use?

Lexion, Natural Language Processing (NLP).

What results were reported?

Process compliance for information requests: gone way up; Deal-making speed: making deals close more quickly; Legal professional time savings: saving legal professionals time (source-reported, not independently verified).

What failed first in this deployment?

Wilson Sonsini tested numerous legal tech platforms and found that larger vendors required expensive planning proposals just to begin information extraction, without delivering actual results.

How is this legal document review AI workflow structured?

Legal document extraction request → NLP-based information extraction → Information delivered to stakeholders → Continuous model building.