AI Listing Ingestion & Structuring
This turns a property listing into quote-ready structured data for your placement team, FileMaker workflow, and pricing process.
Extract listing details without manual copy-paste
Paste a property URL once and convert the listing into clean, standardized data your team can review, price, and sync.
Listing URL input
Source receivedCapture source page content, property metadata, unit details, and pricing elements.
Normalize amenities, furnished status, policies, and availability into a standard record shape.
Flag missing fields, confidence issues, and sync the final result into internal review.
Structured extraction result
Ready to syncJSON output preview
{
"source": "apartments_com",
"property_name": "The Porter",
"address": "1800 Smith St, Houston, TX 77002",
"unit_type": "Unit 1208",
"beds": 2,
"baths": 2,
"rent_min": 3480,
"rent_max": 3620,
"furnished": false,
"pet_policy": "cats_dogs_allowed",
"parking": "garage_available",
"available_date": "2026-04-10"
}
Internal system-ready result
FileMaker payloadHow this helps
Teams stop retyping listing details, reduce quote mistakes, and get standardized property data that can move cleanly into sourcing and pricing workflows.
Best fit
Operators pulling options from listing portals, owner feeds, and broker links who need faster response times with cleaner internal data.