AI Text Detector API

An AI Text Detector API is a software interface that leverages machine learning algorithms to analyze and detect whether a given text was generated by an AI model or a human.

About the API:  

This API can be valuable in a variety of contexts, such as detecting fake news, identifying chatbots or virtual assistants, and improving the quality of machine-generated text.

The API works by analyzing the language and patterns in the text and comparing them to a database of known samples of AI-generated text. It uses natural language processing (NLP) techniques to analyze the grammar, syntax, vocabulary and style of the text and determine whether or not it exhibits human-like characteristics.

One of the main applications of an AI text detection API is the detection of fake news and propaganda. With the proliferation of social networks and the ease of generating and sharing content, it is becoming increasingly difficult to distinguish between authentic and fake news. An AI Text Detector API can analyze the language and style of text and determine whether it was written by a human or an AI model, which can help identify fake news and prevent its spread.

Another use case for an AI Text Detector API is the identification of chatbots and virtual assistants. Many companies use chatbots or virtual assistants to automate customer service or support tasks, but it is essential to ensure that these bots are not impersonating human agents. An AI Text Detector API can analyze the language and style of text and identify whether it has been generated by a bot or a human. This can help ensure transparency and build trust with customers.

An AI Text Detector API can also be used to improve the quality of machine-generated text. With the rise of natural language generation (NLG) technologies, many companies are using AI models to generate text for various purposes, such as product descriptions, news articles or marketing copy. However, the quality of machine-generated text can vary significantly, and it is essential to ensure that it is indistinguishable from human-written text. An AI Text Detector API can analyze the language and style of the text and provide information to note the quality and consistency of the machine-generated text.

 

What this API receives and what your API provides (input/output)?

It will receive parameters and provide you with a JSON.

 

What are the most common uses cases of this API?

  1. Content moderation: An AI Text Detector API can be used to identify if the content being posted on a website or social media platform has been generated by an AI, which can help in preventing the spread of spam or fake news.

  2. Fraud detection: An AI Text Detector API can be used to flag messages or emails that have been generated by AI chatbots, which can help in identifying potential phishing scams.

  3. Plagiarism detection: Can be used to identify if the text being submitted for academic or professional purposes has been generated by an AI.

  4. Digital marketing: Can be used by marketers to identify if a message or comment on their social media or website has been generated by an AI, which can help in determining the authenticity of customer engagement.

  5. Content creation: Can be used by content creators to ensure that their work has not been generated by an AI, which can help in maintaining originality and creativity.

     

Are there any limitations to your plans?

Basic Plan: 3,000 requests and 75,000 words per month.

Pro Plan: 6,000 requests and 75,000 words per month.

Pro Plus: 20,000 requests and 75,000 words per month.

Premium Plan: 100,000 requests and 250,000 words per month.

API Documentation

Endpoints


To use this endpoint, all you have to do is insert the text you want to analyze.

Free trial: 

1,000 Words per day and 10 requests per day.



                                                                            
POST https://zylalabs.com/api/2009/ai+text+detector+api/1780/get+probability
                                                                            
                                                                        

Get Probability - Endpoint Features

Object Description
Request Body [Required] Json
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"confidence":"low","language":"en","predicted_class":"human","probabilities":{"ai":0.3844298781459912,"human":0.613689883128011,"mixed":0.0018802387259977912}}
                                                                                                                                                                                                                    
                                                                                                    

Get Probability - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/2009/ai+text+detector+api/1780/get+probability' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "text": "Technology is advancing at a rapid pace, transforming the way we interact, work and live. From artificial intelligence to automation, these innovations promise to facilitate our daily tasks, optimize processes and open up new opportunities in a variety of fields. However, they also present ethical and social challenges that we must address."
}'

    

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 AI Text Detector 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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 Service Level
99%
 Response Time
720ms

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