The Extract API uses AI to extract key information from unstructured text, such as names, emails, dates, amounts, and more. Simply send a block of text and a list of fields you want to extract — the API returns clean, structured JSON.
Built with FastAPI and OpenAI, this API is ideal for automating document processing, form filling, CRM enrichment, and more.
It supports flexible field definitions and works on everything from emails and messages to receipts and reports. Whether you're extracting one field or many, the response is fast, accurate, and ready for integration into your applications.
No need to train any models — the intelligence is built-in.
Extracts specific fields such as name, email, date, amount, or any custom key-value from raw text using AI. Send a block of text and a list of fields you want to extract, and the API returns structured JSON.
Extract - Endpoint Features
Object | Description |
---|---|
text |
[Required] The unstructured text to extract information from |
fields |
[Required] A list of field names to extract (e.g. name, email, amount) |
Request Body |
[Required] Json |
{
"message": "Data extracted successfully",
"data": {
"name": "Jane Doe",
"email": "[email protected]",
"amount": "$300",
"date": "May 12th"
}
}
curl --location --request POST 'https://zylalabs.com/api/8379/ai+data+extraction+api/14640/extract?text="John Doe lives at 123 Main St, NYC, phone: (555) 123-4567"&fields="name,address,phone"' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"text": "John Doe lives at 123 Main St, NYC, phone: (555) 123-4567",
"fields": "name,address,phone"
}'
Header | Description |
---|---|
Authorization
|
[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.
The Extract endpoint returns structured data in JSON format, including key fields such as names, emails, amounts, and dates extracted from the provided text.
The key fields in the response data typically include "name," "email," "amount," and "date." Additional custom fields can also be specified based on user requirements.
Users can customize their data requests by specifying a list of fields they want to extract from the input text. This allows for tailored data extraction based on specific needs.
The response data is organized in a JSON structure, containing a "message" field indicating success and a "data" field that holds the extracted key-value pairs.
Typical use cases include automating document processing, enriching CRM systems, filling forms, and extracting information from emails, receipts, and reports.
Data accuracy is maintained through the use of advanced AI algorithms that are built-in, ensuring reliable extraction from unstructured text without the need for user training.
Standard data patterns include recognizable formats for names, emails, dates, and monetary amounts. Users can expect consistent extraction results across various text types.
The Extract endpoint can extract various types of information, including personal identifiers (names, emails), financial figures (amounts), and temporal data (dates) from unstructured text.
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