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Didit’s Document Address Geolocation verification offers a comprehensive solution to validate user addresses efficiently and accurately. Our system leverages advanced AI technology and external data sources to ensure the authenticity and validity of address information.
Didit document geolocation flow extracting and validating addresses from ID documents

Capture

Users upload an image of their document containing address information. Our advanced AI handles the rest.

Data Extraction

The extracted address is validated against multiple sources and geolocated by IP.

Analysis

A full report is generated on the validation status with standardized outputs.
Didit address geolocation result on map cross-checking declared address against Google Maps
Our system supports global address formats and provides standardized outputs regardless of the input document type or region.

Report Structure

The Document Geolocation report returns a JSON object with a root-level address field containing all verification results.

Core Response Fields

Response Fields

Address Information

  • address: Complete address as extracted from document
  • parsed_address.street_1: Primary street information
  • parsed_address.street_2: Secondary street information
  • parsed_address.city: City name
  • parsed_address.region: State or region
  • parsed_address.postal_code: ZIP or postal code

Geolocation Data

  • raw_results.geometry.location: Precise coordinates
  • raw_results.location_type: Accuracy level of geolocation
  • raw_results.viewport: Coordinate boundaries
  • raw_results.formatted_address: Standardized address format

Sample JSON Response

For a complete list of possible properties and their values, please refer to our API Reference.

Security and Privacy Considerations

Address information extracted from documents should be handled with appropriate security measures and in compliance with relevant data protection regulations. Implement proper access controls and data retention policies for this sensitive information.