What Is Document Processing And How Can It Be Automated?

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Every business (regardless of its size or sector) deals with documents on a daily basis. Whether it's invoices, sales orders, or contracts, managing and processing these documents efficiently is crucial for businesses to streamline operations and maintain a competitive edge. While manual document processing was once the industry standard as it provides a sense of security, it is not scalable or efficient in the long run. Not only does it require a lot of time and effort, but it is also prone to human error, which can result in costly mistakes that can impact the overall business operations.

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To overcome the challenges of manual document processing, many businesses are turning to automation solutions such as optical character recognition (OCR) and intelligent document processing (IDP). OCR-based solutions can help extract data from simple documents with a structured layout, while IDP solutions use techniques like machine learning (ML) algorithms to extract, classify, and validate data from more complex documents with unstructured layouts.

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However, despite their capabilities, these solutions still have limitations. This set the groundwork for AI-based document processing solutions—a more advanced approach to automate the entire document processing workflow, end-to-end.

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So, what exactly is document processing? How can it be automated? And what benefits can businesses expect from adopting AI-based document processing solutions? We'll answer these questions and more so you can better understand the technology and make informed decisions for your business.

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Document Processing: Understanding the Basics

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Image credit: Storyset

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What is Document Processing?

Document processing is defined as the process of analyzing paper-based documents, images, and PDFs, extracting information, and converting them into structured, digital formats. This information can then be further utilized for various purposes, such as data analysis, storage, retrieval, and integration into other business systems like CRMs or ERPs.

Traditionally, document processing referred to the manual method where data entry operators scanned each document, extracted the required information, and entered it into a database or spreadsheet. However, with the advancements in technology, document processing, and data extraction tasks can now be streamlined and automated, making the process faster and more accurate.

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How Does Document Processing Work?

Document processing involves various techniques such as neural networks, computer vision algorithms, and manual labor to convert physical documents (analog data) into digital format.

Here's a breakdown of how document processing in general works:

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1. Document Categorization and Extraction of Structure/Layout

The first step in document processing is to categorize documents based on their layout and structure. Document processing solutions (without AI) rely on a set of predefined rules set by humans to identify and extract the structure and layout of a document. This process involves manual labor, as human input is necessary to define extraction rules for different document categories and formats.

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2. Document Information Extraction

Next, optical character recognition (OCR) is used to scan and convert paper-based documents into digital data. Another form of intelligent character recognition (ICR) is handwritten text recognition (HTR). This technology is capable of recognizing standard text, as well as various styles and fonts of handwriting. HTR is often used in image-to-text converters to extract text from images and documents automatically.

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3. Document Error Detection and Correction

While OCR can digitize physical documents, it is not always 100% accurate and may produce errors, so a manual review is necessary. If any errors are detected, the document can be flagged for human review and correction. This process may involve manual data entry to fix any errors found during the digitization process.

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4. Document and Data Storage

Once the final document is ready, it is then stored in a structured format(e.g., CSV, XML, etc.) that allows for easy integration with existing business systems or applications such as databases, CRMs, or ERPs.

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The Role of AI in Document Processing

Artificial Intelligence has been making significant strides in various industries, and document processing is no exception. AI-based document-processing solutions help businesses automate their document-related tasks, like document ingestion, extraction, validation, routing to the right teams for approval, and data entry. AI solutions not only take the burden off workers' shoulders but also streamline workflows, resulting in faster and more efficient document processing.

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AI-automated Document Processing Explained

AI-based document processing solutions go beyond just extracting, validating, and processing data from semi-structured and unstructured documents. They use advanced techniques like large language models (LLMs) and natural language processing (NLP) to understand the context and meaning behind the data, adapt to changes in document types and formats, and assist in making more informed decisions. AI-powered solutions don't just automate repetitive, manual tasks in document processing (e.g., data extraction and validation) like classical IDP software but can automate the entire document processing pipeline, from data ingestion to integration with business systems.

