Specialized Software for “reading” Documents

Intelligent Document Processing is a specialized software designed to “read” documents.

Processing refers to the actions that the software (IDP) performs on document data, rather than being the software itself. Intelligent Document Processing is software that carries out a series of automated actions, or “processes,” to interpret and handle data within documents. Essentially, the “processing” part involves reading, extracting, classifying, validating, and routing document information, turning unstructured content into structured, usable data. So, “processing” describes what the software does, not what it is.

It can also pull out key data, whether from digital files, scanned images, or even handwritten forms. AT it’s core, Intelligent Document Processing combines Optical Character Recognition (OCR) and artificial intelligence (AI) to tackle this task with speed and accuracy. This goes beyond simple scanning and archiving.

Benefits of Intelligent Document Processing

Intelligent Document Processing (IDP) is a valuable tool for modern businesses that manage large volumes of documents. It helps companies by reading and organizing stacks of documents like invoices or contracts. Using advance technology to pull out important information accurately and quickly, saving people time. This helps in cutting down on mistakes, and making sure companies can handle more documents without needing extra help.

  • Faster Work: Intelligent Document Processing makes handling documents quicker by automatically reading and organizing them, so people can spend time on critical tasks.
  • Fewer Mistakes: Intelligent Document Processing reduces errors by accurately capturing data and learning to improve over time.
  • Saves Money: Companies don’t need as many people to sort and manage documents, which saves money.
  • Grows with Demand: It can manage more documents as a business grows, without needing extra workers.
  • Useful Data: Intelligent Document Processing turns documents into organized information, making it easy to find patterns or make decisions.
  • Helps with Rules: Data tracking is done in a secure way, making sure companies meet legal rules.
  • Better Service: Faster processing of things like loans or claims helps customers get answers quickly.
  • Flexible with Different Files: As it works with a wide range of files, like scanned images or PDFs, making it a flexible tool for any business.

Data Capture

To show how Intelligent Document works, let’s start with the first step: Data Capture.

intelligent document processing data capture

In data capture, Intelligent Document Processing uses a technology called Optical Character Recognition (OCR) to read documents. OCR scans each page, identifying and converting text from scanned images, PDFs, or other digital files into machine-readable data. This step works a bit like when your phone reads a photo and recognizes the letters in it.

Once OCR converts the text, the system begins recognizing important fields or pieces of information, like names, dates, or invoice numbers. These details are identified based on patterns or pre-set rules that direct Intelligent Document Processing to pick out what’s important in each document. This foundation lets Intelligent Document Processing systems extract information from a range of document types, from structured forms to less structured documents like contracts or emails.

Data Classification and Extraction

After Data Capture, the next step in Intelligent Document Processing is Data Classification and Extraction.

file transfer

Once Intelligent Document Processing has read the document, it begins classifying it. This means it identifies the type of document—like an invoice, contract, or form—so it knows what information to look for. Using AI, Intelligent Document Processing learns patterns and knows where to find specific details for each type. For example, in an invoice, it would look for fields like invoice number, amount, and due date.

Next, Data Extraction happens. Intelligent Document Processing extracts the key details it identified, like names, dates, or amounts, and pulls them into a structured format (like tables or fields in a database). This makes the information ready to use, whether for analysis, storage, or to trigger the next steps in a workflow.

Data Extraction

Together, classification and extraction ensure that each piece of information in the document is accurately identified and ready for use in the system.

Data Validation

Data Validation

After data is captured, classified, and extracted, the next step in Intelligent Document Processing is Data Validation.

Here, the system verifies that the extracted information is accurate and complete.

For instance, Intelligent Document Processing might cross-check data against a company’s internal database to confirm that an invoice number is valid or a client’s name matches existing records. Some systems even apply rules, like making sure dates are formatted correctly or that a total amount is calculated right.

Once validated, the data is ready for integration and storage within the organization’s systems, such as ERP (Enterprise Resource Planning) software or other databases, where it can be accessed, analyzed, and utilized in workflows. This step is key for ensuring clean, actionable data, completing the document’s journey from raw content to a valuable asset.

A list of all critical processes and sub-processes involved in Data Validation for Intelligent Document Processing:

Storage and Integration

Once the data has been captured, classified, extracted, and validated, the final steps in Intelligent Document Processing are Storage and Integration.

In the Storage phase, the validated data is securely stored in a document management system, database, or cloud storage. Organized and categorized, this data is now easy to retrieve and reference whenever needed.

In Integration, the structured data is linked to other systems, such as CRM, ERP, or workflow automation tools. This allows the data to be seamlessly used across various business functions—like triggering payments, generating reports, or updating customer records—making it accessible and valuable across the organization.

Steps involved in Storage

In Intelligent Document Processing, Storage is the step where organized, validated data from documents is saved in a secure, searchable format, ensuring it’s easily accessible.

Steps involved in Integration

Intelligent document processing data integration

Integration in Intelligent Document Processing is the process of connecting validated and stored data with other software or systems within an organization. This step is vital because it enables the extracted data to be used in workflows and applications across departments.

These last steps enable the data to be readily available for analysis, audits, or any other processes. This completes its transformation from raw document data into actionable information that drives business decisions and workflows.

Evolution of Advanced Technology

Tech behind Intelligent Automation

Intelligent Document Processing relies on several advanced technologies, each evolving from earlier data-handling and automation tools.

Create the opportunity for Personas like Citizen Developer in your Company.

Intelligent Document Processing for Mission Critical work

Intelligent Document Processing (IDP) can foster several innovative roles and capabilities beyond just processing documents. Like “Citizen developer”—a persona of someone who is empowered by technology to create solutions without deep coding expertise.

  • Data Explorer: This persona uses the software to uncover valuable insights hidden in documents, exploring trends, patterns, or correlations without needing advanced analytical skills.
  • Compliance Guardian: Focused on meeting industry regulations, this persona relies on the software to ensure document compliance and security, catching errors or risks automatically.
  • Process Optimizer: Driven by efficiency, the Process Optimizer uses the tool to automate repetitive tasks in document-heavy workflows, creating smoother processes across teams.
  • Knowledge Curator: This persona leverages the entire process to categorize and organize vast amounts of unstructured information, making knowledge easily accessible and searchable for others.
  • Insight Catalyst: An insight-driven persona, the Insight Catalyst uses Intelligent Document Processing to pull actionable insights from data-rich documents, supporting faster, data-informed decision-making.

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