Get Clean Data Tables With Document AI Software
Learn how Document ArtificiaI Intelligence (AI) software enables operations teams to process documents 10x faster.
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Businesses Do Extraordinary Things With Docsumo
$100 Million
Saved in processing costs
3.4 Million
Work hours saved
20 Million
Documents processed
95%+
Straight-through processing achieved
The Best Document AI Software of 2025 Ranked
Docsumo
Docsumo is a Document AI software tailored for operations and technology teams looking to get clean data tables from their unstructured documents.
Key features -
- AI-powered data extraction for complex documents (invoices, bank statements, contracts).
- Excel-like data tables to view & analyze captured data.
- Multiple input methods: emails, APIs, cloud drives, local uploads.
- Customizable validation rules for accurate data and seamless integration.
- Pre-trained AI models with options for custom training on specific datasets.
- Intuitive, user-friendly interface for reduced manual efforts and errors.
- Streamlines document workflows, improves accuracy and cuts processing time.
Things to consider -
According to user reviews, no significant limitations have been reported regarding Docsumo's performance.
Pricing -
Dosumo’s pricing model is divided into Free, Growth, and Enterprise plans. The Free plan offers a free trial, which includes 100 pages per month. The price per page for the Growth plan starts at $0.3.
Amazon Textract
Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, layout elements, and data from scanned documents. Unlike basic OCR, it can identify, interpret, and retrieve specific data from documents.
Key features -
- Automatically detects and extracts printed and handwritten text from documents.
- Identifies and extracts key-value pairs, preserving context-like fields and their values.
- Extracts table data while maintaining the structure of rows and columns.
- Recognizes layout elements like paragraphs, titles, and headers for better document understanding.
- Allows query-based extraction, retrieving specific data using natural language queries.
Things to consider -
- Accuracy for handwritten documents can be low, requiring manual intervention.
- Service can be expensive, especially for large-scale document processing.
- Limited language support is available.
Pricing -
Amazon Textract offers a pay-as-you-go pricing model, with rates varying based on the specific API used and the number of pages processed. The basic plan for 1,000 pages begins from $1.50 per page.
Google Document AI
Google Document AI extracts structured data from documents, allowing for efficient analysis, search, and storage. The Document AI suite includes pre-trained models for data extraction, the Document AI Workbench for creating custom models or enhancing existing ones, and the Document AI Warehouse for searching and storing documents.
Key features -
- Transforms scanned images and PDFs into searchable, editable text with OCR.
- Extracts key-value pairs and table data from structured forms.
- Categorizes documents using machine learning for efficient organization.
Things to consider -
- Some documentation is outdated or ambiguous, with limited code examples for various use cases.
- Instructions for training models are unclear, especially for non-technical users.
- Multilingual support is minimal.
- Data extraction from PDFs can sometimes be inaccurate, requiring manual retraining.
Pricing -
Google Doc AI offers a pay-as-you-go pricing model. Basic OCR starts at $1.50 per 1,000 pages, with additional costs for more advanced features that come with the different processors.
ABBYY Vantage
ABBYY Vantage is a Document AI tool that is praised for its efficiency in digitizing, editing, and managing PDFs, Word documents, and scanned files. It offers a graphical interface that allows users to scan documents, import them, and apply OCR to them.
Key features -
- Utilizes AI-powered OCR for highly accurate text recognition.
- Supports a wide range of document formats.
- Comprehensive tools for editing and managing PDFs.
- Designed to meet the needs of both businesses and individual users.
Things to consider -
- Some advanced features may have a steeper learning curve for users.
- The pricing can be higher compared to more basic OCR solutions.
Pricing -
ABBYY offers two different plans for the Vantage solution, catering to businesses and individuals. The pricing for their Individual plan begins at $34.50/year for Mac devices and $49.50/year for Windows users.
UiPath Document Understanding
UiPath Document Understanding is a Document AI solution that integrates seamlessly with UiPath's broader RPA platform, offering advanced capabilities for automating document-centric workflows.
Key features -
- Combines OCR, computer vision, and machine learning for intelligent document processing.
- Supports a wide range of document types, including invoices, receipts, and contracts.
- Offers pre-built models and the ability to train custom models for specific document types.
- Integrates with UiPath's RPA tools for end-to-end process automation.
Things to consider -
- Requires familiarity with UiPath's RPA ecosystem for optimal use.
- Has a steeper learning curve for organizations new to RPA.
