Best Table Parsing APIs in 2024

Best Table Parsing APIs in 2024

What is Table Parsing?

Table Parsing API, often referred to as OCR Table, allows applications to extract information from tables in scanned documents, images, or PDFs. The API leverages Optical Character Recognition (OCR) technology to recognize and retrieve data from tables then converts the extracted information into a structured format, such as a CSV or JSON file.

Table Parser on Eden AI
Table Parser on Eden AI

This type of technology is commonly used in business applications, where large amounts of data need to be processed and analyzed. By automating the process of extracting information from tables, the API can save time and reduce the risk of manual errors. Additionally, the structured data output by Table Parser can be easily integrated into other applications or analyzed using data analysis tools.

Table Parsing APIs uses cases

You can use OCR Table in numerous fields, here are some examples of common use cases:

  • Business: retrieve financial data, such as sales and expenses, from spreadsheets and financial reports to facilitate financial analysis and decision-making.
  • E-commerce: extract product information, prices, and reviews from e-commerce websites to inform purchasing decisions and price comparison.
  • Healthcare: extract patient data from electronic medical records and other healthcare documents for research and analysis purposes.
  • Marketing: retrieve data from reports and other sources to inform marketing strategies and decisions.
  • Research: extract data from scientific articles and research papers for meta-analyses, systematic reviews, and other types of research.
  • Sports: extract player statistics and other data from sports websites and databases to analyze performance and make decisions.

These are just a few examples of the many different fields in which table parser APIs can be applied. The ability to extract structured data from tables and turn it into actionable information makes this API a valuable tool for a wide range of industries and applications.

Best Table Parsing APIs on the market

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

  • Amazon Textract
  • Asprise
  • Google Cloud Document AI
  • Microsoft Azure Form Recognizer
  • Rossum

1. Amazon Textract - Available on Eden AI

Amazon Web Services (AWS) provides a Table Parsing solution through its Amazon Textract service. The service uses advanced Machine Learning algorithms to analyze the structure of a document and then extract data with high accuracy, even if the table is complex or has merged cells. Amazon Textract can also handle a variety of input file formats, including PDF, JPEG, PNG, and TIFF.

2. Asprise

Asprise offers a comprehensive set of OCR and Document Parsing tools, including Table Parser API. Asprise's solution can extract data from both PDF and image-based tables and then output it in a variety of formats including CSV and XML, making it compatible with popular spreadsheet applications, like Excel, Google Sheets, and many more. Asprise also supports multiple-language recognition for their API (en, fr, de, es, ja, ko, zh, etc.)

3. Google Cloud Document AI - Available on Eden AI

Google Cloud offers a suite of tools for analyzing and processing documents named Document AI. The solution can extract tables from a variety of document formats, including PDFs and scanned images, even if they are complex or have varying layouts. The API then output data in a structured format. They also offer multiple-language support, including English, French, German, Italian, Spanish, Portuguese, Dutch, Russian, and more.

4. Microsoft Azure Form Recognizer - Available on Eden AI

Microsoft Azure offers an OCR Table API through their Form Recognizer service. By using Machine Learning algorithms, the API is trained to recognize a wide range of document layouts and can even learn to recognize new layouts over time. Azure's API can also handle tables with multiple headers and footers, making it a versatile tool for processing complex documents.

5.'s Table Parser can extract data from both PDF and image-based tables and output data in a variety of formats, including CSV, Excel, and JSON. The company also provides a simple REST API interface with multiple-language support, making it easy to integrate their tools into existing software projects.

6. Rossum

Rossum uses Machine Learning algorithms to identify the layout of the table and extract the data in a structured format. It can handle tables with merged cells, multi-line cells, and other complex table structures (with or without borders, different spacing, header rows, etc.)

Performance variations of Table Parser APIs

For all companies who use Table Parser in their software: cost and performance are real concerns. The Table Parser market is quite dense and all those providers have their benefits and weaknesses.

Performances of Table Parsing vary according to the specificity of data used by each AI engine for their model training. This means that some Table Parsing may perform great for some languages but won’t necessarily for others.

Variation performances across languages

Table Parsing APIs perform differently depending on the language of the text. Some providers are specialized in specific languages. Different specificities exist in Region specialties: some Table Parsing APIs improve their machine learning algorithm to make them accurate for text in a specific language. For example, some Table Parsing APIs perform well in translating English (US, UK, Canada, South Africa, Singapore, Hong Kong, Ghana, Ireland, Australia, India, etc.), while others are specialized in Asian languages. Rare language specialty: some Table Parsing vendors care about rare languages and dialects. You can find Table Parsing APIs that allow you to process text in Gujarati, Marathi, Burmese, Pashto, Zulu, Swahili, etc.

Variation performances depending on the quality of the document

When testing multiple Table Parsing APIs, you will find that providers' accuracy can be different according to text quality. For example, some Table Parser APIs may perform better for handwriting text while others may perform better for digital text.

Why choose Eden AI to manage your Table Parser 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 Table Parsing tasks in their cloud-based applications, without having to build their own solutions.

Eden AI offers multiple AI APIs on its platform amongst several technologies: Text-to-Speech, Language Detection, Sentiment Analysis, Summarization, Question Answering, Data Anonymization, Speech Recognition, and so forth.

We want our users to have access to multiple Table Parser 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 Table Parser 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 OCR Table API.
  • Cost - Performance ratio optimization: You can choose the cheapest Table Parsing 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 Table Parsing 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. Eden AI allows you to call multiple AI APIs.

Eden AI platform - Multiple AI engines in one API
Multiple AI engines in one API

  • Centralized and fully monitored billing on Eden AI for all Table Parsing 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 Table Parsing 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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