Most Efficient Data Extraction Techniques for PDFs: Parsing, OCR, and AI OCR

19 Nov, 2024

Most Efficient Data Extraction Techniques for PDFs: Parsing, OCR, and AI OCR

Introduction

We have all struggled with extracting tables and content from PDFs. This is because PDFs are designed to preserve the formatting of a document, which makes them great for reading but an absolute nightmare for extracting data. Over the years, technology has stepped up to help, from basic parsers to OCR to most recently, AI-powered extraction tools.

Each of these methods vary in cost, accuracy, and the types of documents that they are ideally suited for. Picking the right kind of data extraction tools can save you millions, depending on the kinds and volumes of documents you’re processing.

In this blog, we’ll walk you through the three major technologies used for data extraction—Parsers, OCR, and AI OCR—how they work, what types of documents they’re best for, and how much they cost. Whether you’re dealing with simple invoices or complex legal contracts, you’ll be able to choose the most efficient technique for your needs.

Technologies Used in Extraction

Parser

What It Is:

A parser is a rule-based extraction tool that reads structured data in a document, often focusing on tables, bullet points, or data in predictable locations. If you have a PDF with well-defined sections, a parser can quickly extract that info.

How It Works:
Think of a parser like a well-trained dog sniffing out specific sections. It’s looking for data that follows consistent patterns (e.g., invoices with the same layout). It uses positional or pattern recognition to locate the data and pull it out. For example, it can grab all invoice numbers, GST numbers, bank account details ec. in a consistent spot on every PDF.

Best for:

Financial data (invoices, tables).
Forms with well structured sections that follow fixed patterns.
Natively digital documents. Parsers don’t work well on scanned copies or images.

OCR (Optical Character Recognition)

What It Is:
OCR converts scanned documents or images into editable, searchable text. It’s great for printed PDFs or older documents that don’t contain digital text.

How It Works:
OCR works by recognizing individual characters from an image and transforming them into digital text. This is particularly useful for scanned documents or PDFs that started as physical papers. OCR essentially “reads” the document and extracts the text, which you can then manipulate or search.

Best for:

Scanned PDFs (e.g., historical documents, contracts, printed forms).
PDFs without selectable text (e.g., images of text).

AI OCR

What It Is:
AI OCR takes regular OCR to the next level. It combines machine learning and AI to not only recognize characters but also understand context and relationships between data elements, like tables, columns, or key phrases.

How It Works:
Using AI, this method goes beyond extracting characters—it interprets them. AI OCR can extract tables across multiple pages, recognize patterns even if the layout changes, and maintain data accuracy. It’s particularly useful for unstructured PDFs where data doesn’t follow a set pattern.

Best for:

Complex documents (multi-page PDFs, varied layouts).
Unstructured or semi-structured data.

Comparison of Technologies: Parser vs. OCR vs. AI OCR

Technique	Best For	Strengths	Weaknesses
Parser	Structured data (tables, forms)	Quick, accurate for predictable formats	Struggles with unstructured data, multi-page tables
OCR	Scanned PDFs, printed documents	Good for text recognition from images, great for scanning	Struggles with layout, lacks ability to understand table relationships
AI OCR	Complex, unstructured documents	Can extract data with context, handle multi-page tables, and various formats	More expensive, requires setup for optimal performance

What Kind of Extraction is Required for Different Document Types

Choosing the right extraction technique depends on the type of document you’re working with:

Invoices and Financial Reports: A parser works great here because these documents usually follow a consistent format. If your reports are highly structured, this is the fastest and cheapest option.
Scanned Contracts or Printed PDFs: OCR is your best bet for any document that started as paper. It can convert printed text into searchable and editable formats, but it might struggle with complex layouts, multi page tables, and poor quality scans.
Legal Contracts, Unstructured documents and Complex Multi-Page PDFs: This is where AI OCR shines. It can understand document structure, understand context, extract key phrases, and handle irregular layouts—perfect for complex business documents.

Costs of Each Technique

Here’s a breakdown of the cost implications of each technique:

Parser:
Low cost. If you’re dealing with highly structured documents, parsers are fast and relatively cheap. Open-source options like Tabula are available, but enterprise versions might charge a small fee for automation features.
OCR:
Medium cost. Tools like Adobe Acrobat Pro can cost upwards of $15/month. They work well for standard PDFs but require manual cleanup for complex documents.
AI OCR:
High cost. AI OCR solutions are more expensive due to their ability to handle complex and unstructured data. Costs vary based on volume, but if you’re dealing with thousands of PDFs per month, AI OCR offers the best return on investment.

How to Choose the Right Extraction Method

Not sure which method to use? Here’s a quick guide to help you choose:

If your documents are well-structured and follow a consistent layout (like invoices, purchase orders, bills of lading), go with a parser for fast, affordable extraction.
If you’re working with scanned or printed documents, OCR is the way to go. It’s perfect for converting physical documents into editable digital formats.
For unstructured data and complex PDFs, like financial reports, medical data, due diligence data, and legal documents, AI OCR is your best choice. It understands context, adapts to different layouts, and reduces the manual cleanup required.

Conclusion

Data extraction doesn’t have to be painful. Whether you’re using a parser for structured data or deploying AI OCR for complex PDFs, there’s a tool for every need. OCR might be the perfect solution for scanned documents, but if you’re working with varying layouts or large multi-page tables, AI OCR can save you time and reduce errors.

Looking for a solution that scales with your business? TwingLabs offers flexible document processing plans based on your unique use case and custom trained AI-powered extraction tailored to your specific needs, whether you’re handling a handful of invoices or thousands of complex records.