Client Snapshot
Industry:
PropTech / Real Estate SaaS
Location:
San Francisco, CA, USA
Engagement Type:
Lease Abstraction & Validation
Software:
Lease Management Platform
Key Highlights
Impact Area:
AI-Powered Lease Abstraction & Validation Accuracy
Improvement:
100% On-time Completion Despite High Complexity
Accuracy:
99.9%+ Verified Field-Level Accuracy
Scope:
293 Leases, 75 Fields per Abstract
Client Background
A leading proptech company headquartered in San Francisco offering an AI-powered lease management platform that automates data extraction from lease agreements. In 2025, The
Company partnered with OHI to manage a large-scale lease abstraction and validation project involving hundreds of complex commercial and institutional leases. The collaboration aimed to ensure the accuracy and completeness of AI-extracted lease abstracts within tight timelines.
Scope of Work
- Review and validation of AI-extracted data from 293 lease agreements
- Each abstract contained 75 key data fields including financial, legal, and operational terms
- Responsibilities included verifying AI outputs, correcting discrepancies, ensuring completeness, and conducting final quality reviews
Business Challenge
The project began with a straightforward scope — OHI’s team would validate AI-generated lease abstracts created by the platform, covering 75 key fields per lease.However, soon after starting, the team discovered that each lease was unique, differing significantly in structure, terminology, and clause presentation. This complexity made the process more time-intensive than initially anticipated.
Processing Time
Each lease required 2.5 to 3 hours to process due to clause-level variations.
Field-Level Accuracy
Maintaining accuracy across 75 data points within tight delivery timelines.
Legal Complexity
Adapting to complex legal language and non-standard formatting across 293 leases.
Delivery Timeline
Delivering within the original timeline despite the overall complexity.
OHI's Approach & Solution
Discovery & Reassessment
- Conducted an in-depth review of lease formats and complexity levels
- Defined a structured validation process for AI-extracted data
Execution Plan
- Deployed a dedicated five-member team of experienced Lease Experts
- Implemented a dual-phase process: AI Extraction Validation followed by 75-field Quality Review
- Maintained daily progress tracking and two-level QC checks
Commitment and Delivery
- The team worked extended hours and weekends to complete 293 leases on time
- Ensured 99.9% field accuracy verified through dual QC reviews
- Delivered before the deadline, earning client appreciation
Results & Impact
| KPI | OHI Result | Impact |
|---|---|---|
| Lease Project Completion | 100% within 6 Weeks | On-Time Delivery |
| Data Accuracy | 99.9% | High Consistency |
| Productivity | 2.5–3 hrs/lease (75-field review) | Exceeded Client Expectations |
| Client Satisfaction | Excellent | Positive Feedback |
Through disciplined project management and technical precision, OHI completed the project within the original deadline while maintaining 99.9%+ accuracy. The outcome strengthened the company’s confidence in outsourcing complex AI-assisted abstraction projects.
“I am very impressed with the quality and care you and your team put into the work for the project. I know this project was a bit complicated and, at times, challenging, but you were a wonderful partner throughout. I have a high degree of confidence that our future collaborations will only continue to improve.”
A San Francisco–Based Leading Proptech Company
Co-Founder & CEO
Struggling to Extract Critical Lease Data at Scale?
AI-driven lease abstraction simplifies complex lease portfolios and supports faster decision-making.
