Intelligent Document Processing

Top 10 intelligent document processing tools in 2023

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Top 10 intelligent document processing tools in 2023

Document processing tools are designed to help users create, edit, format, manage, and manipulate electronic documents. These tools can include anything from automated document sorting, indexing and archiving, to advanced analysis capabilities such as extracting data from structured and unstructured documents. Document processing tools commonly feature optical character recognition (OCR), natural language processing (NLP) and other advanced technologies to extract data from documents. 

In this article, we talk about 10 best document processing tools that help you capture data from unstructured documents. 

Let’s jump right into it:-

Best document processing tools in 2023

Let’s take a look at best document processing tools in no particular order:-

1. Docsumo 

Docsumo is an AI-powered document processing software that automates data entry and document processing tasks. Here are some of its key features:

AI-powered document reading

Docsumo uses artificial intelligence (AI) and machine learning (ML) based intelligent document processing technology to extract data from unstructured documents, such as invoices, receipts, and contracts.

Automated data extraction

Docsumo automates data entry tasks by extracting key information from documents and populating it in predefined fields.

Customizable data capture

Docsumo allows users to define specific data fields for extraction and configure the system to capture data in the desired format.

Integration with other systems

Docsumo integrates with other business systems, such as accounting software and CRM systems, to streamline data entry and processing tasks.

Real-time data validation

Docsumo uses data validation rules to ensure that the extracted data is accurate and consistent.

Analytics and reporting

Docsumo provides insights into document processing metrics, such as processing time and error rates, through a user-friendly dashboard.

Data security and compliance

Docsumo adheres to industry-standard security and compliance protocols, such as GDPR and SOC-2, to ensure the safety and privacy of user data.

Cloud-based platform

Docsumo is a cloud-based platform that can be accessed from anywhere with an internet connection, making it easy to collaborate and share documents with team members.

Use Cases

Docsumo is a versatile document processing software that can be used in a variety of industries and applications. Here are some of its use cases:

Accounts payable automation

Extract key data from invoices and automating data entry into accounting software.

Contract management

Extract key data from contracts and populate it in predefined fields.

Insurance claims processing

Automate insurance claims processing by extracting key data from claim forms and populating it in predefined fields, reducing manual data entry and improving accuracy.

Commercial Lending

Docsumo can be used to automate commercial lending such as underwriting and identity verification by extracting key data from tax and identity verification documents.

Logistics

Docsumo can be used to automate capturing key data from logistics documents such as shipping label, bill of lading, and packing list.

Legal

Automate legal processes such as contract management and discovery by extracting key data from documents and populating it in predefined fields, reducing manual data entry and improving efficiency.

Real estate

Automate real estate processes such as lease management and property valuation by extracting key data from documents and populating it in predefined fields, reducing manual data entry and improving accuracy.

Pricing 

Docsumo offers several pricing plans to meet the needs of businesses of different sizes and requirements. Here are some of the pricing options available:

Growth

This plan is suitable for small businesses or teams and starts at $500 per month. Ideal for start-ups and businesses that need to automate one or two document types

Business Plan

This plan is suitable for larger businesses that need to capture specific data points from documents and train on their data

Enterprise Plan

This plan is suitable for large enterprises with specific requirements and starts at custom pricing. It includes advanced features, dedicated support, and customizable options.

Docsumo also offers a 14-day free trial for users to test the software before committing to a paid plan. 

2. Kofax

Kofax is a document processing and automation software that helps businesses automate their manual data entry tasks and streamline their document processing workflows. Here are some of its key features:-

Intelligent data capture

Kofax uses intelligent data capture technology to automatically extract data from various types of documents, such as invoices, receipts, and forms, and convert them into structured data.

Cognitive automation

Kofax uses cognitive automation to automate complex document workflows, such as invoice processing and loan origination, by automatically routing documents to the right people or systems for processing.

Integration with other systems

Kofax integrates with other business systems, such as ERP and CRM systems, to streamline document processing and data entry tasks.

