Organizations process vast amounts of documents daily, many of which contain critical business information buried in unstructured or semi-structured formats. Manual document handling is slow, error-prone, and resource-intensive, creating bottlenecks in operations. UiPath Document Understanding eliminates these bottlenecks by automating these workflows for greater accuracy and efficiency. Whether streamlining accounts payable, accelerating customer onboarding, or enhancing compliance, Document Understanding helps organizations unlock the full potential of automation.
What is UiPath Document Understanding?
UiPath Document Understanding is a powerful AI-driven tool within the UiPath platform, designed to automatically extract and process data from documents that don’t follow a strict structure, such as invoices, contracts, receipts, and forms. Instead of manual data entry, this technology uses AI, machine learning, Optical Character Recognition (OCR), and natural language processing to identify key information, classify document types, and extract relevant data with high accuracy. It enables businesses to automate document-heavy workflows, reduce manual effort, minimize errors, and improve efficiency.
Document Understanding automates manual document handling, saving time and reducing operational costs by minimizing the need for human intervention in repetitive tasks. It excels in processing diverse document types, including unstructured and semi-structured data, and scales to handle high volumes efficiently. By leveraging AI and machine learning, it improves accuracy, reduces errors, and continuously enhances its performance over time. The tool also ensures compliance through robust data validation and audit trails, integrates seamlessly with end-to-end workflows, and supports human-in-the-loop validation for exceptional cases. These capabilities enable real-time processing, accelerate decision-making, and drive digital transformation by modernizing document workflows with advanced AI technologies.
How to Use Document Understanding
Implementing UiPath Document Understanding involves a series of well-defined steps to ensure optimal results.
Load Taxonomy – Define the Data Structure
- Why it matters: Taxonomy acts as a blueprint for data extraction, ensuring clarity on what information needs to be captured.
- How to execute: Use the Load Taxonomy feature to set up a hierarchical structure for document types, fields, and categories. For example, specify fields like “Invoice Number,” “Due Date,” or “Total Amount” for invoices.
Digitization (OCR) – Convert Documents to Machine-Readable Text
- Why it matters: OCR is the foundation for converting scanned documents or images into text that can be processed digitally.
- How to execute: Use the Digitize Document activity to initiate the OCR process. Configure the OCR engine, such as Tesseract or UiPath Document OCR, based on the document’s language and complexity. Adjust settings like accuracy thresholds to ensure optimal results.
Classification – Categorize Document Types
Classify documents when dealing with multiple types (e.g., invoices, receipts).
- Why it matters: Classification ensures that each document is routed to the appropriate extraction process based on its type.
- How to execute: Utilize the Classify Document activity to categorize documents. Leverage pre-trained classifiers for common document types or build custom classifiers tailored to unique business needs. For instance, train a classifier to distinguish between purchase orders and contracts.
Data Extraction – Retrieve Structured Information
Extract structured data using the Extract Data activity. Combine various extraction methods:
Why it matters: Extracts relevant data points for automated processing.
How to execute: Combine multiple extraction techniques for optimal results:
- Regex-based extractors: Ideal for identifying specific patterns, such as dates, invoice numbers, or monetary amounts. Example: Use regex to extract all dollar amounts from a financial report.
- Machine Learning Extractor: Adaptable to varied and complex document layouts. Train the model to identify fields like supplier names or tax IDs.
- Form Extractor: Effective for structured documents like applications or questionnaires. Example: Extract names, addresses, and signatures from loan applications.
- Intelligent Keyword Classifier: Extract relevant data by identifying keywords or phrases. Example: Detect the phrase “Payment Due” to locate deadlines within invoices.
Validation (Optional) – Ensure Accuracy with Human Review
- Why it matters: Validation ensures that extracted data is accurate, especially for critical or ambiguous fields.
- How to execute: Use the Present Validation Station activity to allow users to review and correct data flagged as uncertain. Set confidence thresholds for automated validations, enabling human intervention only when needed. Please see the image below of validation station at work:
Export Data – Send Extracted Information to Target Systems
Send the processed data to downstream systems or save it in desired formats.
- Why it matters: Extracted data needs to be actionable, seamlessly integrating with other systems or workflows.
- How to execute: Define export destinations such as Excel files, relational databases, ERP systems (e.g., SAP), or APIs. Example: Automatically transfer validated invoice data to an accounts payable system for payment processing.
Examples of Use Cases for Document Understanding
Document Understanding has a wide range of practical applications across industries:
- Invoice and Receipt Processing: Automatically extract details like invoice numbers, dates, and amounts to streamline accounts payable workflows. This reduces manual errors and accelerates processing times.
- Legal Document Review: Automate the analysis of contracts, non-disclosure agreements, and compliance documents by extracting and validating critical clauses and dates, saving legal teams hours of manual effort.
- Customer Onboarding: Simplify onboarding processes by extracting key details from ID verification documents such as passports, driver’s licenses, or utility bills, ensuring compliance with Know Your Customer (KYC) requirements.
- Claims Processing: Automate the extraction of policy numbers, claim amounts, and customer details from insurance claims forms to expedite approvals and reduce administrative overhead.
- Healthcare Document Analysis: Extract patient information, diagnostic codes, and treatment details from medical forms or lab reports to improve operational efficiency and patient care.
- Shipping and Logistics: Process shipping manifests, bills of lading, and customs declarations to ensure accurate and timely supply chain operations.
- HR Document Management: Automate the processing of resumes, employee onboarding documents, and performance review forms, improving recruitment and employee management workflows.
- Financial Data Processing: Extract data from bank statements, financial reports, and tax forms for use in financial analysis and compliance reporting.
Conclusion
UiPath Document Understanding is a transformative tool for organizations looking to optimize document processing workflows. By automating time-consuming tasks, handling diverse document types, and integrating advanced AI capabilities, it delivers unparalleled efficiency, accuracy, and scalability. Whether your organization needs to process invoices, onboard customers, or manage compliance documents, Document Understanding can help you achieve your automation goals and accelerate digital transformation.
Ready to unlock the power of automation with Document Understanding? Reach out to us today to learn more.