Age & Identity Verification

Tuteliq Verification is a production-grade identity and age verification pipeline that combines document intelligence, biometric matching, liveness detection, and multi-layer fraud prevention in a single API call. Most verification providers give you OCR and a face match. Tuteliq cross-references every data source on the document against every other — MRZ check digits, barcode data, OCR text, front vs. back, document vs. selfie — and flags any inconsistency as potential tampering. This catches forgeries that pass single-layer checks.

Age Verification

Confirm user age via document analysis, biometric estimation, or both.

Identity Verification

Full identity confirmation with document authentication, face matching, liveness detection, and fraud prevention.

Document Checks

45 countries with algorithmic validation. ICAO 9303 MRZ. PDF417 barcode decoding.

Fraud Prevention

7 cross-referencing layers, recapture detection, LLM-powered authenticity analysis, and IP geolocation checks.

What makes Tuteliq different

45-Country Document Validation

Algorithmic check digit validation for CPF, personnummer, Aadhaar, Codice Fiscale, CURP, SSN, and 39 more. Not just format checks — full mathematical verification.

7-Layer Cross-Referencing

MRZ vs. OCR. Barcode vs. OCR. Front vs. back. Document vs. selfie. Declared type vs. detected type. IP vs. document country. OCR confidence gating. Every inconsistency is flagged.

AI-Powered Authenticity

Vision model analyzes document layout, security features, fonts, and color consistency against known templates. Detects screen photos, printout recaptures, and digital manipulation.

Tier availability

Feature	Minimum Tier	Credits
Age Verification (liveness only)	Pro ($99/mo)	10 per verification
Age Verification (full)	Pro ($99/mo)	20 per verification
Identity Verification	Business ($349/mo)	25 per verification

Age Verification

POST /v1/verification/age Verify a user’s age through document analysis, biometric age estimation, or both. Returns a verified age range, confidence score, and detailed document intelligence.

Verification methods

Method	How it works	Best for
Document	Extracts DOB from government ID via OCR, MRZ parsing, and barcode decoding	High-assurance age gates, parental consent
Biometric	Estimates age from a selfie using vision AI (child/teen/adult classification)	Frictionless age checks, onboarding flows
Combined	Document + biometric with cross-reference — flags age inconsistencies > 10 years	Maximum assurance — verifies the document belongs to the person

Request

const result = await tuteliq.verifyAge({
  document: fs.createReadStream('id-front.jpg'),     // Government-issued ID
  documentBack: fs.createReadStream('id-back.jpg'),  // Optional — enables barcode reading + back cross-ref
  selfie: fs.createReadStream('selfie.jpg'),          // Optional — for biometric estimation
  method: 'combined',                                  // 'document' | 'biometric' | 'combined'
});

console.log(result.verified);        // true
console.log(result.estimated_age);   // 15
console.log(result.age_range);       // "13-15"
console.log(result.is_minor);        // true
console.log(result.confidence);      // 0.97
console.log(result.document_type);   // "passport"

Response

{
  "verified": true,
  "estimated_age": 15,
  "age_range": "13-15",
  "is_minor": true,
  "confidence": 0.97,
  "method": "combined",
  "document_type": "passport",
  "document_country": "GB",
  "biometric_age": 15,
  "document_age": 15,
  "document": {
    "ocr_confidence": 94,
    "mrz_valid": true,
    "document_number_valid": true,
    "expired": false
  },
  "credits_used": 20
}

Response fields

Field	Type	Description
`verified`	boolean	Whether age verification succeeded
`estimated_age`	integer	Best estimate of user’s age
`age_range`	string	Tuteliq age bracket: `under-10`, `10-12`, `13-15`, or `14-17`
`is_minor`	boolean	Whether the user is under 18
`confidence`	float	Confidence score (0.0-1.0)
`method`	string	Method used: `document`, `biometric`, or `combined`
`document_type`	string	Detected document type
`document_country`	string	ISO 3166-1 alpha-2 country code
`biometric_age`	integer	Age estimated from selfie (if provided)
`document_age`	integer	Age from document DOB (if provided)
`document.ocr_confidence`	integer	OCR confidence percentage (0-100)
`document.mrz_valid`	boolean	Whether MRZ check digits passed (if MRZ present)
`document.document_number_valid`	boolean	Whether document number passed algorithmic validation
`document.expired`	boolean	Whether the document has expired
`credits_used`	integer	Credits consumed

Age extraction sources

DOB is extracted from multiple sources and cross-referenced. Priority order:

MRZ (Machine Readable Zone) — Most reliable. ICAO 9303 check digit validated.
PDF417 barcode — US/Canadian driver’s licenses. AAMVA-encoded structured data.
OCR labels — Text patterns like “Date of Birth:”, “DOB:”, date formats.
Selfie estimation — Vision AI age bracket classification (fallback).

When multiple sources disagree, the verification flags the inconsistency.

