Content Integrity Checker API

Ensure content originality by detecting reuse, paraphrasing, and semantic adaptation across multiple languages.

About the API:  

Content Integrity Checker API offers an AI-driven solution for detecting plagiarism, paraphrasing, and semantic alterations in various types of content. With support for several languages such as English, German, French, Spanish, and Italian, this API scans and identifies both exact matches and loose reuses. Whether you are working in education, publishing, or digital media, Content Integrity Checker helps maintain content integrity by catching any unauthorized use or adaptations. With a quick, real-time analysis and seamless integration, this API ensures your content remains original, promoting creativity and safeguarding intellectual property.

API Documentation

Endpoints


Send a JSON body with the text to be parsed.The API will return exact matches, paraphrases and semantic adaptations of the inline content.

 

 

 



                                                                            
POST https://zylalabs.com/api/5799/content+integrity+checker+api/7559/check+text+originality
                                                                            
                                                                        

Check Text Originality - Endpoint Features

Object Description
Request Body [Required] Json
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"status":"success","results":[{"id":0,"queryText":"This is an example:\nThe rise of capable Generative AI has ushered in a new era of AI-generated co...","overallResults":{"textReused":true,"percentageOverlap":95.65,"earliestMatch":{"type":"Exact match","score":88,"scoreUnits":"words"},"matchScores":{"exactMatch":88,"looseMatch":0,"semanticMatch":0},"reuseMatches":["Exact match"],"sourceCount":1},"processStatus":{"completedStages":["Exact match"],"earlyTermination":{"occurred":true,"reason":"Exact match found"}},"reuseDetails":{"exactMatch":{"score":88,"scoreUnits":"words","percentageOverlap":95.65,"sources":[{"source":"https://genaios.ai/textmachina/","score":88,"scoreUnits":"words","percentageOverlap":95.65,"snippets":[{"querySnippet":"The rise of capable Generative AI has ushered in a new era of AI-generated content bringing with it countless positive use-cases, but also potential perils in the form of widespread automated misinformation and disinformation, fake reviews, reputational damage, and so forth.\nThis has brought with it a pressing need to automatically detect human content, detect AI-generated content, and determine the boundaries between the two. Explainability and transparency are also needed in the form of attribution of AI-generated text to the underlying Large Language model.","querySpan":[]}]}]},"looseMatch":{"score":0,"scoreUnits":"sentences","percentageOverlap":0.0,"sources":[]},"semanticMatch":{"score":0,"scoreUnits":"snippets","percentageOverlap":0.0,"sources":[]}}}]}
                                                                                                                                                                                                                    
                                                                                                    

Check Text Originality - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/5799/content+integrity+checker+api/7559/check+text+originality' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '[
  {
    "id": 0,
    "text": "This is an example:\nThe rise of capable Generative AI has ushered in a new era of AI-generated content bringing with it countless positive use-cases, but also potential perils in the form of widespread automated misinformation and disinformation, fake reviews, reputational damage, and so forth.\nThis has brought with it a pressing need to automatically detect human content, detect AI-generated content, and determine the boundaries between the two. Explainability and transparency are also needed in the form of attribution of AI-generated text to the underlying Large Language model."
  }
]'

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Content Integrity Checker API REST API, simply include your bearer token in the Authorization header.
Headers
Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Content Integrity Checker API FAQs

The Content Integrity Checker API can analyze various types of content, including text documents, articles, and digital media, to detect plagiarism, paraphrasing, and semantic alterations.

The API supports multiple languages, including English, German, French, Spanish, and Italian, allowing for a broad range of content analysis.

The API uses AI-driven algorithms to scan content for both exact matches and loose reuses, identifying unauthorized use or adaptations through advanced semantic analysis.

Yes, the Content Integrity Checker API is particularly useful in educational settings for maintaining academic integrity by detecting potential plagiarism in student submissions.

The API offers seamless integration options, allowing developers to easily incorporate its features into their applications for real-time content analysis.

The API returns a JSON response containing details about content originality, including exact matches, paraphrases, and semantic adaptations. It also provides metrics like percentage overlap and match scores.

Key fields include "status," "results," "overallResults," "processStatus," and "reuseDetails." Each field provides insights into the analysis outcome, match types, and processing stages.

The response data is structured in a hierarchical format, with a main "results" array containing individual match details. Each match includes metrics and sources, making it easy to navigate and interpret.

The primary parameter is the text to be analyzed, sent in a JSON body. Users can customize their requests by adjusting the content length and language, ensuring relevant analysis.

Users can leverage the "overallResults" to assess content originality quickly. The "reuseDetails" section provides specific sources and match types, enabling targeted revisions or citations.

Typical use cases include academic integrity checks, content verification for publishers, and ensuring originality in digital media. The API helps identify unauthorized adaptations and promotes ethical content creation.

The API employs advanced AI algorithms and machine learning techniques to ensure high accuracy in detecting content reuse. Continuous updates and training on diverse datasets enhance its reliability.

Users can expect results indicating whether text is reused, with specific percentages of overlap. The API typically categorizes matches into exact, loose, and semantic types, providing a comprehensive analysis.

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