Best Document Data Extraction APIs in 2024

Best Document Data Extraction APIs in 2024

What is Document Data Extraction API?

A programming interface known as a Document Data Extraction API, also referred to as a Data Extraction API, is a technology that analyzes a structured document and returns key / value pairs. These are sets of two items within a document—a label or key and its corresponding data (a value).

Depending on the needs of the application, the extracted data may contain text, numbers, dates, locations, and other pertinent information. This technique is frequently utilized in situations when data needs to be extracted from documents for subsequent processing, including document management, data input automation, content indexing, and many more situations.

Document Data Extraction APIs Use Cases

You can use Data Extraction in numerous fields, here are some examples of common use cases:

  1. Financial Services: Financial firms can use document data extraction APIs to automate processes like bank statement parsing, receipt analysis, and invoice processing. By minimizing human data entry and improving accuracy, this improves financial procedures and ultimately results in more effective financial management.
  2. Healthcare: These APIs are essential for converting paper-based systems in the healthcare industry to digital ones. They allow for the accurate processing of insurance claims, the digitization of medical records, and the efficient management of prescription data. As a result, administrative procedures are reduced and patient care is better coordinated.
  3. Legal: In the legal profession, document analysis is crucial. By indexing legal papers for quick retrieval and streamlining document search procedures, document data extraction APIs support in-depth contract analysis. Legal practitioners may manage legal papers effectively and make educated decisions thanks to technology.
  4. Retail and E-commerce: Order processing, inventory updates, and effective product catalog management are made possible through APIs created for the retail and e-commerce industries. Businesses can improve customer satisfaction and operational efficiency by automating these operations to ensure that customers receive correct and current information.


Best Document Data Extraction APIs on the market

While comparing Document Data Extraction APIs, it is crucial to consider different aspects, among others, cost security and privacy. Data Extraction experts at Eden AI tested, compared, and used many Data Extraction APIs of the market. Here are some actors that perform well (in alphabetical order):

  • Amazon
  • Butlerlabs
  • Google

1. Amazon - Available on Eden AI

Amazon Textract is a machine learning (ML) service that uses scanned documents to automatically extract text, handwriting, and data. To recognize, comprehend, and extract data from forms and tables, it goes beyond simple optical character recognition (OCR). Textract uses machine learning to accurately extract text, handwriting, tables, and other data from any form of document without the need for personal intervention. Whether you're automating the loan application process or extracting data from invoices and receipts, you can process documents fast and take action on the information extracted. Instead of taking hours or days to extract the data, Textract can do so quickly.

2. - Available on Eden AI is artificial intelligence software that can swiftly and accurately extract OCR text, data, handwriting, and images from a variety of documents, including ID cards, licenses, and much more. For most document kinds, it provides 99% accuracy. OCR, data extraction, and integration often take less than three seconds. It instantly determines the document type, extracts the necessary information, validates the results, and integrates them into the client's systems while saving the client thousands of staff hours each month through automated document processing.

3. Butlerlabs

Machine learning models from Butlerlabs called document extraction models can be used to extract important data from your documents. Predefined and customized models fall into two different categories of document extraction. The easiest and most precise document extraction is this one. It makes use of cutting edge ML to guarantee extraction accuracy of 95% or more on any document, tailored to your specific use case.

4. Google Cloud

A Google Cloud service called Document AI is made to automatically extract data from scanned or digital documents. It can recognize and extract tables, key-value pairs, and structured data from documents like invoices, contracts, and more, making it simpler to comprehend, process, and use. It aids in the development of scalable, end-to-end, cloud-based document processing systems using machine learning and Google Cloud.


FormX is a data extraction tool that converts information from physical documents into structured digital data using artificial intelligence (AI). The data extraction process is API-based, and JSON-formatted results are returned. It has preconfigured data extraction models for the majority of official licenses, identity cards, and common shopping receipts. It's a straightforward solution that works with any software and is developer- and business-friendly!

Performance variations of Document Data Extraction API

Data Extraction API performance can vary depending on a number of variables, including the technology used by the provider, the underlying algorithms, the amount of the dataset, the server architecture, and network latency. Listed below are a few typical performance discrepancies between several Data Extraction APIs:

  • Document Complexity: The complexity of the documents being processed can significantly impact performance. Simple and well-structured documents might yield faster and more accurate results compared to documents with complex layouts, handwriting, or poor image quality.
  • Document Type: Different types of documents require different extraction methods. Invoices, receipts, contracts, scientific papers, and handwritten notes each present unique challenges. APIs might excel in one area but struggle with others.
  • Volume of Data: Processing a large volume of documents concurrently can impact performance. APIs might have rate limits or varying response times based on the number of requests.

How to use Document Data Extraction with the Eden AI API?

To start using Data Extraction you need to create an account on Eden AI for free. Then, you'll be able to get your API key directly from the homepage and use it with free credits offered by Eden AI.

Eden AI stands out as an exceptional platform that harnesses the power of the best Document Data Extraction APIs available. By integrating cutting-edge technologies, Eden AI ensures high accuracy, speed, and versatility in extracting data. Upload the document (PNG, JPG or PDF) to extract the data.

You can then compare the different responses you get from the different providers:

Why choose Eden AI to manage your Document Data Extraction APIs

‍Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate Document Data Extraction tasks in their cloud-based applications, without having to build their own solutions.

Eden AI offers multiple AI APIs on its platform among several technologies and specifically Document Parsing APIs like Invoice parser, Resume parser, ID parser, Receipt parser and many more!

We want our users to have access to multiple Docment Data Extraction engines and manage them in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple APIs :

  • Fallback provider is the ABCs: You need to set up a provider API that is requested if and only if the main Document Data Extraction API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
  • Performance optimization: After the testing phase, you will be able to build a mapping of providers’ performance based on the criteria you have chosen (languages, fields, etc.). Each data that you need to process will then be sent to the Best Document Data Extraction API.
  • Cost - Performance ratio optimization: You can choose the cheapest Document Data Extraction provider that performs well for your data.
  • Combine multiple AI APIs: This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because Document Data Extraction APIs will validate and invalidate each other for each piece of data.

How Eden AI can help you?

‍Eden AI has been made for multiple AI APIs use. Eden AI is the future of AI usage in companies.

  • Centralized and fully monitored billing on Eden AI for all Document Data Extraction APIs.
  • Unified API for all providers: simple and standard to use, quick switch between providers, access to the specific features of each provider.
  • Standardized response format: the JSON output format is the same for all suppliers thanks to Eden AI's standardization work. The response elements are also standardized thanks to Eden AI's powerful matching algorithms.
  • The best Artificial Intelligence APIs in the market are available: big cloud providers (Google, AWS, Microsoft, and more specialized engines).
  • Data protection: Eden AI will not store or use any data. Possibility to filter to use only GDPR engines.

You can see Eden AI documentation here.

Next step in your project

The Eden AI team can help you with your Document Data Extraction integration project. This can be done by :

  • Organizing a product demo and a discussion to better understand your needs. You can book a time slot on this link: Contact
  • By testing the public version of Eden AI for free: however, not all providers are available on this version. Some are only available on the Enterprise version.
  • By benefiting from the support and advice of a team of experts to find the optimal combination of providers according to the specifics of your needs.
  • Having the possibility to integrate on a third-party platform: we can quickly develop connectors.

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