Supported documents

Document Type	Coverage
Passport	All ICAO-compliant passports worldwide (MRZ validated)
National ID card	All countries with MRZ-equipped cards + 45 countries with document number validation
Driver’s license	All countries via OCR + US/Canada via PDF417 barcode
Residence permit	Via OCR text extraction

Documents must be a clear, well-lit photo in JPEG or PNG format. Maximum file size: 10MB.

Identity Verification

POST /v1/verification/identity Full identity verification combining document authentication, face matching, liveness detection, and multi-layer fraud prevention.

What it checks

Every identity verification runs all of these checks automatically:

Check	What it does
Document number validation	Algorithmic check digit verification for 45 countries (CPF, personnummer, Aadhaar, CURP, SSN, etc.)
MRZ validation	ICAO 9303 check digits on document number, DOB, expiry, and composite — catches any MRZ tampering
Document authenticity	AI vision analysis of layout, security features, fonts, colors, and photo integration
Recapture detection	Detects photos of screens (moire patterns), printouts, and photo-of-photo attacks
Face matching	128-dimensional descriptor comparison between document photo and live selfie
Liveness detection	Visual analysis: landmark motion, texture analysis, depth cues, cross-frame consistency
MRZ/OCR cross-referencing	Compares name, DOB, and document number between MRZ and printed text — flags mismatches as tampering
Front/back cross-referencing	Compares extracted data between document front and back sides
Barcode cross-referencing	Compares PDF417 barcode data against OCR and MRZ (US/CA licenses)
Document type consistency	Validates declared type matches MRZ-detected type (passport vs. ID card)
IP geolocation check	Flags geographic inconsistency between document country and request origin
OCR confidence gating	Flags low-confidence extractions as unreliable
Document expiry	Checks expiry from labels, MRZ, and barcodes
Age consistency	Cross-checks document age against selfie age estimate (flags > 10 year discrepancy)

Request

const result = await tuteliq.verifyIdentity({
  document: fs.createReadStream('id-front.jpg'),
  documentBack: fs.createReadStream('id-back.jpg'),  // Optional — enables barcode + back cross-ref
  selfie: fs.createReadStream('selfie.jpg'),
  documentType: 'passport',                           // Optional — enables type consistency check
});

console.log(result.verified);                // true
console.log(result.match_score);             // 0.98
console.log(result.liveness_passed);         // true
console.log(result.document_authenticated);  // true
console.log(result.checks.mrz_valid);        // true
console.log(result.checks.recapture);        // "none"

Response

{
  "verified": true,
  "match_score": 0.98,
  "liveness_passed": true,
  "document_authenticated": true,
  "estimated_age": 34,
  "is_minor": false,
  "confidence": 0.99,
  "document_type": "passport",
  "document_country": "GB",
  "flags": [],
  "checks": {
    "mrz_valid": true,
    "mrz_fields": {
      "document_number": "L898902C3",
      "nationality": "GBR",
      "date_of_birth": "1990-06-15",
      "expiry_date": "2030-01-01",
      "surname": "SMITH",
      "given_names": "JOHN WILLIAM"
    },
    "document_number_valid": true,
    "document_expired": false,
    "face_match": true,
    "liveness": true,
    "recapture": "none",
    "authenticity": {
      "is_authentic": true,
      "confidence": 0.94,
      "security_features": ["hologram", "microprint", "guilloche_pattern"],
      "anomalies": []
    },
    "barcode": {
      "format": "PDF417",
      "has_aamva": true,
      "first_name": "JOHN",
      "last_name": "SMITH",
      "date_of_birth": "1990-06-15",
      "state": "CA"
    },
    "cross_references_passed": true
  },
  "failure_reasons": [],
  "credits_used": 25
}

Response fields

Field	Type	Description
`verified`	boolean	All checks passed
`match_score`	float	Face match score (0.0-1.0)
`liveness_passed`	boolean	Liveness check passed
`document_authenticated`	boolean	Document passed authenticity checks
`estimated_age`	integer	Age from document DOB
`is_minor`	boolean	Under 18
`confidence`	float	Overall confidence (0.0-1.0)
`document_type`	string	Detected document type
`document_country`	string	ISO 3166-1 alpha-2 country code
`flags`	array	Warning flags (e.g., `low_ocr_confidence`, `geographic_inconsistency`)
`checks`	object	Individual check results — see below
`failure_reasons`	array	Human-readable reasons for failure (empty if verified)
`credits_used`	integer	Credits consumed

Checks object

Field	Type	Description
`mrz_valid`	boolean \| null	MRZ check digits valid (null if no MRZ)
`mrz_fields`	object \| null	Parsed MRZ fields with check-digit-validated data
`document_number_valid`	boolean \| null	Document number passed algorithmic validation
`document_expired`	boolean	Document expiry check
`face_match`	boolean	Face on document matches selfie
`liveness`	boolean	Liveness detection passed
`recapture`	string	`"none"`, `"screen"`, `"printout"`, or `"photo_of_photo"`
`authenticity`	object	AI-powered document authenticity analysis
`barcode`	object \| null	PDF417/barcode data (US/CA licenses)
`cross_references_passed`	boolean	All cross-referencing checks passed