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Example: 

A sales team receives numerous purchase orders from different clients every day. An AI-based document processing solution will automatically ingest these documents, extract the required information (e.g., customer name, quantity, and price), and validate the data against pre-defined business rules. This automated document processing saves the sales team hours of manual work, allowing them to focus on more critical tasks that drive revenue and growth for the company, like building relationships with clients, identifying new opportunities, and closing deals.

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Technologies involved in AI-based Document Processing

Let's take a look at each of the technologies and its role in document processing:

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Large Language Models (LLMs)

LLMs are advanced AI models trained on vast text datasets to understand natural language and context. These models use deep learning techniques to analyze documents, identify patterns, and extract relevant information with high accuracy. LLMs can handle documents in various formats, structures, or languages, including unstructured data from sources like email-free texts, PDFs, Word files, and images. Moreover, LLMs continually improve their performance by learning from new data and feedback loops, resulting in more accurate data extraction and processing.

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Natural Language Processing (NLP)

NLP enables machines to understand, generate, and manipulate human language. NLP algorithms analyze text within a document, com­prehend its meaning, and extract information from it. NLP also helps with tasks like sentiment analysis, document classification, text summarization, and language translation. By leveraging NLP, AI solutions can accurately extract contextual information from documents and understand the relationships between different data points.

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What are AI Document Processing Core Functions?

AI-automated document processing solutions perform the following core functions:

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1. Document Capture

AI-based document processing automation solutions start by capturing data from different types of documents (e.g., PFDs, Word files, images, scanned documents) and converting them into machine-readable formats like text or structured data. AI algorithms and NLP techniques are employed to analyze the layout, structure, and text of the document to identify relevant data fields and extract them accurately, even if the data is unstructured or handwritten text.

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2. Data Extraction

After data capture, AI solutions automatically extract relevant data points from the document, such as customer name, address, amount, or any other information required for further processing. Unlike classical OCR solutions, which can't handle variations in document layouts, AI can extract data from various formats and layouts without any additional configuration or manual adjustments.

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3. Document Classification & Categorization

Depending on the document type, purpose, or content, AI can automatically classify and categorize documents into different groups. This allows the AI system to route them to the relevant team or department for further processing. For instance, if the document is a sales order, AI can send it to the sales team, whereas if it's an invoice, it can be routed to the accounting team. This not only saves time but also ensures each document is handled by the right team, reducing potential errors.

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4. Document Validation & Verification

After data extraction, AI can automatically validate the extracted information against predefined rules or business logic to ensure data accuracy and quality. This could involve cross-checking the information against existing systems (CRM/ERP) or flagging any discrepancies or errors for human review and correction. For example, if the total amount on an invoice doesn't match the expected amount in the system, the AI system triggers an alert to the accounting team for further investigation.

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5. Automated Document Processing Workflows

AI-powered document processing solutions don't stop at data extraction and validation; they can also automate the entire workflow associated with a document. This could include tasks such as routing documents for review and approval, triggering alerts or notifications for specific actions (e.g., missing information, urgent requests), and automatically updating data in the relevant systems. For instance, if a sales order is delayed, AI can send a notification to the customer service team, update the order status in the ERP system, and trigger a follow-up action like sending an email to the customer with a new estimated delivery date.

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Use Cases of AI-based Document Processing

Here are some of the most common scenarios where AI-based document processing can be applied:

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1. Sales Orders Processing

Manually processing sales orders involves a lot of manual effort, like manually entering data, cross-checking and validating information, generating quotes, and responding to customers. This not only takes up a lot of time but also increases the risk of human error and delays in the sales process. AI-based document processing can speed up this process by automatically extracting and matching order data, generating quotes or new sales orders, and even drafting replies to customers. This allows sales teams to respond faster to customers and free up their time for more important tasks.

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2. Invoice Processing

Invoices are crucial documents for any business, but manually processing invoices can be a tedious and error-prone task. With AI-based document processing, businesses can automate the entire invoice processing workflow from start to finish. AI solutions can extract relevant information from purchase orders (e.g., PO numbers, prices, quantities), validate it against the original order, and generate invoices. If there are any discrepancies (e.g., wrong quantities or prices), the AI agent can flag them for human review/approval before sending the final invoice to the customer. This not only saves time and effort but also ensures accuracy and consistency in the invoicing process.

