Top 10 AI-Based Document Processing Software for Technology Companies

AI-based document processing software allows the organization to extract information from unstructured and complex documents using optical character recognition (OCR), natural language processing (NLP), and machine learning algorithms. 

We’ve curated the list of the 10 best document AI tools for companies for 2023. 

10 best AI-based document processing software for technology companies in 2023

#1. Docsumo 

Equipped with pre-trained invoice capture APIs, Docsumo can capture data from a variety of document formats including Excel, PDF, PNG, JPEG, and others with more than 99% accuracy. If you’re looking for flexible and intelligent document processing software to capture data from structured and unstructured documents, Docsumo is the ideal choice. 

Key features

Ingest, classify, and pre-process any document 

Docsumo parses through documents from scanners, inboxes, and other sources. Docsumo comes with the document auto-classification feature allowing users to classify different document types before capturing data from them. 

Pre-train ML models 

Train custom ML models with as little as 50 documents, and start capturing data from customized APIs specially trained for your use-case.

Data validation within the document 

Excel-like formulas validate extracted data within your documents and databases for reduced errors. Categorize table line items based on descriptions to gather key metrics for decision-making.

Integration with third–party business sources 

For real-time data accuracy, Docsumo can be easily integrated with third-party applications such as CRM, accounting software, and ERP. 

Analytics and reporting 

The self-serve interface with a friendly user dashboard gives insights into the processing time, error rates, and the number of documents uploaded, approved, and held for review. 

Industry agnostic solution 

Docsumo’s touchless processing with 100% document automation works for industries like insurance, finance, real estate, and lending.  

Enterprise-grade security and cloud-based 

To ensure user privacy, Docsumo adheres to industry standards and regulations like SOC2 and GDPR. Being cloud-based, users can access this AI-based document processing software from anywhere and collaborate with team members. 

Cons

• Cannot process handwritten documents. 

#2. Kofax 

AI-based document processing software Kofax combines multichannel document capture and intelligent OCR to allow organizations to process all types of information including unstructured data in business documents and emails. 

Document processing with Kofax’s cognitive capture enables modern workplaces to intelligently automate the otherwise slow, manual, and error-prone data entry process. 

Key features

A single source of truth for all your print and capture needs 

By capturing and processing information from structured, semi-structured, and unstructured documents, Kofax makes document data capture efficient while avoiding costly integration errors. 

Scalable information capture 

Kofax is scalable across the organization as it automates and accelerates business processes for securely capturing all types of information. 

Advanced security 

Reduce compliance risk and boost security with data protection policies, content-based business rules, watermarking for advanced information protection, and security controls. It ensures stringent compliance and information governance in your data workflows. 

Workflow orchestration 

Cognitive AI converts automated workflows with content-aware capture and print technologies. It converts data from unstructured documents into structured data for business intelligence by applying workflow orchestration. 

Zero code deployment 

The zero code deployment drives process improvement, reduces system disruptions, and integrates data with legacy technologies. In addition, Kofax uses robotic process automation (RPA) to speed up document automation workflows.

Multichannel capture 

As an integrated document AI software, Kofax supports multichannel data capture from printed documents, mobile workflows, and emails. 

Cons 

• Limited customization options.

#3. Hyperscience 

Document processing software Hyperscience combines intelligent OCR, computer vision, machine learning, AI, and natural language processing to automate data extraction from documents with both printed and handwritten text in multiple formats. 

Key features 

Intelligent data extraction in multiple formats 

It automates the processing of unstructured and structured documents from inputs including PDF, image, and email with 99.5% accuracy.

Learning capabilities of the ML models 

Firstly, Hyperscience is template-free. In addition, the ML handles document variability by learning from day-to-day processing so that it requires less human intervention over time. 

Human-in-the-loop

To ensure the highest level of accuracy, the ML identifies areas that need human intervention. 

Custom configurable 

Hyperscience’s custom building blocks can be arranged into flows based on your business processes. 

Scalability 

This document AI software which is trained on real-world documents with pre-trained ML models. It is easy to set up and allows organizations to add more use cases often within days without added complexity. 

Cons 

• As per user reviews, the tool struggles to extract information from multiple tables in the same form. 

#4. ABBYY FlexiCapture 

Enterprise-grade document AI software ABBYY FlexiCapture handles the data extraction needs of complex enterprise organizations by combining NLP, ML, and advanced recognition. 

FlexiCapture’s AI-based document processing capabilities enable organizations to focus on compliance and cost reduction, and transform business documents into business value. 

Key features 

NLP-based intelligent data extraction 

The data capture capabilities of NLP extend to automating the identification and extraction of data from unstructured documents like contracts, leases, agreements, and emails along with structured and semistructured documents. The benefits of AI-based document processing software FlexiCapture include quicker transactions and reduced operating costs and errors. 

Data validation and control 

This document AI platform can be trained for continuous improvement and cost control. It identifies, validates, and processes data fields, context, and identities based on business rules. 

Faster STP 

Eliminate the friction of manual processing by automatically extracting content from documents entering through any channel for faster straight-through processing. 

Multi-level document classification 

AI-based classifiers remove the need for manual sorting and labeling. FlexiCapture is trained on the latest ML methods to automate the task of understanding, separating, and routing structured, semi-structured, and unstructured documents. 

Auto-learning 

Advanced ML and NLP capabilities accelerate the time to production and reduce maintenance costs. Users can train the document AI to process flexible and irregular document layouts. 

Image recognition and handwritten ICR 

For processing documents with complex backgrounds such as transcripts and transformation forms or even when the image quality is poor, FlexiCapture has an image enhancement feature. Using advanced ICR technology, the intelligent document AI can extract handwritten data in medical forms, prescriptions, bills, and more. 

