What is document processing?
Table of contents
Document processing captures, classifies, extracts, and validates information from paper documents and born-digital files, such as PDFs and emails. This enables the information to flow into business systems. Paper inputs first need digitization. Organizations handle documents manually or — increasingly — automatically, where software captures documents, reads their data, and routes the results without human data entry.
Intelligent document processing (IDP) uses artificial intelligence (AI) within document processing. The broader automation category also includes rule-based systems that don’t use AI. While some organizations still process documents manually, automation is sweeping the space because organizations are working toward a complete digital transformation.
Automating this process helps manage documents throughout their lifecycle and can improve efficiency, productivity, and compliance. Rule-based document processing can recognize text, extract fields, and validate them against configured patterns. Now, with AI-driven solutions, IDP systems comprehend context, apply machine learning to adapt, and handle diverse document types.
This article will discuss software’s role in document processing, real-world use cases, software automation, benefits and challenges, and future trends.
What is AI document processing?
AI document processing is the use of artificial intelligence to read, classify, extract, and validate data from documents automatically. That includes optical character recognition (OCR), machine learning, natural language processing (NLP), computer vision, and increasingly large language models (LLMs). Unlike rule-based systems that depend on fixed templates, an AI-driven system interprets context. As a result, it can handle unstructured files such as contracts, emails, and scanned forms and adapt to document types it hasn’t seen before.
How AI changes traditional document processing
Fixed-layout extraction can require new rules when a form changes. AI can reduce that dependence, but new document types still need testing:
- Context over templates — The system identifies fields such as an invoice number or contract date by meaning, not fixed position.
- Unstructured documents — Machine learning and NLP extract data from freeform text, not just structured forms.
- Continuous improvement — A human-in-the-loop step flags uncertain results for review. Teams can use corrections to refine prompts, rules, and tests; model retraining requires a separate supported feedback or training process.
The result is a repeatable pipeline:
Capture (OCR) → classify → extract → validate → route
Manual effort depends on document quality, layout variation, and validation requirements. Rule-based and AI methods can both support automated processing; compare them on representative inputs.
| Approach | What it does | Unstructured documents | Adapts to new layouts |
|---|---|---|---|
| Classic (rule-based, templates) | Extracts fields using positions, patterns, or rules | Can extract predictable patterns from text | Rules may need updates when layouts change |
| OCR | Converts document images to machine-readable text | Text only, no meaning | Not applicable |
| AI document processing (IDP) | Classifies, extracts, and validates data by context | Yes | Can handle varied layouts; validate on new document types |
AI document processing is closely related to intelligent document processing (IDP), and people often use the terms interchangeably. For a deeper look at the IDP technology stack, see the dedicated guide.
Nutrient provides AI document processing both as a self-hosted AI Document Processing SDK and a cloud Data Extraction API for building it into a pipeline.
The role of software in document processing
Document processing software captures data, applies validation rules, and routes results for review or downstream use. AI can help interpret varied layouts, while deterministic rules remain useful for predictable documents.
What are the advantages of document processing software?
IDP software includes both AI and machine learning. Using software for document processing has many advantages, outlined below.
Improved security
Document processing pipelines need access controls, encryption, and secure handling of temporary files. Storage security, backups, and retention belong to the document management or storage systems connected to the pipeline.
Information retrieval
Searching through and finding information with just a few clicks is easier in the digital realm. If data and information are digitized as opposed to being in a manual format, information retrieval is much faster.
Increased productivity
Extracting and validating fields can reduce manual entry. A connected document management system can also help staff find the original records.
Version control
Version control is a document management capability, not an inherent feature of extraction software. Connect processing results to the correct source version and use a repository that retains the history your workflow requires.
Better compliance
Many industries have strict document and record-keeping compliance requirements. Common examples include the Health Insurance Portability and Accountability Act (HIPAA) for healthcare records and the General Data Protection Regulation (GDPR) for personal data. Digital forms enforce consistent processes to match the policies and procedures within your organization or department. As compliance regulations continue to increase in both number and scope, the automation of compliance workflows has become critical.
Reduce errors
IDP reduces the number of humans needing to involve themselves in manual tasks. For example, when manually gathering information from a document, you can accidentally key in the wrong data, so reducing manual entry can improve efficiency. Extracted values still need validation and exception handling.
Document processing tools
The following sections outline our document processing tools, including document conversion services for enterprise document workflows.
Nutrient Workflow
Create unlimited innovative, complex business forms the way you want, with complete formatting and advanced layout tools in Nutrient Workflow. The interface is designed to manage processes visually.
AI Document Processing
Our AI PDF data extraction solution supports document classification and extraction through configurable components, templates, and validators. Developers integrate the SDK into their application and test it against representative documents to measure accuracy and define review rules.
