What is Intelligent Document Processing (IDP)?

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Efficient and accurate processing of documents is the cornerstone of any successful business. Yet, when handled manually, this critical process can become a breeding ground for inefficiency, errors, and delays. From invoices and purchase orders to customer requests and contracts, businesses receive and generate hundreds (if not thousands) of documents every single day. This mountain of data, even if you have a dedicated team to handle it, can overwhelm your business and hinder its growth.

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To overcome the document processing bottlenecks, companies are digitizing their operations by adopting intelligent document processing solutions. IDP technology is changing the way businesses handle documents. It can extract, classify, and validate data from varied documents (e.g., PDFs, images). But what is really behind the “intelligent” in IDP?

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In this blog post, we'll walk you through every aspect of intelligent document processing, from its definition and how it works to its benefits and where it falls short. By the end, you'll have a clear picture of what IDP is and isn't and why businesses need to look beyond it for true intelligent automation.

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Understanding Intelligent Document Processing (IDP)

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Image credit: Freepik

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What Is IDP?

Intelligent document processing (often referred to as IDP) is a technology that automates the extraction, classification, and processing of data from different types of documents. Unlike traditional document processing methods, which rely on manual entry, and human intervention, IDP depends on a spectrum of technologies to automatically identify, extract, and interpret relevant data from structured and unstructured documents.

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Key Technologies in IDP

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• OCR (Optical Character Recognition): Optical character recognition (OCR) serves as the backbone of IDP. It converts different forms of documents, like PDFs, and scanned paper documents, into machine-readable text. However, it does not understand the content or meaning of the data. It simply recognizes the characters and arranges them in a machine-readable format.
• Machine Learning: Machine learning (ML) is like the brain of IDP. It teaches the system to recognize, analyze, and interpret patterns in data. It requires structured data, a lot of training, and fine-tuning to perform its tasks accurately; otherwise, it may not deliver the expected results.
• Robotic Process Automation (RPA): If machine learning algorithms are like the brain of IDP, then Robotic process automation (RPA) is like the body of IDP that gets things done. RPA is a type of automation technology that uses software bots to mimic human actions with digital systems. It is primarily used to perform repetitive tasks, like data entry and form filling. RPA is good at handling structured, rule-based tasks but cannot handle unstructured data or understand the context of the data.

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How Does Intelligent Document Processing Work?

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Image credit: Freepik

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The working mechanism of intelligent document processing software varies from solution to solution; however, most of them follow a similar framework. The typical IDP workflow consists of three main phases: classification, extraction, and processing.

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1. Document Classification

The initial step in IDP involves the data capture and classification of documents. IDP systems use OCR technology and ML algorithms to identify and categorize different types of documents, such as invoices, receipts, contracts, or purchase orders. These documents can be either digital or paper-based. This classification is very crucial as it defines the following processing steps for each type of document.

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2. Data Extraction

Once the documents are classified, the IDP system extracts relevant data from them. It often relies on a combination of OCR and ML algorithms to identify specific information like name, date, amount, or address. This data is then validated to ensure its accuracy and consistency. A good IDP-system may cross-check the extracted data with existing databases or use predefined rules to identify any errors.

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3. Data Processing

After the data is extracted and validated, IDP systems process it in alignment with its intended purpose. For example, if the document is an invoice, the system will route the data for payment processing. If it is a purchase order, the system might send it to the procurement team for further action.

The final structured data is then integrated into other business systems, such as ERP or CRM, to ensure smooth data flow and automate specific actions driven by the processed information. Robotic process automation (RPA) often plays a crucial role in this phase, where it mechanically executes rigid workflows. For instance, it can transfer data from a specific field in a document (e.g., invoice number) to a corresponding field in an ERP system.

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Benefits of Intelligent Document Processing (IDP)

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Intelligent document processing (IDP) has been an efficiency booster for many businesses, bringing several benefits to the table. Here are some of the main benefits of IDP solutions:

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• Increased Efficiency: IDP solutions automate the extraction, classification, and processing of data, which drastically reduces the manual labor required to handle documents. It frees up employees' time to focus on more critical and strategic tasks, like decision-making and customer service.
• Reduced Error Rates: Unlike manual document processing, IDP systems can identify, extract, and validate data with high accuracy levels. It minimizes the chances of human error and ensures data consistency.
• Cost-efficiency: Using IDP solutions can result in significant cost savings over time. It reduces the need for manual labor, which can be costly, and eliminates the need for paper-based processes, which often involve printing, storing, and mailing costs.

