Skip to main content
POST
/
v3
/
database-validation
/
curl -X POST "https://verification.didit.me/v3/database-validation/" \
  -H "x-api-key: YOUR_API_KEY" \
  -F "issuing_state=IDN" \
  -F "services=idn_residential_identity_card" \
  -F "vendor_data=user-1234" \
  -F "consent=true" \
  -F "full_name=John Doe" \
  -F "date_of_birth=1990-01-01" \
  -F "national_id=1111111111111111" \
  -F 'address={"street_1":"123 Sample Street","street_2":"Unit 4","city":"Sample City","region":"Sample State","postal_code":"10001","country":"US"}'
{
  "request_id": "req_01H…",
  "status": "Approved",
  "issuing_state": "IDN",
  "match_type": "full_match",
  "validations": [
    {
      "outcome_code": "MATCH",
      "service_id": "idn_residential_identity_card",
      "service_name": "Indonesia Residential Identity Card",
      "source_data": {
        "address_match_score": "1.000",
        "date_of_birth": "1990-01-01",
        "identification_number": "SAMPLE-ID-12345",
        "verifications": {
          "address": true,
          "date_of_birth": true,
          "full_name": true,
          "identification_number": true
        }
      },
      "validation": {
        "address": "full_match",
        "date_of_birth": "full_match",
        "full_name": "full_match",
        "identification_number": "full_match"
      }
    }
  ]
}
Verifies input data against a Government agency. Didit exposes this service through POST /v3/database-validation/ so you can verify the submitted data against the authoritative source and receive normalized match results.

Coverage

  • Coverage: ~ 90%
  • Country: Indonesia
  • Service ID: idn_residential_identity_card
  • Data domain: Address
  • Category: Residential

Inputs

FieldRequiredExample
full_nameYesJohn Doe
date_of_birthYes1990-01-01
national_idYes1111111111111111
address.street_1Yes123 Sample Street
address.postal_codeYes10001
address.street_2NoUnit 4
address.cityNoSample City
address.regionNoSample State
genderNoM
vendor_dataNouser-1234
  • Required inputs: full_name, date_of_birth, national_id, address.street_1, address.postal_code
  • Optional inputs: address.street_2, address.city, address.region, gender, vendor_data
  • Consent: Required
  • Workflow availability: Available in workflow
  • Coverage: ~ 90%
  • Price: $0.16 per successful query

Body parameters

issuing_state
string
default:"IDN"
required
ISO 3166-1 alpha-3 country code for this database service.Example: IDN
services
string
default:"idn_residential_identity_card"
required
Array containing this service ID. Pinning the service keeps the request scoped to this exact database.Example: idn_residential_identity_card
Explicit end-user consent for this service.Example: true
full_name
string
default:"John Doe"
required
Full legal name to validate.Example: John Doe
date_of_birth
string
default:"1990-01-01"
required
Date of birth in YYYY-MM-DD format.Example: 1990-01-01
national_id
string
default:"1111111111111111"
required
National identity number for this service.Example: 1111111111111111
address
object
required
Structured residential address object. Use street_1, street_2, city, region, postal_code, and country. A complete legacy address string is still accepted but not recommended.Example: {"street_1":"123 Sample Street","street_2":"Unit 4","city":"Sample City","region":"Sample State","postal_code":"10001","country":"US"}
gender
string
default:"M"
Gender value, when required by the database.Allowed values: M (male), F (female), X (other or unknown).Example: M
vendor_data
string
default:"user-1234"
Your stable user reference for this person, such as your internal user ID. Didit uses it to link standalone checks to the same end user and reduce duplicate-detection noise.Example: user-1234

Input rules & validation notes

  • national_id must contain digits only; remove spaces, hyphens, and punctuation before sending the request.
  • national_id must be exactly 16 characters long.
  • For address services, send structured address fields instead of a single address string when possible.
  • address.street_1 is the street address, including street number and street type.
  • address.street_2 is apartment, unit, building, floor, or extra address line. Send it only when you have it.
  • address.city is city, suburb, district, locality, or neighborhood.
  • address.region is state, province, region, or town.
  • address.postal_code is postcode or postal code.
  • Address-based database services require at least street address and postal code; requests rejected before source lookup are not charged.

How to call it

curl -X POST "https://verification.didit.me/v3/database-validation/" \
  -H "x-api-key: YOUR_API_KEY" \
  -F "issuing_state=IDN" \
  -F "services=idn_residential_identity_card" \
  -F "vendor_data=user-1234" \
  -F "consent=true" \
  -F "full_name=John Doe" \
  -F "date_of_birth=1990-01-01" \
  -F "national_id=1111111111111111" \
  -F 'address={"street_1":"123 Sample Street","street_2":"Unit 4","city":"Sample City","region":"Sample State","postal_code":"10001","country":"US"}'
Every successful call returns HTTP 200. The outcome_code field tells you what actually happened — distinguishing, for example, a real biometric mismatch (BIOMETRIC_NO_MATCH) from a selfie that could not be read (BIOMETRIC_IMAGE_UNUSABLE). The status shown is the default feature status; your configured Partial Match / No Match actions can override it.

Returned data

The exact fields surfaced in source_data depend on what the registry returns. The generated example for idn_residential_identity_card currently documents this normalized shape:
  • address_match_score
  • date_of_birth
  • identification_number

Pricing & SLAs

Indonesia Residential Identity Card queries are billed only when Didit receives a conclusive result from the validation source.
  • Per-call price: $0.16 USD.
  • Billing: per successful query. You are not charged when the registry is unreachable, when required fields are missing, or when the request is rejected before reaching the source.
  • Latency: typical p95 < 2 s.
  • Availability: 99.9% per quarter on Didit’s side; downstream source availability varies by country and dataset.

Continue reading