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:-
Let’s take a look at best document processing tools in no particular order:-
Docsumo is an AI-powered document processing software that automates data entry and document processing tasks. Here are some of its key features:
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.
Docsumo automates data entry tasks by extracting key information from documents and populating it in predefined fields.
Docsumo allows users to define specific data fields for extraction and configure the system to capture data in the desired format.
Docsumo integrates with other business systems, such as accounting software and CRM systems, to streamline data entry and processing tasks.
Docsumo uses data validation rules to ensure that the extracted data is accurate and consistent.
Docsumo provides insights into document processing metrics, such as processing time and error rates, through a user-friendly dashboard.
Docsumo adheres to industry-standard security and compliance protocols, such as GDPR and SOC-2, to ensure the safety and privacy of user data.
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.
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:
Extract key data from invoices and automating data entry into accounting software.
Extract key data from contracts and populate it in predefined fields.
Automate insurance claims processing by extracting key data from claim forms and populating it in predefined fields, reducing manual data entry and improving accuracy.
Docsumo can be used to automate commercial lending such as underwriting and identity verification by extracting key data from tax and identity verification documents.
Docsumo can be used to automate capturing key data from logistics documents such as shipping label, bill of lading, and packing list.
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.
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.
Docsumo offers several pricing plans to meet the needs of businesses of different sizes and requirements. Here are some of the pricing options available:
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
This plan is suitable for larger businesses that need to capture specific data points from documents and train on their data
This plan is suitable for large enterprises with specific requirements and starts at custom pricing. It includes advanced features, dedicated support, and customizable options.
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:-
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.
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.
Kofax integrates with other business systems, such as ERP and CRM systems, to streamline document processing and data entry tasks.
Kofax supports mobile capture, allowing users to capture and process documents using their mobile devices, such as smartphones and tablets.
Kofax provides insights into document processing metrics, such as processing time and error rates, through a user-friendly dashboard.
Kofax supports multi-channel capture, allowing users to capture and process documents from various sources, such as email, fax, and web portals.
Kofax uses intelligent document recognition technology to identify and classify different types of documents, making it easier to process them.
Kofax adheres to industry-standard security and compliance protocols, such as GDPR and HIPAA, to ensure the safety and privacy of user data.
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.
Here are some of Kofax use cases:
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.
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.
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.
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.
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.
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.
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.
Ask for pricing.
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:
Hyperscience uses advanced machine learning algorithms to extract data from various types of documents, such as invoices, receipts, and forms, with high accuracy.
Hyperscience combines automation with human validation to ensure high accuracy rates and reduce errors in document processing.
Hyperscience uses artificial intelligence to automatically classify documents into predefined categories, such as invoices, contracts, and applications.
Hyperscience uses machine learning to automatically validate data extracted from documents, reducing the need for manual data entry.
Hyperscience integrates with other business systems, such as CRM and ERP systems, to streamline document processing workflows and data entry tasks.
Hyperscience automates document processing workflows by automatically routing documents to the right people or systems for processing.
Hyperscience provides real-time insights into document processing metrics, such as processing time and error rates, through a user-friendly dashboard.
Hyperscience adheres to industry-standard security and compliance protocols, such as GDPR and HIPAA, to ensure the safety and privacy of user data.
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.
Here are some use cases of Hyperscience:-
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.
The software can extract relevant data such as policy numbers, dates, and claim amounts, and route the claims to the appropriate departments for processing.
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.
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.
Ask for pricing.
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:
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.
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.
Abbyy FlexiCapture supports over 200 languages and can extract data from documents in multiple languages simultaneously.
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.
Abbyy FlexiCapture can integrate with other business systems such as enterprise resource planning (ERP), customer relationship management (CRM), and electronic content management (ECM) systems.
FlexiCapture can be deployed on-premises or in the cloud, depending on the needs of the business.
FlexiCapture provides detailed reports and analytics on document processing and data extraction performance, allowing businesses to identify bottlenecks and areas for improvement.
Here are some use cases for Abbyy FlexiCapture:-
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.
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.
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.
Law firms and legal departments can use Abbyy FlexiCapture to automate the processing of legal documents such as contracts, agreements, and court filings.
Ask for pricing
Ocrolus is a financial technology company that specializes in data verification and analysis. Some of the features offered by Ocrolus include:
Ocrolus uses optical character recognition (OCR) and machine learning to extract data from various financial documents such as bank statements, pay stubs, and invoices.
Ocrolus compares extracted data against the source document to ensure accuracy and completeness.
Ocrolus uses pattern recognition and machine learning algorithms to detect fraudulent activity within financial documents.