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Due to its numerous benefits, many businesses often assume intelligent document processing as the pinnacle of intelligent automation. However, the reality is that IDP has its limitations and is not a clever genius who can handle everything. Understanding what IDP cannot do is just as crucial as understanding what it can do because it helps businesses make informed decisions about their automation needs.

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Where IDP Falls Short: The Limits of 'Intelligence'

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Although intelligent document processing (IDP) solutions are efficient, they are not perfect. In fact, they are not even true 'intelligent' systems. Here are some of the major limitations of IDP that businesses should be aware of to avoid unrealistic expectations:

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1. Lack of Contextual Understanding

IDP can handle repetitive, labor-intensive tasks like a pro—data validation, extraction, and classification faster than your best employees. But when it comes to understanding the why behind the what, IDP is still very much in the dark. For example, it can extract specific fields from a sales order, but it cannot understand the entire document in context and interpret its meaning.

Imagine if a sales order lists a customer's address as "123 Main Street" when it should be "321 Main Street." What would IDP do? It simply extracts the information without identifying any potential error. Why? Because IDP isn't equipped to understand the meaning behind the words, it simply sees them as data points to be processed, not comprehended.

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2. Inability to Adapt to Changes

Despite its name, 'intelligent,' IDP is not a self-learning system. For automating one particular type of document, IDP is excellent, but that's it. It cannot adapt to changes in document formats or fields, it cannot read and understand different types of documents, and what's even more limiting, it will continue to make mistakes. For example, if you train IDP to extract certain fields from a document (e.g., address, price, date), it can't understand why that particular field is important or what to do if the field is missing or incorrect. It will simply follow the same rules you've set and extract whatever data falls under those categories, regardless of whether it's relevant or not. This means:

• You'll have to constantly train IDP for new document types or changes in existing ones.
• You'll have to manually review and correct any errors made by IDP, which defeats the purpose of automation.
• You'll have to rely on human intervention to fill the gaps left by IDP.

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3. Language-related Barriers

IDP systems have limitations when handling documents in other languages besides the ones they are trained on. This can be a significant challenge for businesses with global operations or those that handle documents in multiple languages. Aging IDP systems that lack multilingual support can result in inaccurate data extraction and processing, which not only hinders efficiency but can also lead to compliance issues.

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Why IDP Is Outdated: The Era of AI Agents

The scope of what IDP can do is often overestimated. It's undoubtedly a valuable tool for automating document processing, but it is not the true intelligent automation panacea many businesses make it out to be. They fall short because they can't automatically adapt to changes in document formats, fields, and languages. They also cannot learn from their mistakes or interpret the context of a document, which makes them outdated in today's rapidly changing technological landscape.

However, there is a solution that goes beyond IDP and offers true intelligent automation - AI Agents. These advanced artificial intelligence (AI) agents leverage large language models (LLMs) to understand and interpret documents in real-time, regardless of format, field, or language.

They can learn from their mistakes and constantly adapt to changes, ensuring accurate processing and understanding of documents. They can understand the why behind the what, providing a more comprehensive and contextual understanding of documents- something IDP is incapable of doing. In our next article, we will give you a full overview of "Why intelligent document processing is outdated" and why businesses need more than just aging IDP solutions to achieve true intelligent automation.

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Streamline Your Document Processing Workflow with turian

At turian, we understand the challenges businesses face when it comes to document processing. That's why we've developed our AI Agents (also called AI Assistants) with one goal in mind: to streamline your document processing workflow and make it more efficient, accurate, and intelligent. turian uses the world's most advanced LLMs to extract data from various documents (e.g., PDFs, Word, Excel, images), interpret its context, and perform relevant actions based on your business requirements. Our AI agents can handle documents in multiple languages, regardless of their format or structure.

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With natural language processing (NLP) at its core, turian's AI agents can understand the meaning behind each document, not just the words on the page. From drafting personalized email responses to automatically managing your sales orders, our AI agents offer a suite of features to help optimize your workflow. It's a long-term, scalable solution that grows with your business.

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turian requires no specific hardware or software, and you don't need to learn another tool. Our AI agents seamlessly integrate into your existing ERP/CRM systems and email clients (e.g., Outlook, Gmail) without disrupting your current workflow. It's pre-trained, customizable, and ready to use within less than two weeks. It supercharges your operational efficiency and eliminates manual data entry, saving you time and resources while enhancing data accuracy.

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We are so confident in our solution that we offer a free Proof of Concept (PoC) so you can see the real-life impact of turian on your document processing workflow. If you've got any concerns or questions, you can directly ask us, and we would be happy to explain how turian can fit into your business.

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