How it works
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.
- Document Capture: Users upload their identity document containing the address information.
- Data Extraction: Our advanced AI technology extracts the address information.
- External Validation: The address is validated against external map services.
- Result Generation: A detailed verification report is created.
- Result Handling: Results are available through dashboard, webhooks, or API.
Key Features
1. Document Capture and Processing
- Support for multiple document types (passports, IDs, permits)
- Multi-language and format support
- Advanced document layout analysis
2. AI-Powered Data Extraction
- State-of-the-art OCR technology
- Complex address structure handling
- High accuracy extraction rates
3. External Data Source Integration
- Integration with Google Maps and OpenStreetMap
- Component-level address validation
- Fictitious address detection
4. Comprehensive Address Analysis
- Granular address component verification
- Format standardization
- Completeness checking
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 documentparsed_address.street_1
: Primary street informationparsed_address.street_2
: Secondary street informationparsed_address.city
: City nameparsed_address.region
: State or regionparsed_address.postal_code
: ZIP or postal code
Geolocation Data
raw_results.geometry.location
: Precise coordinatesraw_results.location_type
: Accuracy level of geolocationraw_results.viewport
: Coordinate boundariesraw_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.