Cons 

• Unlike the best AI-based document processing software Docsumo, FlexiCapture does not provide auto-alert for discrepancies or auto-classification and auto-split. 

#5. UiPath 

Powered by AI and robotic process automation (RPA), UiPath helps process everyday documents for data extraction such as onboarding papers, contracts, and invoices to increase the team’s productivity and mitigate the risks of human errors. 

Key features

Intelligent data extraction for a wide range of documents 

Whether your documents involve handwriting, checkboxes, signatures, or other unstructured data which is rotated or low-resolution, UiPath’s AI-based document processing software can handle it all. 

No-code pre-trained machine learning models 

Pre-trained ML models coupled with RPA result in highly intelligent document AI that keeps learning and becomes more accurate over time. The no-code implementation adds to the ease of use. 

Drag and drop document understanding abilities 

What sets UiPath apart from other AI-based document processing software is the user-friendly drag-and-drop interface. Also, the platform can validate data and alert users in case of exceptions. 

Cons 

• As per reviews, users have to train multiple templates with changing columns and row sizes in each PDF. 

#6. Amazon Textract 

Fully managed machine learning document processing software Amazon Textract automatically extracts printed text, handwriting, and other data from scanned documents. 

Key features 

AI-based data extraction without templates and configuration 

Textract uses ML to extract text and structured data from tables and forms within documents with no manual effort. 

Goes beyond OCR 

It goes beyond OCR to extract relationships, structure, and text from documents such as invoices, receipts, and loan processing forms. 

Supports multiple compliance standards 

For enhanced security, Textract’s AI-based document processing software has features supporting encryption and security, and is compliant with HIPAA, GDPR, and other regulations. 

Amazon Augmented AI enables human review 

Implement human reviews to manage sensitive workflows and audit predictions. 

Cons 

• It cannot detect document errors or validate databases.

#7. Google Document AI 

The Document AI suite of solutions by Google has pre-trained models for extracting data from structured documents, along with analyzing, searching, and storing this data. 

Key features

Processing documents from a unified console 

This AI-based document processing software has a unified console for document processing using extractors like OCR, Form Parser, and specialized models. The benefits of Document AI include automating and validating documents to streamline workflow, ensure data compliance, and reduce guesswork. 

State-of-art AI combining ML + OCR 

The pre-trained models use ML and OCR technologies for high-volume, high-value documents. In addition, Google’s knowledge graph technology enriches data such as company name, phone number, and other details to make it more useful. 

Integrate human review 

The human-in-the-loop AI involves the purpose-built capability of adding human review to achieve higher document processing accuracy. 

Digitize text from documents 

Google’s Document AI can extract text, words, paragraphs, and correct rotation from classifying documents and entity extraction. 

Cons 

• Unlike Docsumo, it cannot extract data from unstructured documents and it cannot integrate with third-party software. 

#8. Docparser 

Using Zonal OCR and advanced pattern recognition, Docparser identifies and extracts data from PDF, Word, and image-based documents. This powerful AI-based document processing software is built with automation features for the modern cloud stack. It can automatically fetch documents from various software, extract the information you are looking for, and move it to sources where it belongs. 

Key features 

Create custom parsing rules 

You can build 100% customized parsing rules to extract data within minutes, based on your individual use case. 

Extract tabular data

Docparser’s set of tool features allow extraction and formatting of repeating text patterns and tables from PDF, Word, and Image documents. 

Smart filters for invoice processing 

Advanced Zonal OCR-based smart filters for invoice extraction help extract header data such as tax amounts, invoice ID, and totals from scanned documents. 

Import document automatically 

Using Docparser’s API and cloud integrations, you can automatically import documents, upload files in batches and drag and drop documents from local disks. 

Fetch documents from cloud storage providers 

Importing documents from Docparser involves connecting your cloud storage provider such as Google Drive, OneDrive, and Dropbox. 

Barcode and QR-detection 

Docparser’s inbuilt scanners allow reading barcodes from documents to identify a specific form layout and parcel shipping numbers. 

Cons 

• Docparser does not auto-learn new document layouts. 

#9. Rossum 

Modern cloud-native AI-based document processing software Rossum is built to bring your entire document processing operations from data intake to integration on a single cloud platform. 

Key features

Automate intake and document preparation 

At the pre-processing stage, the platform allows the intake of documents across any format or channel and filters spam and unnecessary documents. 

Adaptable data extraction when layouts vary 

Rossum’s AI-based document processing software reads documents even when the layouts vary and adapts to new changes without new templates. You can extract complex objects such as nested tables and grids. 

Customized document automation process

The automation marketplace allows users to implement pre-built extensions for calculations and sorting, build webhook-driven business logic in low-code environments, and send real-time updates to partners. 

In-built reporting 

Generate useful insights and reports such as user-level metrics and validation time per document without any BI integration. 

Cons 

• Rossum does not have pre-trained ML models that can auto-learn with usage over time. 

#10. Nanonets 

The no-code, workflow-based intelligent AI-based document processing platform Nanonets uses intelligent AI-enhanced OCR API to extract data from documents while automatically labeling entries and performing document classification. 

Key features 

Automated data entry 

Upload unstructured invoices from customers and Nanonets extracts only essential fields to keep your data clean. 

Reconcile invoices 

The AI-led functionality fetches purchase orders and reconciles expenses to match the balances and SKU-level information. 

Automated learning 

AI and OCR-led models learn, understand, and capture data with higher accuracy each time new documents are processed. 

Convert unstructured images into structured and validated data 

What separates Nanonets from other document AI software is its ability to transform unstructured images uploaded from cloud storage providers into structured and validated data which is then sent to business tools like CRM, ERP, and accounting software. 

Cons 

• Nanotes does not allow users to create new document types unlike its counterpart Docsumo. 

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