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Document Geolocation

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.

  1. Capture

  • Users upload an image of their document with their address information
  • Support for multiple document types (passports, IDs, permits)
  • Multi-language and format support
  • Our advanced AI extracts the data from the document

  1. Data Extraction

  • The address is validated with different sources and geolocated by IP
  • Integration with Google Maps and OpenStreetMap
  • Component-level address validation
  • Fictitious address detection to avoid possible fraud

  1. Analysis

  • A full report is generated on the validation status
  • Detailed verification results with standardized outputs
  • Comprehensive verification reports
  • Results can be received via dashboard, webhooks or API

📘

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

interface DocumentGeolocationResponse {
  address: string;
  parsed_address: {
    id: string;
    label: string;
    street_1: string;
    street_2: string | null;
    city: string;
    region: string;
    postal_code: string;
    raw_results: {
      geometry: {
        location: {
          lat: number;
          lng: number;
        };
        location_type: string;
        viewport: {
          northeast: {
            lat: number;
            lng: number;
          };
          southwest: {
            lat: number;
            lng: number;
          };
        };
      };
      formatted_address: string;
    };
  };
}

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

{
  "address": "Avda de Madrid 34, Madrid, Madrid",
  "parsed_address": {
    "id": "7c6280a2-fb6a-4258-93d5-2ac987cbc6ba",
    "city": "Madrid",
    "label": "Spain ID Card Address",
    "region": "Madrid",
    "street_1": "Avda de Madrid 34",
    "street_2": null,
    "postal_code": "28822",
    "raw_results": {
      "geometry": {
        "location": {
          "lat": 37.4222804,
          "lng": -122.0843428
        },
        "location_type": "ROOFTOP",
        "viewport": {
          "northeast": {
            "lat": 37.4237349802915,
            "lng": -122.083183169709
          },
          "southwest": {
            "lat": 37.4210370197085,
            "lng": -122.085881130292
          }
        }
      },
      "formatted_address": "Avda de Madrid 34, Madrid, Madrid 28822, Spain"
    }
  }
}

📘

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.