Lease and statement extraction
The extraction pipeline turns lease packages and CAM reconciliation statements into structured fields used by the audit engine.
Problem
Commercial leases bury CAM rights, caps, exclusions, pro-rata definitions, and audit windows across dense PDF clauses. Reconciliation statements use inconsistent labels, summary categories, and property manager formats. Manual abstraction slows the audit before calculations even start.
Solution
CAMAudit uses OCR and AI-assisted extraction to convert lease language and reconciliation line items into structured audit inputs. The extraction step prepares the data that deterministic rules need, while preserving source references for partner review.
Proof points
Lease fields include exclusions, caps, base year terms, gross-up language, and pro-rata definitions.
Statement fields include expense categories, totals, allocation details, and line-item descriptions.
Source references help partners trace findings back to the uploaded documents.
Extraction prepares data for rules without letting AI perform financial math.
Workflow
01
OCR handles scanned or image-heavy lease and statement PDFs before semantic extraction starts.
02
Lease clauses and statement line items are mapped into the fields required by the audit engine.
03
The report can cite where the relevant lease language or statement amount came from.
Related feature pages
Every audit runs a consistent set of forensic CAM checks so partners do not depend on memory or one-off spreadsheet review.
Dollar amounts are calculated by deterministic rules, not guessed by AI.
Findings are stronger when the report shows the clause, statement line, and calculation path behind the issue.
Related guides and tools
FAQ
No. Extraction prepares the audit inputs. Partners still review findings, confidence notes, and source references before sending anything to a client.
Extraction handles messy language and document formats. Calculation is deterministic so dollar figures can be checked, reproduced, and explained.
Next step
