AI case study

JLLLease data extraction

Classical ML choked on legal nuance across 175 jurisdictions. AI agents now draft; humans validate — then the portfolio answers questions.

Published

Key results

Cost Reduction Per Abstract
30%
Per-Lease Review Time
85 mins
Pre-Review Accuracy
92%+

Result highlights

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The story

Context

A global real estate services firm managing lease portfolios across 175 legal jurisdictions and more than 45 languages, where accurate lease data underpins every pricing, management, and advisory decision across five business lines.

Challenge

For years, thousands of tenured specialists manually reviewed lease documents, with extracted data landing in spreadsheets disconnected from...

Solution
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Quotes

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The company

Commercial real estate services and investment management firm.

IndustryReal Estate & Construction
LocationChicago, IL, USA
Employees100K+

The implementation partner

DealSumm logo

DealSumm

dealsumm.com
Role in this case study

Helped JLL build and deploy an AI-powered lease abstraction platform on Databricks

IndustryReal Estate & Construction
LocationLondon, England, UK
Employees11-50
Founded2021

The vendor

Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.

IndustrySoftware & Platforms
LocationSan Francisco, California, United States
Employees10K-50K
Founded2013

Use case

JLL's Lease data extraction is part of this use case:

Contract Analysis
40 case studies(+35% YoY)
Proven impact?
LowModerateVery Strong
5.0Strong
12.0Very strongwithin Real Estate & Construction

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