How To Extract Data From PDF Automatically Using AI

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Artificial intelligence (AI) has emerged as a transformative force in today's fast-paced business landscape. It has redefined the way companies operate, make decisions, and interact with customers. One such area where AI has made a huge impact is in automating data extraction from PDFs. While PDFs are ubiquitous in the business world, extracting data from them is often a manual process. Why? Well, because of its nature. PDFs are essentially formatted for humans to read, not machines. However, with AI, this monotonous and time-consuming task can now be automated.

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So, how can AI help businesses extract data from PDFs? And what benefits does it bring? If you're curious to know, then read on!

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How to Extract Data from PDF Using AI?

Let's be real. If you only have a few PDF documents to extract data, the manual copy & paste method might be the most efficient option. This process is quite simple. Open each document, select the data you need to extract, and then copy & paste it into the desired location. But what if you have a large number of PDFs? It's simply not feasible to spend hours manually extracting data from each one.

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This is where AI comes in. AI-automated data extraction tools can help businesses save time and resources by automatically extracting data from large volumes of PDF documents, validating and verifying the information, and then transferring it to the desired location in a matter of seconds.

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Here's how you can use AI to extract data from PDFs:

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1. Upload the Document: The first step is to upload the PDF document (e.g., invoices, sales orders) into the AI tool. The tool will then scan the document and identify areas that contain data to be extracted.
2. Data Extraction: Next, the AI tool will use advanced algorithms and LLMs to extract the data from the identified areas of the document. This could include things like invoice numbers, customer names, order dates, etc. .
3. Verify and Validate Data: The AI-powered tool will then verify and validate the extracted data to ensure accuracy. This is done by comparing the data against predetermined rules and patterns.
4. Transfer the Data: Once the data has been validated, you can either choose to have it automatically transferred to your desired location (e.g., ERP/CRM system) or review it before transferring.

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How Does AI Work for PDF Data Extraction?

Also known as intelligent data capture, AI-based data extraction involves using AI, LLMs, and NLP techniques to extract relevant information from a PDF file, regardless of its structure or layout.

Here's a simplified process flow of how AI-powered solutions work to extract data from PDF documents:

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1. Data Ingestion:

This step is the foundation of the entire process. The process starts by ingesting unstructured data from a variety of sources, like scanned documents, emails, PDFs, images, or digital files, into the AI system.

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2. Preprocessing:

After data ingestion, the next step is to preprocess the data. This could include tasks like noise reduction, image preprocessing, or enhancement to enhance the quality and readability of the data. The goal here is to prepare the documents for data extraction, for example, converting images or scanned documents into digital text. OCR is often used in this step to analyze images, scanned documents, or handwritten text and convert them into machine-readable text.

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3. Data Extraction:

Once the data is preprocessed, the AI system uses a variety of techniques, such as LLMs and NLP, to identify and extract relevant information from documents. This might involve identifying key fields, such as names, addresses, dates, invoice numbers, etc., and extracting the pertinent data from different sections of the document.

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4. Data Validation and Verification:

AI solutions don't just extract text from PDF documents. They also validate and verify the extracted data to ensure its accuracy and reliability. This might involve cross-checking data against existing databases, performing data validation checks, or comparing data against predefined-defined rules to identify any discrepancies or errors. For example, if a purchase order is missing a date or an invoice number, the AI system will identify the error, flag it, and send notifications to the relevant team for correction.

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5. Data Integration:

Once the data is extracted, verified, and validated, the final step is to enter it into your system or database. AI-backed solutions can seamlessly integrate with existing systems, like CRMs or ERPs, eliminating the need for manual data entry and reducing the risk of errors. This means that businesses can have accurate, up-to-date, and error-free data at their fingertips to make informed decisions.

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Technologies Used to Extract Data from PDF

Now that you have a fair idea of how AI works to extract data from PDF documents, let's discuss the key technologies that power these solutions:

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Optical Character Recognition (OCR)

Optical character recognition (OCR) is a commonly used technique for extracting data from PDFs. ORC-based data extraction tools can effectively extract data from a structured PDF document with a predictable layout.

