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OSL Extraction

When you upload an Ontario Standard Lease, our AI extracts key information automatically. This page explains what gets extracted and how.

Extracted Fields

Landlord Information

FieldSource in OSL
NameSection 1 - Landlord(s)
AddressSection 1 - Address for Giving Notices
EmailSection 1 - Email
PhoneSection 1 - Phone

Tenant Information

FieldSource in OSL
Name(s)Section 2 - Tenant(s)
EmailSection 2 - Email
PhoneSection 2 - Phone

Property Information

FieldSource in OSL
AddressSection 3 - Rental Unit
Unit NumberSection 3 - Unit (if applicable)
ParkingSection 3 - Parking Space

Lease Terms

FieldSource in OSL
Start DateSection 4 - Tenancy Start Date
End DateSection 4 - End Date (fixed-term)
Lease TypeSection 4 - Fixed-term or Month-to-month
Base RentSection 5 - Lawful Rent
Rent Due DateSection 5 - Due Date
Payment MethodSection 5 - Payment Method

Services and Utilities

FieldSource in OSL
ElectricitySection 6
HeatSection 6
WaterSection 6
InternetSection 6
ParkingSection 6
Air ConditioningSection 6

Deposits

FieldSource in OSL
Rent DepositSection 7
Key DepositSection 7

Extraction Technology

Our extraction uses:

  1. PDF Text Parsing - For text-based PDFs
  2. OCR (Optical Character Recognition) - For scanned documents
  3. AI Understanding - To map fields correctly

Confidence Scores

Each extracted field has a confidence score:

High Confidence (90-100%)

  • Field clearly readable
  • Standard format recognized
  • Likely correct

Medium Confidence (70-89%)

  • Field readable but unusual format
  • Some ambiguity
  • Review recommended

Low Confidence (Below 70%)

  • Field difficult to read
  • Non-standard format
  • Manual verification required

Handling Edge Cases

Handwritten Text

  • Printed text extracts best
  • Handwritten may need OCR
  • Very poor handwriting may fail

Multiple Tenants

  • All tenant names are extracted
  • Each becomes a separate tenant record
  • All linked to the same lease

Non-Standard Formats

If your OSL has been modified:

  • Core fields usually still extract
  • Custom additions may be missed
  • Review carefully and add manually

Comparing to Original

After extraction, you can compare:

  1. View extracted data
  2. Click "View Original"
  3. Side-by-side comparison
  4. Correct any discrepancies

Improving Extraction

Before Uploading

  • Use clean, high-quality scans
  • Ensure all pages included
  • 300 DPI or higher recommended

After Uploading

  • Review all fields
  • Check medium/low confidence items
  • Correct errors before confirming

Data Validation

The system validates extracted data:

  • Dates are valid
  • Rent amount is reasonable
  • Postal codes are valid format
  • Email addresses are valid format

Invalid data is flagged for review.

Next Steps