AI Lease Abstraction Accuracy: Benchmarks and What to Expect
What accuracy can you realistically expect from AI lease abstraction tools? We break down field-level accuracy rates, where AI excels, where it struggles, and how to validate output.
The full physical address of the leased space.
By Angel Campa, Founder · Updated March 2026
The premises address defines the exact location subject to the lease and is critical for legal notices, insurance certificates, and tax filings. An incorrect address can void insurance coverage and create ambiguity about which property is bound by the lease terms. It also determines the governing jurisdiction for dispute resolution.
Stated in the lease preamble or a "Premises" definition section within the first few pages. Often supplemented by an Exhibit showing the floor plan or site plan with the demised area highlighted.
Lextract uses a combination of AWS Textract OCR and Claude AI to identify and extract the premises address from your lease PDF. The AI searches for all pages of the document, then assigns a confidence score based on OCR quality and extraction certainty. Fields with lower confidence are flagged for human review.
Landlord Name
The legal corporate name of the landlord/lessor.
Tenant Name
The legal corporate entity leasing the premises.
Guarantor Name
The entity or individual providing financial backing for the tenant.
Suite/Unit Number
The specific identifier for the tenant's space within a multi-tenant building.
Rentable Area (RSF)
The total area for which the tenant pays rent, including common area allocations.
Usable Area (USF)
The exact private physical space occupied by the tenant.
Discrepancies between the lease address and the actual property address can create legal issues with notice delivery, insurance claims, and lien filings. Any such discrepancy should be corrected via a lease amendment as soon as it is discovered.
Sometimes the suite number is included in the address, but in multi-tenant buildings it is usually broken out separately to allow for suite reassignments without amending the full address. Both should be verified during abstraction.
What accuracy can you realistically expect from AI lease abstraction tools? We break down field-level accuracy rates, where AI excels, where it struggles, and how to validate output.
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