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.
Capture
Users upload an image of their document containing address information. Our advanced AI handles the rest.| Capability | Description |
|---|
| Document types | Passports, IDs, residence permits, and more |
| Language support | Multi-language and multi-format recognition |
| AI extraction | Automatic data extraction from the uploaded document |
Data Extraction
The extracted address is validated against multiple sources and geolocated by IP.| Capability | Description |
|---|
| Map integration | Google Maps and OpenStreetMap cross-referencing |
| Component validation | Street, city, region, and postal code verified individually |
| Fraud detection | Fictitious address detection to prevent possible fraud |
Analysis
A full report is generated on the validation status with standardized outputs.| Capability | Description |
|---|
| Verification results | Detailed results with standardized output format |
| Comprehensive reports | Full verification reports for every submission |
| Delivery options | Results 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: 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. 
