Commercial real estate teams spend days abstracting data from leases, rent rolls, operating statements, loan documents, and closing packages into spreadsheets.
Key terms repeat across sources but rarely match perfectly, forcing manual cross-referencing and version chasing.
The workflow scales linearly with volume: more deals or more leases means more headcount or more missed details.
Errors hide in bulk work: a single missed clause or mis-keyed number can cascade into underwriting and asset management decisions.
Eagle Eye is Rets AI’s bulk document abstraction feature for CRE. It ingests large document sets, extracts and normalizes key fields into review-ready tables, and preserves traceability back to the underlying source language for validation.
Abstracts key terms across many documents in a single run (not one document at a time).
Normalizes outputs into consistent columns, formats, and units to enable side-by-side comparison.
Surfaces missing fields, conflicts, and outliers so reviewers focus on exceptions instead of transcription.
Maintains citation trails that link each table value back to where it came from in the source material.
Exports structured outputs for downstream workflows (for example: underwriting models, reporting, and portfolio monitoring).