Mobile capture

Kofax supports mobile capture, allowing users to capture and process documents using their mobile devices, such as smartphones and tablets.

Analytics and reporting

Kofax provides insights into document processing metrics, such as processing time and error rates, through a user-friendly dashboard.

Multi-channel capture

Kofax supports multi-channel capture, allowing users to capture and process documents from various sources, such as email, fax, and web portals.

Intelligent document recognition

Kofax uses intelligent document recognition technology to identify and classify different types of documents, making it easier to process them.

Compliance and security

Kofax adheres to industry-standard security and compliance protocols, such as GDPR and HIPAA, to ensure the safety and privacy of user data.

Cloud-based platform

Kofax is a cloud-based platform that can be accessed from anywhere with an internet connection, making it easy to collaborate and share documents with team members.

Use-cases 

Here are some of Kofax use cases:

Accounts payable automation

Kofax can be used to automate accounts payable processes by extracting key data from invoices and automating data entry into accounting software, reducing manual data entry and improving accuracy.

Loan origination

Kofax can be used to automate loan origination processes by extracting key data from loan applications and populating it in predefined fields, reducing manual data entry and improving efficiency.

Insurance claims processing

Kofax can be used to automate insurance claims processing by extracting key data from claim forms and populating it in predefined fields, reducing manual data entry and improving accuracy.

Human resources

Kofax can be used to automate HR processes such as onboarding, candidate screening, and resume parsing by extracting key data from documents and populating it in predefined fields.

Healthcare

Kofax can be used to automate healthcare processes such as medical record keeping and claims processing by extracting key data from documents and populating it in predefined fields.

Government

Kofax can be used by government agencies to automate document processing workflows, such as permit and license applications, by extracting key data from documents and automating the routing of documents to the right people or systems.

Financial services

Kofax can be used in financial services to automate processes such as mortgage processing and credit card applications, by extracting key data from documents and populating it in predefined fields.

Pricing 

Ask for pricing.

3. Hyperscience

Hyperscience is an intelligent automation platform that combines advanced machine learning and artificial intelligence with human-in-the-loop workflows to automate and streamline document processing tasks. Here are some of its key features:

Intelligent data extraction

Hyperscience uses advanced machine learning algorithms to extract data from various types of documents, such as invoices, receipts, and forms, with high accuracy.

Human-in-the-loop workflows

Hyperscience combines automation with human validation to ensure high accuracy rates and reduce errors in document processing.

Document classification

Hyperscience uses artificial intelligence to automatically classify documents into predefined categories, such as invoices, contracts, and applications.

Data validation

Hyperscience uses machine learning to automatically validate data extracted from documents, reducing the need for manual data entry.

Integrations with other systems

Hyperscience integrates with other business systems, such as CRM and ERP systems, to streamline document processing workflows and data entry tasks.

Workflow automation

Hyperscience automates document processing workflows by automatically routing documents to the right people or systems for processing.

Real-time data insights

Hyperscience provides real-time insights into document processing metrics, such as processing time and error rates, through a user-friendly dashboard.

Advanced security and compliance

Hyperscience adheres to industry-standard security and compliance protocols, such as GDPR and HIPAA, to ensure the safety and privacy of user data.

Cloud-based platform

Hyperscience is a cloud-based platform that can be accessed from anywhere with an internet connection, making it easy to collaborate and share documents with team members.

Use-cases

Here are some use cases of Hyperscience:-

Invoice Processing

The software can extract data such as vendor name, invoice number, and amount due, and can also verify the accuracy of the data against the company's financial systems.

Insurance Claims Processing

The software can extract relevant data such as policy numbers, dates, and claim amounts, and route the claims to the appropriate departments for processing.

Healthcare Data Management

Digitize patient records, extract data from medical forms, and automate administrative tasks such as insurance billing. The software can also identify potential errors or discrepancies in patient data, helping to improve patient safety and care quality.

Financial Document Processing

The software can extract relevant data such as personal information, income statements, and credit scores, and use this data to determine eligibility and make informed decisions.