Pricing -
UiPath offers a tiered pricing model with options for businesses of all sizes. The Document Understanding software starts at $420/month for a Pro license.
Automation Anywhere Document Automation
Automation Anywhere Document Automation leverages AI and machine learning to extract, process, and analyze data from various document formats, integrating with Automation Anywhere's intelligent automation platform.
Key features -
- Uses AI-powered OCR and natural language processing for accurate data extraction.
- Offers pre-built bot templates for common document processing tasks.
- Provides a no-code interface for creating custom document processing workflows.
- Seamlessly integrates with other Automation Anywhere products for comprehensive automation.
Things to consider -
- Primarily designed for use within the Automation Anywhere ecosystem.
- Requires additional configuration for highly specialized document types.
Pricing -
Automation Anywhere offers their Cloud Starter Pack at $750/month and custom pricing for more advanced features and enterprise solutions.
How Does Document AI Software Work in Different Scenarios?
For Images
- Advanced OCR techniques: Utilizes convolutional neural networks (CNNs) for image pre-processing and feature extraction.
- Image enhancement: Applies adaptive thresholding, deskewing, and noise reduction algorithms to improve image quality.
- Character segmentation: Uses connected component analysis and contour detection for isolating individual characters.
- Deep learning models: Employs architectures like LSTM (Long Short-Term Memory) networks for sequence-to-sequence learning in text recognition.
- Post-processing: Implements language models and lexicon-based correction for improving OCR accuracy.
For Structured Documents
- Layout matching: Uses computer vision algorithms to identify document layout and field positions.
- Zonal OCR: Applies targeted OCR to predefined regions for efficient data extraction.
- Rule-based parsing: Implements regex patterns and business rules for data validation and extraction.
- Machine learning classifiers: Utilizes SVM (Support Vector Machines) or Random Forests for field classification.
For Unstructured Documents
- Natural Language Processing (NLP): Applies techniques like tokenization, part-of-speech tagging, and named entity recognition.
- Semantic analysis: Uses word embeddings (e.g., Word2Vec, BERT) for understanding context and relationships between words.
- Information extraction: Implements conditional random fields (CRFs) or bidirectional LSTMs for entity extraction.
- Topic modeling: Utilizes Latent Dirichlet Allocation (LDA) or more advanced transformer-based models for content categorization.
For Handwritten Documents
- Specialized HTR models: Employs recurrent neural networks (RNNs) with attention mechanisms for sequence-to-sequence learning.
- Data augmentation: Generates synthetic handwriting samples to improve model robustness.
- Transfer learning: Adapts pre-trained models on large handwriting datasets to specific use cases.
- Online and offline recognition: Supports both real-time (stroke-based) and image-based handwriting recognition.
For Tables
- Table detection: Uses deep learning models like Mask R-CNN for identifying table structures within documents.
- Cell segmentation: Applies image processing techniques like Hough transform for detecting table lines and cell boundaries.
- Logical structure recognition: Implements graph-based algorithms to understand relationships between table cells.
- Data extraction and normalization: Uses rule-based systems or machine learning models to interpret and standardize cell contents.
For Documents Over 20 Pages Long
- Document segmentation: Applies hierarchical clustering algorithms to break down long documents into logical sections.
- Distributed processing: Utilizes parallel computing techniques for efficient processing of large documents.
- Memory-efficient models: Implements attention mechanisms and transformer architectures that can handle long-range dependencies.
- Incremental processing: Uses streaming algorithms to process documents in chunks, reducing memory requirements.
- Automatic summarization: Employs extractive and abstractive summarization techniques, utilizing models like BART or T5 for generating concise summaries.
Five Must-Have Document AI Software Features
Advanced OCR and Text Extraction
- Document AI leverages sophisticated Optical Character Recognition (OCR) algorithms, often employing convolutional neural networks (CNNs) for feature extraction and recurrent neural networks (RNNs) for sequence recognition.
- These systems can handle complex layouts, multiple languages, and various font styles, achieving high accuracy in text extraction from diverse document types, including scanned images, PDFs, and handwritten notes.
Intelligent Data Structuring and Semantic Analysis
- Post-extraction, Document AI employs advanced parsing techniques to structure and categorize data. This process utilizes machine learning models such as conditional random fields (CRFs) or transformer-based architectures to identify key-value pairs, tables, and hierarchical relationships within documents.
- The system can be trained on domain-specific ontologies to enhance semantic understanding and data categorization accuracy.