However, when it comes to documents with varying layouts and structures, OCR-based solutions fall short as they rely on recognizing data based on its coordinates within the document. This means that whenever there's a change in the layout or structure of the document, you or your team will need to manually adjust the OCR settings.

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Natural Language Processing (NLP)

Natural language processing (NLP) and rules-based techniques are also widely used for extracting data from PDFs. While these methods are good for extracting text from documents with consistent structures, they, too, have their limitations when it comes to dealing with large volumes of data.

However, NLP approaches can be useful for cleaning up text that has been extracted from a PDF. For example, NLP models can detect and filter out any symbols or noise that may have been inserted into the document during the encoding process, resulting in cleaner and more accurate data.

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AI-based Solutions

AI-based solutions, on the other hand, offer a more efficient and scalable approach to extracting data from PDFs. Unlike OCR techniques, AI can learn and understand the context and meaning of data within a PDF document. This allows them to accurately extract data from different types of documents ( like invoices, sales orders, contracts, purchase ordersPOs, etc.) regardless of their layout or structure.

Moreover, AI-backed solutions can also extract data from handwritten notes or even images within a PDF, which is an added advantage for businesses dealing with a large variety of document types.

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The Challenges with Extracting Data from PDFs

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Image credit: Ideagram

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Portable document format (or more commonly known as PDF) is like a double-edged sword for businesses. On one hand, it provides a lot of flexibility in terms of how information can be stored and shared. PDFs can be opened and viewed by anyone, regardless of what software they use. PDFs don't have any structure or schema rules, which makes it easy for businesses to organize their data in a way that makes sense to them. In a word, PDFs are ubiquitous in today's digital age.

However, this very flexibility comes with its own set of challenges when it comes to extracting data from PDFs. Here are some of the most common challenges that businesses face:

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1. Inconsistent Layout & Formatting

PDF documents often have an inconsistent layout, which means that the data is not presented in a uniform manner. This makes it difficult to programmatically extract text, tables, or images in a way that retains the original meaning or structure of the document. For example, if a PDF has multiple columns or non-linear text flow, it can confuse basic extraction tools and result in incomplete or incorrect data.

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Moreover, different PDFs from the same source may have variations in how information is presented. For instance, one PDF document may have a particular data field in bold and underlined, while another may have the same field in italics or highlighted in a different color. This inconsistency in formatting can lead to data extraction errors and make it difficult for businesses to efficiently extract and use the data.

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2. Data Quality & Types

When dealing with scanned PDFs, the quality of the scan can greatly affect the ability to extract data. Low-quality scans may result in OCR errors, missing information, or incorrect data extraction, so businesses may need to manually correct these errors or utilize advanced error-handling algorithms.

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Aside from the quality of the scan, PDFs can also contain a mix of different data types like text, images, tables, charts, and even multimedia elements. Now, extracting data from these varied types of content requires different strategies and technologies, adding another layer of complexity to the extraction process.

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3. Security Features & Encrypted Files

Some PDFs contain embedded or encrypted data, which requires additional steps to access and decode before data extraction can take place. PDFs can include security settings that prevent copying, printing, or editing the document. To extract data from these types of PDFs, businesses may need to provide appropriate permissions or find ways to bypass these security measures.

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The following images are an example of an order confirmation received as a scanned PDF document with handwritten notes and the text that was extracted from it using AI-powered solutions.

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As you can see, the scanned PDF document, which is a PO confirmation containing handwritten notes (like changes in delivery date), may be easy for a human to understand, but not so much for machines. Extracting data from such varied and unstructured PDF documents is not simple; it requires the ability to detect and understand the meaning of the data in order to accurately extract it. turian AI, with its advanced document extraction capabilities, was able to correctly identify the delivery date as 08.02.2024, even though it was written in a different format than the rest of the text. This is just one example of how turian can help businesses overcome the challenges of extracting data from complex and unstructured PDF documents.