Pricing

Ask for pricing.

4. Abbyy Flexicapture 

Abbyy FlexiCapture is a powerful data capture and document processing software that uses optical character recognition (OCR), machine learning, and other advanced technologies to extract data from various sources such as paper documents, forms, emails, and more. Some of the features of Abbyy FlexiCapture include:

Intelligent Document Processing

Abbyy FlexiCapture uses advanced algorithms to identify and extract data from documents regardless of their layout or format. It can also recognize handwritten text and barcode information.

Automated Data Extraction

FlexiCapture can extract data from a variety of sources such as invoices, purchase orders, shipping manifests, and other business documents. It can also automatically validate the extracted data to ensure accuracy.

Multilingual Support

Abbyy FlexiCapture supports over 200 languages and can extract data from documents in multiple languages simultaneously.

Data Verification and Validation

FlexiCapture uses sophisticated verification and validation algorithms to ensure the accuracy and completeness of the extracted data. It can also flag potential errors or inconsistencies for review.

Integration with Other Systems

Abbyy FlexiCapture can integrate with other business systems such as enterprise resource planning (ERP), customer relationship management (CRM), and electronic content management (ECM) systems.

Flexible Deployment Options

FlexiCapture can be deployed on-premises or in the cloud, depending on the needs of the business.

Advanced Reporting and Analytics

FlexiCapture provides detailed reports and analytics on document processing and data extraction performance, allowing businesses to identify bottlenecks and areas for improvement.

Use cases

Here are some use cases for Abbyy FlexiCapture:-

Accounts Payable Processing

The software can extract data such as vendor name, invoice number, and amount due, and can validate the accuracy of the data against financial systems.

Healthcare Claims Processing

The software can extract data such as patient name, diagnosis codes, and treatment information, and can validate the accuracy of the data against electronic health record (EHR) systems.

Human Resources Onboarding

Abbyy FlexiCapture can help automate the onboarding process for new employees by extracting data from forms such as W-4s, I-9s, and employee agreements. 

Legal Document Processing

Law firms and legal departments can use Abbyy FlexiCapture to automate the processing of legal documents such as contracts, agreements, and court filings. 

Pricing

Ask for pricing 

5. Orcolous

Ocrolus is a financial technology company that specializes in data verification and analysis. Some of the features offered by Ocrolus include:

Automated Data Extraction

Ocrolus uses optical character recognition (OCR) and machine learning to extract data from various financial documents such as bank statements, pay stubs, and invoices.

Data Validation

Ocrolus compares extracted data against the source document to ensure accuracy and completeness.

Fraud Detection

Ocrolus uses pattern recognition and machine learning algorithms to detect fraudulent activity within financial documents.

Customizable Workflows

Ocrolus provides customizable workflows for data processing and validation to meet the unique needs of different organizations.

API Integration

Ocrolus can be integrated into existing software systems through its API, allowing for seamless integration with other applications.

Real-time Reporting

Ocrolus provides real-time reporting and analytics on extracted data, enabling organizations to make informed decisions.

Secure Data Storage

Ocrolus employs multiple layers of security to protect sensitive financial data, including encryption, firewalls, and access controls.

Use-cases

Ocrolus is an AI-powered platform for analyzing financial documents. Here are some of the use cases where Ocrolus can be used:

Loan processing

The platform can extract data from bank statements, pay stubs, tax returns, and other financial documents to speed up the loan approval process.

Mortgages

Ocrolus can be used by mortgage lenders to extract financial data from borrower documents and automate the underwriting process.

Insurance claims

The platform can extract data from insurance claims documents, such as medical records and invoices, to accelerate the claims process.

Account verification

Ocrolus can be used by financial institutions to verify account holder information, such as name, address, and bank account number, by analyzing bank statements and other financial documents.

Investment analysis

Extract financial data from financial reports, SEC filings, and other financial documents to analyze investment opportunities.

Tax preparation

Capture financial data from tax documents, such as W-2 forms and 1099 forms, to automate the tax preparation process.

