iterationlayer Extract Real Estate Listing
Real estate agencies and property platforms use this recipe to digitize a listing document. Upload a property listing PDF and receive structured JSON with address, price, and property features — ready for your MLS integration or property database.
APIs Used
Document Extraction (1 credit per page)
Prerequisites
You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
Implementation
curl -X POST https://api.iterationlayer.com/document-extraction/v1/extract \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"files": [
{
"type": "url",
"name": "listing.pdf",
"url": "https://example.com/listings/listing.pdf"
}
],
"schema": {
"fields": [
{
"name": "address",
"type": "ADDRESS",
"description": "Full property address"
},
{
"name": "listing_price",
"type": "CURRENCY_AMOUNT",
"description": "Listed sale price"
},
{
"name": "bedrooms",
"type": "INTEGER",
"description": "Number of bedrooms"
},
{
"name": "bathrooms",
"type": "INTEGER",
"description": "Number of bathrooms"
},
{
"name": "square_footage",
"type": "INTEGER",
"description": "Total square footage"
}
]
}
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const result = await client.extractDocument({
files: [
{
type: "url",
name: "listing.pdf",
url: "https://example.com/listings/listing.pdf",
},
],
schema: {
fields: [
{
name: "address",
type: "ADDRESS",
description: "Full property address",
},
{
name: "listing_price",
type: "CURRENCY_AMOUNT",
description: "Listed sale price",
},
{
name: "bedrooms",
type: "INTEGER",
description: "Number of bedrooms",
},
{
name: "bathrooms",
type: "INTEGER",
description: "Number of bathrooms",
},
{
name: "square_footage",
type: "INTEGER",
description: "Total square footage",
},
],
},
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
result = client.extract_document(
files=[
{
"type": "url",
"name": "listing.pdf",
"url": "https://example.com/listings/listing.pdf",
}
],
schema={
"fields": [
{
"name": "address",
"type": "ADDRESS",
"description": "Full property address",
},
{
"name": "listing_price",
"type": "CURRENCY_AMOUNT",
"description": "Listed sale price",
},
{
"name": "bedrooms",
"type": "INTEGER",
"description": "Number of bedrooms",
},
{
"name": "bathrooms",
"type": "INTEGER",
"description": "Number of bathrooms",
},
{
"name": "square_footage",
"type": "INTEGER",
"description": "Total square footage",
},
]
},
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
result, err := client.ExtractDocument(il.ExtractDocumentRequest{
Files: []il.FileInput{
il.FileInput{
Type: "url",
Name: "listing.pdf",
Url: "https://example.com/listings/listing.pdf",
},
},
Schema: il.ExtractionSchema{
Fields: []any{
il.AddressFieldConfig{
Name: "address",
Type: "ADDRESS",
Description: "Full property address",
},
il.CurrencyAmountFieldConfig{
Name: "listing_price",
Type: "CURRENCY_AMOUNT",
Description: "Listed sale price",
},
il.IntegerFieldConfig{
Name: "bedrooms",
Type: "INTEGER",
Description: "Number of bedrooms",
},
il.IntegerFieldConfig{
Name: "bathrooms",
Type: "INTEGER",
Description: "Number of bathrooms",
},
il.IntegerFieldConfig{
Name: "square_footage",
Type: "INTEGER",
Description: "Total square footage",
},
},
},
})
if err != nil {
panic(err)
}
_ = result
}
{
"name": "Extract Real Estate Listing",
"nodes": [
{
"parameters": {
"content": "## Extract Real Estate Listing\n\nReal estate agencies and property platforms use this recipe to digitize a listing document. Upload a property listing PDF and receive structured JSON with address, price, and property features \u2014 ready for your MLS integration or property database.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes on self-hosted n8n, or add it directly on n8n Cloud with Verified Community Nodes enabled.",
"height": 280,
"width": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
200,
40
],
"id": "87bfaa5a-7dfd-4b13-a506-fc47c2a1c137",
"name": "Overview"
},
{
"parameters": {
"content": "### Step 1: Extract Data\nResource: **Document Extraction**\n\nConfigure the Document Extraction parameters below, then connect your credentials.",
"height": 160,
"width": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
475,
100
],
"id": "17bf5410-88ba-4288-bdf0-c7d81249f3df",
"name": "Step 1 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "a9b0c1d2-e3f4-5678-abcd-789012345abc",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "documentExtraction",
"schemaInputMode": "rawJson",
"schemaJson": "{\"fields\":[{\"name\":\"address\",\"type\":\"ADDRESS\",\"description\":\"Full property address\"},{\"name\":\"listing_price\",\"type\":\"CURRENCY_AMOUNT\",\"description\":\"Listed sale price\"},{\"name\":\"bedrooms\",\"type\":\"INTEGER\",\"description\":\"Number of bedrooms\"},{\"name\":\"bathrooms\",\"type\":\"INTEGER\",\"description\":\"Number of bathrooms\"},{\"name\":\"square_footage\",\"type\":\"INTEGER\",\"description\":\"Total square footage\"}]}",
"files": {
"fileValues": [
{
"fileInputMode": "url",
"fileName": "listing.pdf",
"fileUrl": "https://example.com/listings/listing.pdf"
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "b0c1d2e3-f4a5-6789-bcde-890123456bcd",
"name": "Extract Data",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Extract Data",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
Extract real estate listing data from the file at [file URL]. Use the extract_document tool with these fields:
- address (ADDRESS): Full property address
- listing_price (CURRENCY_AMOUNT): Listed sale price
- bedrooms (INTEGER): Number of bedrooms
- bathrooms (INTEGER): Number of bathrooms
- square_footage (INTEGER): Total square footage
Response
{
"success": true,
"data": {
"address": {
"value": {
"street": "1847 Maple Drive",
"city": "Austin",
"region": "TX",
"postal_code": "78704",
"country": "US"
},
"confidence": 0.97,
"citations": ["1847 Maple Drive, Austin, TX 78704"]
},
"listing_price": {
"value": {
"amount": "549,000.00",
"currency": "USD"
},
"confidence": 0.98,
"citations": ["Listed at $549,000"]
},
"bedrooms": {
"value": 3,
"confidence": 0.99,
"citations": ["3 Bed"]
},
"bathrooms": {
"value": 2,
"confidence": 0.99,
"citations": ["2 Bath"]
},
"square_footage": {
"value": 1850,
"confidence": 0.96,
"citations": ["1,850 sq ft"]
}
}
}