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The Benefits of Using AI for PDF Data Extraction

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Image credit: DilokaStudio

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AI-backed solutions bring a range of benefits to businesses when it comes to extracting data from PDF documents. Unlike manual data extraction, where your team reads each document line by line, extracts required/essential data, verifies it, and then manually enters the data into your system. AI tools automate the entire process from start to finish.

Here are some of the main benefits that businesses can enjoy when using AI for PDF data extraction:

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1. Fast and Efficient Data Extraction

One of the key perks of using AI for PDF data extraction is its speed and efficiency. AI-powered solutions can process, extract, and organize data from a large number of PDF documents in a matter of minutes, whereas manually performing the same task would take hours or even days. This not only saves time but also increases productivity and allows your team to focus on more valuable tasks.

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2. More Accurate and Reliable Data

In a manual data extraction process, there is always a chance of human error. These errors can range from simple typos to missing out on important information, which can ultimately affect the quality and integrity of your data. AI-powered solutions eliminate the need for manual data entry, which in turn, reduces the risk of human errors.

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This means:

• No more duplicate entries or missing information
• No more spending hours fixing errors in your data
• Better data quality and integrity for decision-making

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3. Adaptability to Various Document Types

AI solutions are designed to adapt to different document layouts, formats, and structures. This means that whether your PDF files have tables, charts, images, or text-based data, AI-powered solutions can extract the relevant data accurately and efficiently. This adaptability makes AI the perfect solution for businesses that deal with a large volume of PDF documents with varying layouts and formats.

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4. Cost-Effective Solution

By automating the data extraction process, businesses can save significant costs associated with manual data entry, such as labor costs and the cost of human errors.

AI-powered solutions require a one-time investment, and once implemented, they can significantly reduce operational costs in the long run. Moreover, AI-powered solutions are designed to be scalable, which means they can handle an increasing volume of PDF documents without requiring additional resources or expenses.

Aside from these key advantages, AI-powered data extraction solutions also offer improved data security, seamless integration with existing systems (e.g., CRMs and ERPs), and the ability to handle multilingual data, which make them a valuable asset for businesses looking to streamline their data extraction processes. In other words, AI solutions not only make your PDF data extraction process faster and more efficient, but they also provide a range of other benefits that can positively impact your business operations.

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Streamline and Automate Data Extraction from PDFs with turian:

If you're looking for a more efficient, reliable, and intelligent way to extract data from your PDF documents, then you should consider turian. Our solutions use the world's most advanced AI technology, including large language models (LLMs) with custom-tailored business rules and data querying techniques, to ensure accurate and hassle-free data extraction from all types of PDF documents. Whether you are dealing with invoices, sales orders, contracts, or any other type of document, no matter the layout, language, or complexity, our AI solution can handle it all.

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But turian isn't just limited to PDFs. Our AI-backed solution can extract data from various types of documents, including emails, Excel sheets, Word files, images, and even handwritten notes.

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turian not only extracts information from these documents but also understands the context and meaning behind the data, cross-verifies it with what's already available in your system, and provides accurate results. If there are any discrepancies or errors (e.g., typos or missing info), turian flags them for human review, saving you time and effort in manual data checking. For instance, if an invoice has a wrong PO number or missing price, turian will identify and highlight the issue and send it to a human reviewer for correction before it gets added to your system. This way, you can ensure the accuracy and consistency of your data without any manual effort.

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Moreover, turian can also handle complex tasks that require human-like understanding and decision-making, such as drafting responses to emails or analyzing customer feedback.. Unlike OCR tools, turian doesn't require any manual adjustment or training on your side. turian can adapt to any document format or layout in any language, making it a truly universal and scalable solution. Plus, turian can seamlessly integrate with your existing ERP/CRM system and popular email platforms (e.g., Outlook, Gmail) for a smoother and more streamlined workflow.

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On top of that, turian is a no-code solution, so you don't need any technical skills or prior training to implement and use it in your business processes. If you want to test or see how turian can help automate your data extraction from PDFs and streamline your business processes, we also offer a free Proof of Concept (PoC).

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