Pricing 

Ask for pricing. 

6. Amazon Textract 

Amazon Textract is a cloud-based optical character recognition (OCR) service offered by Amazon Web Services (AWS) that uses machine learning to extract text and data from various types of documents. Some of the features offered by Amazon Textract include:

Document Type Support

Amazon Textract supports a wide range of document types, including PDFs, scanned documents, and images.

Automatic Document Layout Analysis

Amazon Textract can analyze the layout of a document, including tables and forms, and extract data from specific fields.

Accurate Text Extraction

Amazon Textract uses machine learning algorithms to accurately extract text from documents, including handwriting and low-quality scans.

Customizable Data Extraction

Amazon Textract provides customizable templates for data extraction, allowing customers to extract specific data fields relevant to their business needs.

Batch Processing

Amazon Textract can process large volumes of documents quickly and efficiently, enabling organizations to process documents at scale.

Integration with Other AWS Services

Amazon Textract can be integrated with other AWS services, including Amazon S3, Amazon DynamoDB, and Amazon Comprehend.

Secure and Compliant

Amazon Textract is designed to meet strict security and compliance requirements, including HIPAA, PCI, and SOC 2.

Use-cases

Here are some of the use cases where Amazon Textract can be useful:

Invoice processing

Automatically extract data from invoices, such as vendor information, invoice number, and line item details, which can help automate accounts payable and invoice processing workflows.

Forms processing

Extract data from forms such as tax forms, insurance claims, and loan applications.

Legal document processing

Capture data from legal documents such as contracts and court orders. 

Healthcare document processing

Extract data from medical records, such as patient information and medical history, to help healthcare providers make informed decisions.

Compliance document processing

Automate data capture from compliance documents such as regulatory filings and audit reports to help organizations meet regulatory requirements.

Mortgage document processing

Amazon Textract can be used to extract data from mortgage documents, such as loan applications and closing documents, to help automate the mortgage processing workflow.

Pricing 

Amazon Textract pricing is based on the number of pages processed per month, with different pricing tiers based on the volume of pages. The pricing starts at $0.0015 per page for the first 1 million pages and decreases as the volume increases.

Amazon Textract also offers a free tier for customers to try the service with up to 1,000 pages per month free of charge for the first 12 months.

7. Google Doc AI

Google Doc AI is a cloud-based artificial intelligence (AI) platform designed to automate document processing and data extraction tasks. Some of the key features of Google Doc AI include:

Document Parsing

Google Doc AI can analyze documents in various formats, including PDFs, images, and scanned documents, and extract structured data from them.

Natural Language Processing (NLP)

The platform uses NLP to identify and extract information from unstructured text, such as contracts, invoices, and receipts.

Customizable Models

Google Doc AI offers pre-built models for various document types, but also allows users to create custom models tailored to their specific needs.

Data Validation

The platform verifies extracted data against predefined rules to ensure accuracy and consistency.

Human-in-the-Loop Review

Google Doc AI enables users to review and validate extracted data through a human-in-the-loop process, ensuring high levels of accuracy.

Collaboration

The platform allows teams to collaborate on document processing tasks, with the ability to assign tasks, track progress, and share data.

Secure and Compliant

Google Doc AI is built on Google Cloud Platform, which adheres to industry-standard security and compliance protocols.

Use-cases

Google Doc AI has a wide range of use cases across industries and sectors. Here are some examples of how the platform can be used:

Finance

Banks and financial institutions can use Google Doc AI to extract data from loan applications, tax documents, and financial statements.

Healthcare

Hospitals and healthcare providers can use the platform to extract information from medical records, insurance claims, and billing documents.

Legal

Law firms can use Google Doc AI to extract data from contracts, legal briefs, and court documents.

Real Estate

Real estate companies can use the platform to extract data from property listings, lease agreements, and mortgage applications.

Retail

Retail companies can use Google Doc AI to extract data from invoices, receipts, and purchase orders.

Government

Government agencies can use the platform to extract data from public records, census data, and tax filings.

