Document parsing is the process of recognizing/examining data in a document and extracting useful information from it. For instance, data from PDF and Word documents can be extracted using document parser APIs and stored in a JSON file. How so? Thanks to Optical Character Recognition (OCR) and Named Entity Recognition (NER) technologies, Document Parser APIs are built in a way to extract textual content first, then locate and classify named entities into categories such as names, locations, quantities, percentages, etc.
Document Parsing can be found in various industries, to automate manual processes and improve data entry efficiency or to help with the digitalization of companies and eliminate paperwork for good.
You can choose between several Document Parser APIs depending on the documents you want to analyze:
As mentioned above, Optical Character Recognition is the conversion of images of typed, handwritten, or printed text into machine-encoded text, whether from a document, or a photo of a document.
One of the many use cases of Document Parsing is the extraction of data from images of tables. With Table Extraction API, you can automatically detect tables & extract all tabular data from documents in one go.
Invoice Parsing is a technique that lets you extract and digitalize meaningful data from scanned or PDF invoices. Fields commonly captured by Invoice OCR include description, quantity, due date, line items, invoice number, merchant information, customer information, unit price, bill, receipt number, total amount, tax amount, etc. If you’re interested in Invoice Parsing, we recommend reading our Top 10 OCR Invoice Parser APIs.
Resume Parsing is the conversion of a CV into a structured set of information suitable for storage, reporting, and manipulation by software. Resume parsing helps recruiters efficiently manage resume documents sent electronically. For more insight on CV parsing, here is our Top 10 OCR Resume Parser APIs.
Receipt Parsing allows you to extract data from scanned receipts: total amount, list of tax items, date, time, purchase categories, supplier information, currency, location, etc. Choosing the right receipt OCR for your application can be challenging, which is why our OCR experts came up with a Top 10 Receipt Parser APIs to help you out.
Initially designed for financial documents such as receipts or invoices, OCR also allows the scanning of passports and driving licenses, including data extraction. OCR for ID documents works on all ID documents: ID card, passport, driving license, etc.
While comparing Document Parsing APIs, it is crucial to consider different aspects, among others, cost security and privacy. Document Parsing experts at Eden AI tested, compared, and used many Document Parsing APIs of the market. Here are some actors that perform well (in alphabetical order):
For all companies who use Document Parsing in their software: cost and performance are real concerns. The Document Parsing market is quite dense and all those providers have their benefits and weaknesses.
Performances of Document Parsing vary according to the type of data used by each AI engine for their model training: AI engines are usually trained with specific data. This means that some Document Parsing APIs may perform great for some languages or type of images but won’t necessarily for others.
When testing multiple Document Parsing APIs, you will find that providers' accuracy can be different according to text quality. For example, some Document Parsing APIs may perform better with text coming from handwriting while others may perform better with text from digital text.
Document 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 Document Parsing APIs improve their machine learning algorithm to make them accurate for text in a specific language. For example, some Document 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 Document Parsing vendors care about rare languages and dialects. You can find Document Parsing APIs that allow you to process text in Gujarati, Marathi, Burmese, Pashto, Zulu, Swahili, etc.
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 Parsing tasks in their cloud-based applications, without having to build their own solutions.
We want our users to have access to multiple Document Parsing 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 Document Parsing APIs :
Set up a Document Parsing API that is requested if and only if the main Document Parsing API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
After the testing phase, you will be able to build a mapping of Document Parsing vendors’ performance that depends on the criteria that you chose (languages, fields, etc.). Each data that you need to process will then be sent to the best Document Parsing API.
You can choose the cheapest Document Parsing provider that performs well for your data.
This approach is required if you look for high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because Document Parsing APIs will validate and invalidate each other for each piece of data.
Eden AI is the future of AI usage in companies: our app allows you to call multiple AI APIs.
You can see Eden AI documentation here.
The Eden AI team can help you with your Document Parsing integration project. This can be done by :
In this article, we explain how the mapping between the input language and the languages supported by the providers is performed to facilitate access to one of our AI engines.