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3. Purchase Order Processing

Similar to sales orders, purchase order processing involves a lot of manual tasks, including data entry, validating supplier information, and handling requests for quotes (RfQs). By leveraging AI, businesses can streamline this process by automatically extracting and matching data from purchase orders, comparing suppliers, and generating RfQs. AI solutions give businesses more control over their procurement processes as they can set custom rules and policies for different scenarios. Moreover, AI solutions can intelligently determine the next actions, such as updating ERP and purchase order systems, requesting missing information, or seeking user confirmation.

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Benefits of Choosing AI Document Processing Solutions

AI-based document processing solutions provide a broad spectrum of benefits compared to the traditional document processing system (e.g., manual data entry, classical IDP/OCR solutions).

Some of the key benefits include:

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1. Faster Data Processing & Turnaround Times

AI-powered document processing solutions can extract, validate, and process data from various documents (e.g., invoices, POs, receipts) at a much faster pace compared to manual data entry. This results in reduced turnaround times, allowing organizations to process large volumes of documents quickly and efficiently.

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2. Unstructured Documents Processing

With unstructured data comprising 80% of the digital data universe, classical OCR solutions can't capture this data accurately. AI document processing solutions, on the other hand, use LLMs to understand and extract messy, unstructured data from different sources like email-free texts, Word files, images, and even handwritten documents.

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3. Higher Accuracy Rates & Reduced Errors

In manual document processing, human error is inevitable. These errors can range from simple typos to major mistakes (e.g., missing information), which not only waste time but also lead to costly consequences like lost sales and damaged customer relationships. AI-based document processing solutions use advanced AI algorithms, including large language models (LLMs), to accurately extract data from documents with minimal errors, improving overall data accuracy and consistency.

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4. Cost Savings & Increased Efficiency

By automating tedious, repetitive tasks, such as data entry, extraction, validation, document analysis, and customer communication, AI-document processing solutions can save organizations time, effort, and money. AI solutions scale as your business grows, so you don't have to hire additional staff for document processing tasks. For instance, if your business is processing a large number of documents during peak season, AI can easily handle the workload without any additional costs. With AI, businesses can better utilize their resources and allow employees to focus on more strategic, value-added tasks like customer engagement and decision-making.

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How turian Streamlines Document Processing for Businesses?

turian provides a comprehensive AI automation solution that streamlines your entire document processing workflow end-to-end. Our AI assistants utilize advanced large language models (LLMs) to extract, analyze, and process documents in any format, structure, or language from a variety of sources, like email-free texts, PDFs, Word files, images, Excel, and handwritten notes.

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LLMs enable our turian to understand the context and meaning of the document it is processing, but we know that LLMs alone are not enough; that's why we've built several layers of proprietary technology to ensure your document processing tasks can be automated with speed, accuracy, and quality.

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turian can automate various document processing tasks such as document capture, extraction, classification, data validation, document routing (e.g., sending to the right person for review and approval), and integration with business systems (e.g., ERP). Our AI assistants can also handle complex tasks that require natural language understanding, like drafting human-like responses to inquiries, analyzing customer feedback, and asking for follow-up information to complete a task.

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With real-time insights and analytics, turian enables businesses to make data-driven decisions and continually improve their processes. For example, if a document (e.g., an invoice) is missing crucial data fields (e.g., a PO number), our AI assistant can flag it and send alerts to the relevant parties for further action, ensuring data accuracy and compliance. No more manual checking or data entry errors.

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Our AI solution is scalable and can grow alongside your business. turian can handle increasing volumes of tasks and expand functionality as needed. With its intuitive UI, turian allows you to monitor and track your document processing tasks, offering full control over the entire automation process.

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turian is compatible with almost all existing IT infrastructures and integrates seamlessly with major ERP/CRM systems and email clients like Outlook/Gmail.; it's a ready-to-use solution that can be deploy  in just days without disruption to your current workflows or requiring lengthy training. If you want to test how turian can streamline your document processing workflows, we offer a Proof of Concept (PoC) to show you the capabilities of our AI automation platform.

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