Pricing 

Google Doc AI's pricing model is divided into two tiers: Standard and Advanced. The Standard tier offers basic document parsing and NLP capabilities, while the Advanced tier includes additional features such as entity extraction, custom entity recognition, and the ability to train custom models

8. Docparser

Docparser is a data extraction and document parsing software that allows businesses to automate their data entry processes. Here are some of its features:

Document parsing

Docparser can extract data from PDFs, scanned documents, emails, and other file types using OCR technology.

Data extraction

Once data is parsed, Docparser can extract specific fields such as names, addresses, and phone numbers.

Integrations

Docparser can integrate with other tools such as Zapier, Salesforce, and Google Sheets to automatically transfer parsed data.

Custom templates

Docparser allows users to create custom parsing templates based on their specific data extraction needs.

Automation

Docparser can automate data extraction and parsing processes, saving businesses time and resources.

Analytics

Docparser provides analytics on parsed data, including error rates and parsing time, to help users improve their processes.

Security

Docparser is secure and compliant with GDPR and HIPAA regulations.

Use-cases

Here are some of the use cases where Docparser can be useful:

Invoicing and accounting

Capture data from invoices, such as vendor information, invoice number, and line item details, which can help automate accounts payable and invoice processing workflows.

Banking and finance

Docparser can be used to extract data from bank statements, loan applications, and financial reports, which can help automate data entry and reduce processing time.

Insurance

Automate data capture from insurance forms, such as claims and applications. This can help automate claims processing and improve efficiency.

Legal

Extract data from legal documents, such as contracts and court orders to help legal professionals quickly find and extract relevant information.

Real estate

Docparser can be used to extract data from property listings, lease agreements, and other real estate documents. 

Pricing

Docparser offers three pricing plans:-

Starter plan: $29/month - allows up to 500 document uploads per month and 50 fields per document.

Business plan: $99/month - allows up to 2,500 document uploads per month and 150 fields per document.

Professional plan: $249/month - allows up to 10,000 document uploads per month and 500 fields per document.

9. Rossum 

Rossum.ai is an artificial intelligence software for document processing and data extraction. Its main features include:

Document parsing

Rossum.ai uses AI and machine learning algorithms to extract data from invoices, receipts, and other documents in various formats.

Data extraction

Once data is parsed, Rossum.ai can extract specific fields such as dates, amounts, and company names.

Integrations

Rossum.ai can integrate with other tools such as Zapier, Salesforce, and Microsoft Dynamics to automatically transfer extracted data.

Customization

Rossum.ai allows users to customize and configure their own extraction models to suit their specific data extraction needs.

Automation

Rossum.ai can automate data extraction and document processing processes, reducing manual labor and errors.

Collaboration

Rossum.ai allows multiple team members to collaborate on document processing tasks, increasing productivity and efficiency.

Analytics

Rossum.ai provides analytics on document processing performance, including accuracy rates and processing time, to help users improve their processes.

Security

Rossum.ai is secure and compliant with GDPR and other data privacy regulations.

Use-cases

Here are some additional use cases for Rossum.ai:

Accounts payable

Automate the extraction of data from invoices and receipts, reducing manual labor and errors in data entry. 

Human resources

Rossum.ai can be used to extract data from resumes, applications, and other HR-related documents. 

Logistics

Capture data from shipping documents, such as bills of lading and delivery receipts. 

Pricing 

Ask for pricing 

10. Nanonets

Nanonets is a cloud-based platform for building custom deep learning models for image and text data. Some of the features of NanoNets are:

Custom model creation

Nanonets allows you to create custom deep learning models using your own data without requiring a lot of expertise in deep learning.

AutoML

The platform uses a proprietary AutoML algorithm to optimize your models for accuracy, speed, and efficiency.

Integration with popular programming languages

Nanonets integrates with popular programming languages like Python, Java, and Ruby, making it easy to use with your existing codebase.

Support for image and text data

The platform supports both image and text data, allowing you to build models for a wide range of use cases.