Deep Learning-Based Natural Language Processing
- Modern Document AI systems integrate state-of-the-art NLP models, often based on transformer architectures like BERT or GPT. These models enable contextual understanding, entity recognition, and relationship extraction.
- They can perform tasks such as coreference resolution, sentiment analysis, and intent recognition, providing a comprehensive interpretation of document content beyond simple keyword extraction.
Automated Workflow Integration
- Document AI platforms offer robust APIs and SDKs for seamless integration with existing enterprise systems. These APIs support event-driven architectures, allowing for real-time document processing and automated workflow triggers.
- Advanced systems may incorporate business process modeling notation (BPMN) for complex workflow definitions and support distributed processing for high-volume document handling.
Adaptive Machine Learning and Continuous Model Refinement
- Document AI systems employ online learning algorithms and transfer learning techniques to continuously improve performance. This includes active learning approaches where the system identifies low-confidence predictions for human review, incrementally updating the model.
- Some platforms offer A/B testing capabilities for model versions and support federated learning for privacy-preserving model updates across distributed datasets.
Industry-specific Use Cases of Docsumo’s Document AI Software
Financial Services
- Debt settlement - Docsumo automates the extraction of critical data from financial statements, bank statements, and other relevant documents involved in debt settlement processes. With a high accuracy rate of 99%, it can quickly pull essential information such as outstanding balances, payment histories, and creditor details.
- Revenue reconciliation - Financial operations teams utilize Docsumo’s Document AI software to extract and validate revenue-related data from various sources, such as invoices, bank statements, and operating statements. The ability to handle complex tables and nested data structures ensures that all revenue entries are accurately captured and matched against the correct bank deposits or invoices.
- Income verification - Docsumo can accurately extract income-related data from pay stubs, tax returns, and bank statements. Its ability to validate extracted data against predefined criteria ensures that the information is accurate and reliable. This ensures quick and accurate income verification for loan approvals or credit assessments, reducing the time taken to process applications.
- Accounts payable - Docsumo Document AI helps automate data extraction from invoices and payment documents, allowing organizations to capture key details such as vendor names, amounts due, and payment terms without manual intervention. Its smart table extraction capabilities enable it to handle complex invoice formats seamlessly. Furthermore, integration with financial software like QuickBooks ensures smooth data flow into accounting systems.
- Accounts receivable - Docsumo can efficiently extract customer invoices and payment receipts data. It allows businesses to improve their collection efforts, reduce sales outstanding (DSO) days, track outstanding payments, and manage cash flow effectively.
Docsumo’s Document AI software allows National Debt Relief, one of America’s largest debt settlement firms, to save over 2.5k hours per year with 95%+ extraction accuracy.
Software
- Risk management - Docsumo enables organizations to quickly identify potential risks and liabilities by automating data extraction from risk assessment reports, compliance documents, and insurance claims.
- Utility bill management: Docsumo efficiently extracts relevant document data from utility bills, such as usage patterns and billing amounts. This automation helps software companies better manage operational costs by providing insights into utility expenses without manual data entry.
- Bookkeeping - Docsumo Document AI automates the processing of financial statements, receipts, and transaction records, simplifying bookkeeping tasks. This reduces the time spent on manual entries and enhances accuracy in financial reporting.
- Invoice processing - Docsumo automates the document processing of key invoice details (e.g., vendor information, amounts due) from diverse formats.
Docsumo partnered with Vertikal, a risk management platform, to help them save $20k in annual outsourcing costs with 40% lower document processing time.
Real Estate
- Property/asset management - Docsumo streamlines property management by extracting data from lease agreements and maintenance records, leading to improved tenant onboarding and experience.
- Rent roll management - The Document AI software automates the extraction of rent roll data to accurately track rental income and tenant details.
- CRE underwriting - Automating the extraction of borrower information from mortgage applications and financial statements aids in quicker underwriting decisions. This improves accuracy in assessing borrower creditworthiness and proactively proactively identifying potential cash flow issues.
- Utility bill management - Docsumo’s Document AI software pulls utility bill data, helping property managers monitor utility costs effectively and identify areas for savings.
- Insurance compliance - The platform efficiently extracts critical compliance-related information from certificates of insurance, ensuring that real estate firms adhere to regulatory requirements while minimizing non-compliance risks.
Docsumo enables Westland, a property management company, to save over 2,000 work hours monthly and drive 98% accuracy in utility bill data extraction by leveraging complex deep learning and LLM to identify patterns.
