vLex Anonymization API
Identify and anonymize personally identifiable information in text
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OpenAPI Specification
openapi: 3.2.0
info:
title: vLex Iceberg Anonymization API
description: The vLex Iceberg Anonymization API identifies and anonymizes names and personally identifiable information from any text input. Pre-trained on legal data to recognize personal names, organizations, and sensitive entities within legal documents, contracts, and court filings for privacy protection and data compliance workflows.
version: 1.0.0
contact:
name: vLex Developer Support
url: https://developer.vlex.com/
license:
name: Proprietary
url: https://vlex.com/
servers:
- url: https://api.vlex.com
description: vLex Iceberg API
tags:
- name: Anonymization
description: Identify and anonymize personally identifiable information in text
paths:
/v1/anonymize:
post:
operationId: anonymizeText
summary: Anonymize Text
description: Accepts a text input and identifies all personally identifiable information (names, organizations, and other sensitive entities). Returns the original text with identified entities replaced or tagged for anonymization. Pre-trained on legal data to handle case law, contracts, and regulatory documents.
tags:
- Anonymization
security:
- SubscriptionKey: []
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/AnonymizeRequest'
examples:
legalText:
summary: Anonymize a legal document excerpt
value:
text: In the case of John Smith v. ABC Corporation, filed on March 15, 2026 in the District Court of New York, the plaintiff John Smith alleges that...
mode: replace
replacement_token: '[PERSON]'
responses:
'200':
description: Anonymized text with identified entities
content:
application/json:
schema:
$ref: '#/components/schemas/AnonymizeResponse'
'400':
$ref: '#/components/responses/BadRequest'
'401':
$ref: '#/components/responses/Unauthorized'
'429':
$ref: '#/components/responses/RateLimited'
/v1/anonymize/entities:
post:
operationId: extractEntities
summary: Extract Named Entities
description: Extract named entities from text without replacing them. Returns a list of identified entities with their positions, types, and confidence scores. Useful for entity analysis and document review.
tags:
- Anonymization
security:
- SubscriptionKey: []
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ExtractEntitiesRequest'
responses:
'200':
description: List of identified entities
content:
application/json:
schema:
$ref: '#/components/schemas/ExtractEntitiesResponse'
'400':
$ref: '#/components/responses/BadRequest'
'401':
$ref: '#/components/responses/Unauthorized'
components:
responses:
BadRequest:
description: Invalid request
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
RateLimited:
description: Rate limit exceeded
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
Unauthorized:
description: Invalid or missing subscription key
content:
application/json:
schema:
$ref: '#/components/schemas/Error'
schemas:
ExtractEntitiesResponse:
type: object
description: Extracted entities from the input text.
properties:
entities:
type: array
items:
$ref: '#/components/schemas/Entity'
entity_count:
type: integer
processing_time_ms:
type: integer
AnonymizeRequest:
type: object
required:
- text
description: Request body for text anonymization.
properties:
text:
type: string
description: The input text to anonymize. Can be a legal document, contract, or any text containing personal data.
minLength: 1
maxLength: 50000
mode:
type: string
description: Anonymization mode.
enum:
- replace
- tag
- redact
default: replace
replacement_token:
type: string
description: Token to use when replacing identified entities (for mode=replace). Use entity-type-specific tokens like [PERSON], [ORG] or a generic [REDACTED].
default: '[REDACTED]'
entity_types:
type: array
items:
type: string
enum:
- PERSON
- ORGANIZATION
- LOCATION
- DATE
- EMAIL
- PHONE
- ID_NUMBER
description: Entity types to detect. Defaults to all types if not specified.
language:
type: string
description: BCP-47 language tag of the input text.
default: en
example: en
Entity:
type: object
description: A named entity identified in the input text.
properties:
text:
type: string
description: The original entity text as it appears in the document.
example: John Smith
entity_type:
type: string
description: The type of entity detected.
enum:
- PERSON
- ORGANIZATION
- LOCATION
- DATE
- EMAIL
- PHONE
- ID_NUMBER
example: PERSON
confidence:
type: number
format: float
description: Confidence score between 0 and 1.
minimum: 0
maximum: 1
example: 0.97
start_offset:
type: integer
description: Character offset where the entity begins in the input text.
end_offset:
type: integer
description: Character offset where the entity ends.
Error:
type: object
properties:
error:
type: string
message:
type: string
code:
type: integer
ExtractEntitiesRequest:
type: object
required:
- text
description: Request body for entity extraction.
properties:
text:
type: string
description: Input text to analyze.
minLength: 1
maxLength: 50000
entity_types:
type: array
items:
type: string
description: Entity types to extract.
language:
type: string
default: en
AnonymizeResponse:
type: object
description: Anonymized text with entity metadata.
properties:
anonymized_text:
type: string
description: The input text with detected entities replaced or tagged.
entities:
type: array
items:
$ref: '#/components/schemas/Entity'
description: List of all detected entities.
entity_count:
type: integer
description: Total number of entities detected.
processing_time_ms:
type: integer
description: Processing time in milliseconds.
securitySchemes:
SubscriptionKey:
type: apiKey
in: header
name: Ocp-Apim-Subscription-Key
description: vLex API subscription key obtained from the developer portal.
externalDocs:
description: vLex Developer Portal
url: https://developer.vlex.com/apis