Easy-to-use API

Nanonets provides an easy-to-use API that allows you to integrate your models into your applications with just a few lines of code.

Pre-trained models

The platform provides pre-trained models for common use cases, allowing you to get started quickly without having to create your own models from scratch.

Model training and deployment

Nanonets handles the end-to-end model training and deployment process, making it easy to get your models up and running quickly.

Cloud-based infrastructure

Nanonets is built on a cloud-based infrastructure, which means that you can easily scale your models as your data and usage grows.

Use-cases

Here are some of the use cases where NanoNets can be useful:

Object detection and classification

Build custom models for object detection and classification tasks in computer vision. For example, detecting and classifying different types of objects in images or videos.

Optical character recognition (OCR)

Nanonets can be used to build OCR models that can recognize and extract text from images, PDFs, and other documents.

Natural language processing (NLP)

NanoNets can be used to build NLP models for tasks such as sentiment analysis, text classification, and language translation.

Autonomous vehicles

Build models for object detection and classification tasks in autonomous vehicles, such as identifying pedestrians, cars, and other objects in real-time.

Quality control

Build models that can perform quality control checks on products, such as identifying defects in manufacturing processes.

Pricing

Ask for pricing 

Questions you need to ask yourself before buying a document processing software

As the next step, you need to get your management and the team on the same table, and ask yourself 5 questions:-

Q1 - What is something you’re trying to achieve with automation?

This question might sound vague at first but you need to have a clear answer to this question. Are you trying to fix manual data entry because you want to free up human resources and put them to more important tasks? Are you trying to grow your business and slow manual data entry slows it down? Is the inaccuracy in manual data extraction something you want to fix? Answer all these questions in yes or no, and find a way to quantify them. The answers to these questions and the metrics you pick will help you judge the success of automating the process when you look back.  

Q2- What is the scale of the problem?

Once you’ve identified the problem statement and objective, you need to identify the scale of it. If you’re processing a few hundred documents, it is possible that the cost to automate outweighs the outcome. You need to compare the objective you’re trying to achieve against the scale of the problem and deduce the outcome and success metrics. No matter what business you are in, you’re in the business of making profit. If automation is nothing but a fancy addition to your business, it’s probably not worth it. Ensure in this step that the benefits you get out of automation makes up for the money you put in.

Q3 - What is the scale of automation you want?

This is yet another crucial question you need to answer. Automating everything is not ideal or practical.  Ask your team whether you strictly need end-to-end automation. That’s where answers to question 1 & 2 come into picture. If you’re processing a few hundred documents, and you want to increase the turn around time & reduce inaccuracy, you’re probably better off with a semi-automated solution with a human in the loop for review exceptions. If you’re processing thousands of documents a month, and have a team of dozens of data entry operators looking at these documents in and out, you can explore the opportunity to automate it end-to-end. Remember, automation is not out there to eliminate human intervention completely but to enable humans to work efficiently.

Q4 - What kind of solution do you want?

Once you have made it through the first 3 questions, it’s time to answer whether you need a template-based semi-automated data capture solution or an AI-based IDP solution. It shouldn’t be a difficult decision to make at this point since you’re already clear on the problem statement, the objective of the automation, and the scale of the problem and solution. If you’re processing different document types with varying structures, you probably need an intelligent document capture solution that adapts to varying structures. A template-based data capture solution is what you need if you’re processing one of two document types with almost similar structures and templates.

Q5 - Do you have resources to successfully enable automation?

One of the most crucial aspects of automation which is often overlooked is if you have enough resources to enable this automation. Remember, that an automated data extraction software is not a stand-alone software - it receives and pushes data back and forth from multiple software in your system. You need multiple such integrations for this solution to work properly.

Suggested Case Study
Automating Portfolio Management for Westland Real Estate Group
The portfolio includes 14,000 units across all divisions across Los Angeles County, Orange County, and Inland Empire.
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Pankaj Tripathi
Written by
Pankaj Tripathi

Helping enterprises capture data for analytics and decisioning

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