Logistics
- Shipment tracking - By automating the extraction of shipment details from bills of lading and tracking documents with advanced shipment notifications, Docsumo helps the logistics team fast-track shipment processing. This leads to improved tracking accuracy and quicker response times.
- Accounts payable - Seamless data extraction of dispatch tickets and trucking receipts allows logistics companies to streamline their accounts payable processes and ensure timely payments to suppliers and truck drivers.
- Invoice processing - Docsumo efficiently helps operations teams extract data from invoices related to shipping costs and logistics services to improve cash flow management.
NS Trucking, an American aggregate hauling company, leverages Docsumo’s Document AI solution daily to save 5,000 work hours in manual processing time with 94% accurate dispatch ticket processing.
Energy and Utility
- Accounts payable - Docsumo simplifies accounts payable processing for energy companies by automating invoice data extraction from utility vendors. This reduces manual entry errors and speeds up payment cycles.
- Utility bill management - Docsumo extracts relevant data from utility bills to analyze consumption patterns and cost management. This helps organizations optimize energy usage, manage carbon emissions, and reduce costs effectively.
Docsumo allows Carbon Direct, a New York-based carbon management company, to reduce reporting errors by 35% and ensures the visibility of carbon footprints in real time. This, in turn, saves them over $2,500 in processing costs.
Healthcare
- Accounts payable - Automating invoice processing for medical supplies and services streamlines accounts payable operations in healthcare settings. This ensures timely payments while reducing administrative burdens.
- Insurance compliance - Document AI software helps healthcare teams extract critical information from insurance claims forms, minimizing the risk of claim denials due to missing or incorrect information.
- Income verification - Automating the extraction of income-related documents (e.g., pay stubs) facilitates quick income verification for patient financial assessments, speeding up eligibility determinations for financial assistance programs.
- Patient application processing - Docsumo streamlines patient application processing by reducing wait times for processing applications and enhancing patient experience.
Leveraging Docsumo, Cassena Care, a healthcare firm based in New York, processes over 130k medicaid applications yearly 2x faster with 99.81% accuracy, leading to faster patient onboarding and an improved focus on delivering quality care.
Human Resources (HR)
- Background verification - Docsumo automates the HR document process by processing candidate information from resumes, cover letters, and application forms. The document workflow software can quickly pull out key details such as qualifications, work experience, and contact information and enable HR teams to focus on evaluating candidates instead.
- Candidate onboarding - By automating the extraction of data from onboarding documents (e.g., tax forms, identification documents, and policy agreements), Docsumo minimizes errors and ensures compliance with organizational policies.
- HR regulatory compliance - The Document AI platform can extract and validate data from compliance-related documents, such as employee contracts and regulatory forms. Its validation reduces the risk of legal issues stemming from incomplete or incorrect documentation ensuring compliance with labor laws and internal policies.
Pento, now HiBob, automates its payroll processing with Docsumo while saving 1,500 work hours and $3,000 in late tax filing fines for its clients every month.
FAQs
What types of documents can Document AI Software process?
- Invoices: Extract details such as amounts, dates, and vendor information.
- Bank Statements: Extracts transaction details, account balances, and financial summaries, enabling automated reconciliation and financial analysis.
- Forms: Capturing data from structured forms, such as surveys, applications, and questionnaires.
- Receipts: Extracting transaction data like itemized lists, prices, and payment methods.
- Purchase Orders: Extracting order details such as items, quantities, and delivery instructions.
- Medical Records: Managing and processing health-related documents while ensuring compliance with privacy regulations.
- Scanned Documents: Converting scanned images (PDF, JPG, PNG) into machine-readable text.
- Contracts & Legal Documents: Identifies key clauses, parties involved, dates, and terms, facilitating contract management and legal review processes.
- Tax Returns: Captures relevant financial data, deductions, and tax calculations, streamlining tax preparation and compliance reporting.
What are the main benefits of using Document AI Software in business operations?
- Increased Efficiency: Automates time-consuming tasks like data extraction, reducing manual effort and speeding up document processing.
- Improved Accuracy: Minimizes human error by accurately extracting and validating data from documents.
- Cost Savings: Reduces operational costs by automating repetitive tasks and optimizing document workflows.
- Faster Decision-Making: By quickly processing and analyzing documents, businesses can make more informed, timely decisions.
- Scalability: Easily handles large volumes of documents, allowing businesses to scale operations without compromising efficiency.
- Enhanced Compliance: Ensures that documents are processed and stored in accordance with industry regulations.