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REST API · Lease to JSON · 100 free pages/mo

Lease Agreement Extraction API

Turn commercial and residential leases into structured JSON. Landlord and tenant, property address, start and end dates, base rent, deposit, notice periods, and the full escalation schedule - typed and ready for a rent roll, a lease abstract, or a diligence review. Works on scanned and signed PDFs.

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Rent, Term, and Escalations as Typed Fields

Send the lease and a schema. The parties, the dates, the money, and every escalation step come back as fields you can sort, diff, and put in a calendar.

request.sh
curl -X POST \
  https://api-parse.conversiontools.io/v1/extract \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "file=@lease.pdf" \
  -F 'schema={
    "landlord": "string",
    "tenant": "string",
    "property_address": "string",
    "lease_start": "date",
    "lease_end": "date",
    "term_months": "number",
    "base_rent": "number",
    "currency": "string",
    "payment_frequency": "string",
    "security_deposit": "number",
    "renewal_option": "string",
    "notice_period_days": "number",
    "permitted_use": "string",
    "escalations": [{
      "effective_date": "date",
      "amount": "number",
      "basis": "string"
    }]
  }'
response.json
{
  "status": "completed",
  "pages": 34,
  "data": {
    "landlord": "Harborline Estates LLP",
    "tenant": "Verdant Coffee Roasters Ltd",
    "property_address": "Unit 4B, 118 Meridian Way, Leeds",
    "lease_start": "2026-04-01",
    "lease_end": "2031-03-31",
    "term_months": 60,
    "base_rent": 4250.00,
    "currency": "GBP",
    "payment_frequency": "monthly",
    "security_deposit": 12750.00,
    "renewal_option": "One 5-year renewal at market rent",
    "notice_period_days": 180,
    "permitted_use": "Cafe and light food preparation",
    "escalations": [
      {
        "effective_date": "2028-04-01",
        "amount": 4550.00,
        "basis": "fixed step"
      },
      {
        "effective_date": "2030-04-01",
        "amount": 4850.00,
        "basis": "fixed step"
      }
    ]
  }
}

Built for Property Teams and Legal Review

A lease buries the dates and the money in forty pages of prose. The schema pulls them back to the surface.

Never miss a notice deadline

Notice periods and renewal options come back as real fields, so a break clause or an auto-renewal shows up in a report months ahead instead of surfacing after the window has closed.

Escalations as a schedule, not a paragraph

Stepped rents, fixed uplifts, and index-linked reviews return as an array with an effective date, an amount, and the basis, ready to drop into a rent roll or a cash-flow model.

Whatever the landlord template looks like

Every landlord, broker, and law firm drafts differently. You describe the fields once and the same schema runs across a whole portfolio, including scans of wet-signed originals.

Frequently Asked Questions

Does it work on both commercial and residential leases?

Yes. The API is schema-driven, so the same request shape covers a retail lease, an office lease, and a residential tenancy agreement. You describe the fields you need and leave out the ones you do not.

Can it pull the rent escalation schedule?

Yes. Define escalations as an array and each step comes back separately with its effective date, amount, and basis, whether the lease sets fixed uplifts, percentage steps, or index-linked reviews.

How does it handle amendments and addenda?

Send the amendment as its own document and extract it against the same schema, then compare the two results. Restated terms come back in the same shape as the original, so the comparison is a field-by-field check rather than a full re-read.

Can it read a scanned, signed lease?

Yes. OCR is applied automatically, so a scan of a wet-signed original or a photographed counterpart is read without a separate pre-processing step. Long leases run asynchronously, so you poll for the result or take a webhook when it is ready.

What happens to the lease documents after extraction?

Uploaded documents are deleted automatically within 24 hours. Extracted data is encrypted in transit and at rest and is never used to train models.

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