contract_management · travel · workflow
Generative AI + IDP Extracts Data from Lease Agreements with 82% Accuracy
A fast-food franchise employed 25 full-time outsourced workers to manually read and re-enter data from 30,000 lease documents annually, a process that was error-prone and required rework, while also needing to meet FASB compliance obligations requiring extraction of more than 350 fields from lease-related documents weekly.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Lease documents submitted
Commercial leasing agents submit lease documents of varying quality, types, and languages.
Tools used
ABBYY VantageGPT-4 Turbo · partnerSS&C Blue Prism · partnerRPA
Outcome
The hybrid IDP and GenAI solution achieved an 82% extraction accuracy rate across 350+ fields and 30K lease documents processed annually, with a human review loop enabling the ML model to improve over time and reduce manual review requirements.
What failed first
The franchise had previously attempted solutions with multiple advisory firms and tested five different technology combinations before finding one that yielded a superior result.
Results
Volume82%
Grounding & classification
Source type: vendor customer story
31 fields verified against source quotes.
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