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Document type

Extracting data from deeds

Attorneys and title companies draft deeds in their own words, and each county recorder adds its own stamps and margins. Title examiners read every deed in a property's chain of title, for each sale and refinance their office closes. The deeds arrive as recorder downloads and scans of decades-old paper.

Title review needs the grantor, the grantee, the consideration, the transfer tax and the parcel number with its legal description. A title production system checks each conveyance against the chain, and the title commitment names the vested owner from the latest deed.

Page 1 of a sample Deed, with extracted values outlined
4,906Markdown characters
39parse blocks
44fields extracted
The problem

What makes deeds hard

The parties sit in prose

A deed names its grantor, grantee and price inside one granting clause of running text, each party followed by its entity description.

Legal descriptions on exhibits

The legal description, by lot and block or by metes and bounds, often sits on an exhibit page that the deed's face points to.

Decades of scanned paper

A chain of title reaches back decades, to photocopied deeds carrying recorder stamps and dates filled in by hand.

How it works

Parse, extract, verify

1

Parse

Parse turns the document into reading-order Markdown and a hierarchy of blocks (text, tables, figures), and grounds each block to its exact location on the page.

2

Extract

You define the fields in a JSON schema, and Extract returns their values in a consistent, structured format, each linked back to where it appears in the Markdown.

3

Verify

Each value links back to where it appears, down to the character range in the Markdown, and the page and bounding box in the source document, so every result can be verified.

Worked example

One deed, end to end

About this document: A grant deed from the City of Los Angeles, kept in the City Clerk's public council file. It sells a surplus parcel in Pacific Palisades to a California corporation. Five scanned portrait pages: the deed, the Exhibit A legal description, approvals, the execution page and the notary acknowledgment. Page 1 is featured. Every party to the conveyance is a public body or a company.

Processing objective: The objective is to read the conveyance on the face of the deed, along with the parcel it covers and the county tax declared on it. A title examiner checks that the grantor matches the grantee of the prior deed in the chain. Each value grounds to its own line of the page.

Demonstration fields: Grantor, Grantee, Consideration, County transfer tax, APN

The document

4 of 5 pages
  • Page 1 of the sample DeedPage 1shown below
  • Page 2 of the sample DeedPage 2
  • Page 3 of the sample DeedPage 3
  • Page 4 of the sample DeedPage 4

Where each value came from

Page 1 of the sample Deed, with every featured field outlined
Grantorgrantor.name
THE CITY OF LOS ANGELES
The region of the sample Deed containing Grantor, with the extracted value outlined
extraction_metadata["grantor.name"]
{
  "value": "THE CITY OF LOS ANGELES",
  "page": 1,
  "range": {
    "end": 486,
    "start": 393
  },
  "box": {
    "xmin": 0.04502,
    "ymin": 0.35604,
    "xmax": 0.90454,
    "ymax": 0.37151
  }
}
Granteegrantee.name
WHITE PICKET FENCE, INC.
The region of the sample Deed containing Grantee, with the extracted value outlined
extraction_metadata["grantee.name"]
{
  "value": "WHITE PICKET FENCE, INC.",
  "page": 1,
  "range": {
    "end": 660,
    "start": 610
  },
  "box": {
    "xmin": 0.27997,
    "ymin": 0.40799,
    "xmax": 0.75285,
    "ymax": 0.42664
  }
}
Considerationconsideration_amount
1,100,000
The region of the sample Deed containing Consideration, with the extracted value outlined
extraction_metadata["consideration_amount"]
{
  "value": 1100000,
  "page": 1,
  "range": {
    "end": 582,
    "start": 487
  },
  "box": {
    "xmin": 0.046,
    "ymin": 0.36967,
    "xmax": 0.90334,
    "ymax": 0.38533
  }
}
County transfer taxdocumentary_transfer_tax[0].amount
1,210
The region of the sample Deed containing County transfer tax, with the extracted value outlined
extraction_metadata["documentary_transfer_tax[0].amount"]
{
  "value": 1210,
  "page": 1,
  "range": {
    "end": 103,
    "start": 59
  },
  "box": {
    "xmin": 0.5131,
    "ymin": 0.16052,
    "xmax": 0.84337,
    "ymax": 0.1761
  }
}
APNapn
4412-028-906
The region of the sample Deed containing APN, with the extracted value outlined
extraction_metadata["apn"]
{
  "value": "4412-028-906",
  "page": 1,
  "range": {
    "end": 391,
    "start": 374
  },
  "box": {
    "xmin": 0.57141,
    "ymin": 0.30972,
    "xmax": 0.71033,
    "ymax": 0.32399
  }
}

How to try it yourself

Everything on this page is reproducible. The sample, its schema, and the Parse and Extract API outputs are published. You can repeat the same two calls from whichever surface you already build on.

  • Claude Skilldescribe the job; the agent writes it
  • CLIno code at all
  • MCPexpose ADE docs as an agent tool
  • REST APIany language
  • Pythonlandingai-ade
  • TypeScriptlandingai-ade
Why LandingAI?

Documents into data

Accurate

The best accuracy on the difficult documents other tools get wrong, such as messy scans, complicated tables, checkboxes and handwriting.

Auditable

Every answer cites its sources. Values come back with an audit trail (page, bounding box, character range) so a human can review them.

Agentic

Applies multi-step reasoning, and plans before it acts. Handles documents it has never seen before and adapts to variations.

API-first

Composable APIs that drop into any tech stack and can be called from anywhere. Easy to build on and embed in your pipelines and products.

Affordable

Cost-competitive rates with complete price transparency. Spend controls before you run, and every job reports its exact cost.

Enterprise-grade

Built for production and scale from day one. Fully observable and monitored, running securely in our cloud or yours.

Built for high-volume, high-throughput production

  • Zero data retention
  • Priority rate limits
  • Enhanced support
  • VPC and on-prem deployment

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Capabilities

Deed processing highlights

Grantor and grantee
Consideration in words and figures
Documentary transfer tax lines
Assessor's parcel number
Lot, block and tract
Metes and bounds text
Exhibit legal descriptions
Reservations and exceptions
Notary acknowledgments
Handwritten execution dates
Scanned and photocopied deeds
Bounding box for every value
FAQs

Questions, answered

Yes. Describe the grantor and grantee as fields in your schema, with each entity description as a field of its own. Extraction reads the granting clause for meaning, so each party comes back separately, grounded to the line that names it.

Yes. Parsing works from the page image, so a scanned or photocopied deed reads the same way as a digital PDF. Handwritten entries, such as an execution date or a notary's commission expiry, are transcribed with the printed text around them.

Yes. Parsing covers every page of the deed, and extraction reads across them. A schema can ask for the full legal description and its parts, such as lot, block, tract and map book, from the exhibit the deed refers to.

Yes. Parsing labels each block that carries a signature, stamp or seal with tags such as SIGNED or STAMPED, and transcribes the readable text inside it. A notary acknowledgment comes back with its date and commission expiry as text.

Every extracted value carries the character range it was quoted from in the parsed Markdown. The Ground API maps that range to a page and a bounding box, so a reviewer sees each value on the line that printed it.

Start extracting deed data

Reliable, structured outputs with full traceability in minutes