Verification outcomes

Status	Meaning	Examples
`verified`	All checks passed	Valid document, face match, liveness passed
`failed`	Hard failure — definitive fraud signal	Liveness failed, face mismatch, recapture detected
`needs_review`	Soft failure — human review recommended	Low OCR confidence, document expired, name mismatch between MRZ and printed text

Integration patterns

// 1. Verify age during sign-up
const verification = await tuteliq.verifyAge({
  selfie: selfieStream,
  method: 'biometric',
});

// 2. Store the verified age group
const ageGroup = verification.age_range;  // "13-15"

// 3. Use verified age group in all safety calls
const safety = await tuteliq.detectUnsafe({
  text: messageContent,
  ageGroup: ageGroup,  // Properly calibrated risk scoring
});

// 1. Verify child's age
const childAge = await tuteliq.verifyAge({
  selfie: childSelfieStream,
  method: 'biometric',
});

if (childAge.estimated_age < 13) {
  // 2. Verify parent's identity
  const parent = await tuteliq.verifyIdentity({
    document: parentIdStream,
    selfie: parentSelfieStream,
  });

  if (parent.verified && !parent.is_minor) {
    await grantParentalConsent(childUserId, parent);
  }
}

Moderator/admin verification

const identity = await tuteliq.verifyIdentity({
  document: documentStream,
  selfie: selfieStream,
});

if (identity.verified && !identity.is_minor) {
  await grantModeratorRole(userId);
}

Error handling

Verification errors use the VRF_9xxx code range:

Code	HTTP	Description
`VRF_9001`	400	Document image is required
`VRF_9002`	400	Document image is unreadable or too low quality
`VRF_9003`	400	Unsupported document type
`VRF_9004`	400	Selfie image is required for liveness check
`VRF_9005`	400	Face not detected in selfie
`VRF_9006`	400	Liveness check failed
`VRF_9007`	500	Verification service error (safe to retry)
`VRF_9008`	403	Age verification not available on your plan (requires Pro)
`VRF_9009`	403	Identity verification not available on your plan (requires Business)

try {
  const result = await tuteliq.verifyIdentity({
    document: documentStream,
    selfie: selfieStream,
  });
} catch (error) {
  if (error instanceof TuteliqError) {
    switch (error.code) {
      case 'VRF_9002':
        // Ask user to retake photo with better lighting
        break;
      case 'VRF_9006':
        // Liveness failed — possible spoofing attempt
        break;
    }
  }
}

Data handling

Verification involves sensitive personal data. Tuteliq processes documents and selfies in real time and does not store images or extracted PII after the verification is complete. Only the verification result (age range, pass/fail) is retained. See the GDPR page for data handling details.

Next steps

Document Checks

Deep dive into 45-country document validation, MRZ parsing, and barcode reading.

Liveness Detection

How visual liveness analysis prevents spoofing attacks.

Fraud Prevention

Multi-layer cross-referencing, recapture detection, and authenticity analysis.

Getting Started

SDKs

Integrations

Verification

Advanced

Compliance

Age & Identity Verification

Age Verification

Identity Verification

Document Checks

Fraud Prevention

What makes Tuteliq different

45-Country Document Validation

7-Layer Cross-Referencing

AI-Powered Authenticity

Tier availability

Age Verification

Verification methods

Request

Response

Response fields

Age extraction sources

Supported documents

Identity Verification

What it checks

Request

Response

Response fields

Checks object

Verification outcomes

Integration patterns

Moderator/admin verification

Error handling

Data handling

Next steps

Document Checks

Liveness Detection

Fraud Prevention

Getting Started

SDKs

Integrations

Verification

Advanced

Compliance

Age Verification

Identity Verification

Document Checks

Fraud Prevention

​What makes Tuteliq different

45-Country Document Validation

7-Layer Cross-Referencing

AI-Powered Authenticity

​Tier availability

​Age Verification

​Verification methods

​Request

​Response

​Response fields

​Age extraction sources

​Supported documents

​Identity Verification

​What it checks

​Request

​Response

​Response fields

​Checks object

​Verification outcomes

​Integration patterns

​Age gate on sign-up

​Parental consent flow (COPPA)

​Moderator/admin verification

​Error handling

​Data handling

​Next steps

Document Checks

Liveness Detection

Fraud Prevention

What makes Tuteliq different

Tier availability

Age Verification

Verification methods

Request

Response

Response fields

Age extraction sources

Supported documents

Identity Verification

What it checks

Request

Response

Response fields

Checks object

Verification outcomes

Integration patterns

Age gate on sign-up

Parental consent flow (COPPA)

Moderator/admin verification

Error handling

Data handling

Next steps