.NET SDK
Our .NET SDK offers solutions to manage electronic documents (locally or online):
- Extract text and magnetic ink character recognition (MICR) characters from scanned images
- Automatically export PDF table data to Excel
- Automatic document recognition and form processing
- View and convert documents in 100+ formats
- Image processing algorithms
- Intelligent document processing
PDF SharePoint solutions
Our low-code platform offers a complete suite of PDF tools for SharePoint with an online app and on-premises deployment. It features conversion to PDF, watermarking, hyper-compression, intelligent data extraction, merging, splitting, and much more. Document Editor for SharePoint enables users to annotate, sign, redact, and edit documents without leaving SharePoint. Furthermore, it supports form creation and form filling capabilities.
OCR SharePoint solutions
Document Searchability is an automated OCR SharePoint solution that audits an entire SharePoint library and reports how many files are searchable, partially searchable, or non-searchable. As a next step, it performs OCR on partially searchable and non-searchable files, making all the documents in a SharePoint library findable and accessible. To further enhance findability, it automatically adds metadata tags to documents based on their content.
What are common use cases for document processing?
The following sections outline a few common use cases for document processing.
Human resources: Automating employee onboarding
A company’s onboarding experience varies widely, especially as more workers are hired and onboarded remotely.
Workflows for human resources (HR) make forms and procedures easier to distribute, process, and review. That can make a world of difference in your costs when onboarding and training new employees.
By digitizing this workflow, you can streamline the onboarding process and ensure it’s done the same way each time. This ensures consistency, accuracy, and accountability when onboarding different employees.
Finance: Streamlining invoice processing
Implementing document processing for your finance department removes barriers to running a high-performing team. You can upgrade budget approvals, accounts payable, purchase requests, expense requests, invoice reconciliation, and other financial processes to automated workflows that ensure consistency and compliance.
Invoice processing is a specific example of a process that would benefit from digital transformation. Software can reduce data entry errors and process delays when extraction, validation, and review rules are configured appropriately. Document processing software can automatically extract data from invoices, validate it against purchase orders, and integrate with accounting software for payment processing.
Healthcare: Enhancing patient record management
For healthcare companies, compliance, accuracy, and accountability are critical. Document processing enables better internal controls and greatly improved efficiency.
Document processing can manage patient records — including medical histories, test results, and insurance information — in a secure location. It can help healthcare providers digitize paper records, organize digital documents, and ensure compliance with privacy regulations.
Automating document processing with software
Automated solutions like Nutrient Workflow enable document processing. The software enables you to replicate your documents into smart forms and then add them to a workflow process to streamline the process entirely.
By automating processes, you capture information efficiently and ensure accuracy. This is a massive step in the right direction compared to manually handling your documents. Automating workflows and documents, especially processes primarily handled manually by employees, can significantly improve efficiency, productivity, accuracy, accountability, and job satisfaction.
Using enterprise workflow software and automation, your business will save time and reduce errors.
Benefits of automated document processing
Enterprise automation doesn’t have to be complicated. Automated workflows can be designed visually to simulate or improve existing processes. Workflow automation provides several benefits over manual processes:
- Policy compliance adherence
- Reduced approval cycles
- Reduced manual handling
- Improved communication
- Improved visibility
- Improved employee satisfaction
- Continual process improvement
- Better workload management
- Reduced errors
Another benefit is that operational efficiency is possible when automating this procedure. Operational efficiency or operational effectiveness, in a business context, is the degree to which an organization can deliver its goods and services with minimal waste.
Frequently asked questions
Document processing captures, classifies, extracts, and validates information from paper and born-digital documents so it can flow into business systems. Paper documents first need to be digitized. Organizations handle documents manually or automatically with software.
AI document processing uses artificial intelligence, including OCR, machine learning, NLP, and computer vision, to automatically read, classify, extract, and validate data from documents. That includes unstructured files that may be difficult to process with fixed rules.
A document is captured (often via OCR) and classified by type, and its data is extracted and validated. Low-confidence results are flagged for human review, and the output is routed into downstream business systems.
OCR only converts an image of text into machine-readable characters. AI document processing adds context: It understands what the text means, identifies specific fields, and adapts to layouts it hasn’t seen before.
The terms are largely interchangeable. IDP is the broader umbrella for the technology stack; see the intelligent document processing guide for details.
Common use cases include invoice and accounts payable automation in finance and patient record and claims handling in healthcare. Others include contract review in legal and employee onboarding in HR.
Conclusion
Document processing combines capture, extraction, validation, and routing. Choose rule-based or AI methods according to your documents, and measure accuracy and review effort before rollout. Storage, version control, and retention require the appropriate connected systems.
Nutrient Workflow can route extracted data and documents through reviews and approvals. Contact us to discuss the integration and controls your process needs.
Related reading
- What is intelligent document processing? — Complete guide to IDP technology, from OCR to AI extraction
- Add AI Assistant to Nutrient PDF viewer — Build an AI-powered PDF editor with summarization and redaction
Learn more about our Document AI capabilities.