Ocrolus provides customizable workflows for data processing and validation to meet the unique needs of different organizations.
Ocrolus can be integrated into existing software systems through its API, allowing for seamless integration with other applications.
Ocrolus provides real-time reporting and analytics on extracted data, enabling organizations to make informed decisions.
Ocrolus employs multiple layers of security to protect sensitive financial data, including encryption, firewalls, and access controls.
Ocrolus is an AI-powered platform for analyzing financial documents. Here are some of the use cases where Ocrolus can be used:
The platform can extract data from bank statements, pay stubs, tax returns, and other financial documents to speed up the loan approval process.
Ocrolus can be used by mortgage lenders to extract financial data from borrower documents and automate the underwriting process.
The platform can extract data from insurance claims documents, such as medical records and invoices, to accelerate the claims process.
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.
Extract financial data from financial reports, SEC filings, and other financial documents to analyze investment opportunities.
Capture financial data from tax documents, such as W-2 forms and 1099 forms, to automate the tax preparation process.
Ask for pricing.
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:
Amazon Textract supports a wide range of document types, including PDFs, scanned documents, and images.
Amazon Textract can analyze the layout of a document, including tables and forms, and extract data from specific fields.
Amazon Textract uses machine learning algorithms to accurately extract text from documents, including handwriting and low-quality scans.
Amazon Textract provides customizable templates for data extraction, allowing customers to extract specific data fields relevant to their business needs.
Amazon Textract can process large volumes of documents quickly and efficiently, enabling organizations to process documents at scale.
Amazon Textract can be integrated with other AWS services, including Amazon S3, Amazon DynamoDB, and Amazon Comprehend.
Amazon Textract is designed to meet strict security and compliance requirements, including HIPAA, PCI, and SOC 2.
Here are some of the use cases where Amazon Textract can be useful:
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.
Extract data from forms such as tax forms, insurance claims, and loan applications.
Capture data from legal documents such as contracts and court orders.
Extract data from medical records, such as patient information and medical history, to help healthcare providers make informed decisions.
Automate data capture from compliance documents such as regulatory filings and audit reports to help organizations meet regulatory requirements.
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.
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.
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:
Google Doc AI can analyze documents in various formats, including PDFs, images, and scanned documents, and extract structured data from them.
The platform uses NLP to identify and extract information from unstructured text, such as contracts, invoices, and receipts.
Google Doc AI offers pre-built models for various document types, but also allows users to create custom models tailored to their specific needs.
The platform verifies extracted data against predefined rules to ensure accuracy and consistency.
Google Doc AI enables users to review and validate extracted data through a human-in-the-loop process, ensuring high levels of accuracy.
The platform allows teams to collaborate on document processing tasks, with the ability to assign tasks, track progress, and share data.
Google Doc AI is built on Google Cloud Platform, which adheres to industry-standard security and compliance protocols.
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:
Banks and financial institutions can use Google Doc AI to extract data from loan applications, tax documents, and financial statements.
Hospitals and healthcare providers can use the platform to extract information from medical records, insurance claims, and billing documents.
Law firms can use Google Doc AI to extract data from contracts, legal briefs, and court documents.
Real estate companies can use the platform to extract data from property listings, lease agreements, and mortgage applications.
Retail companies can use Google Doc AI to extract data from invoices, receipts, and purchase orders.
Government agencies can use the platform to extract data from public records, census data, and tax filings.
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
Docparser is a data extraction and document parsing software that allows businesses to automate their data entry processes. Here are some of its features:
Docparser can extract data from PDFs, scanned documents, emails, and other file types using OCR technology.
Once data is parsed, Docparser can extract specific fields such as names, addresses, and phone numbers.
Docparser can integrate with other tools such as Zapier, Salesforce, and Google Sheets to automatically transfer parsed data.
Docparser allows users to create custom parsing templates based on their specific data extraction needs.
Docparser can automate data extraction and parsing processes, saving businesses time and resources.
Docparser provides analytics on parsed data, including error rates and parsing time, to help users improve their processes.
Docparser is secure and compliant with GDPR and HIPAA regulations.
Here are some of the use cases where Docparser can be useful:
Capture data from invoices, such as vendor information, invoice number, and line item details, which can help automate accounts payable and invoice processing workflows.
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.
Automate data capture from insurance forms, such as claims and applications. This can help automate claims processing and improve efficiency.
Extract data from legal documents, such as contracts and court orders to help legal professionals quickly find and extract relevant information.
Docparser can be used to extract data from property listings, lease agreements, and other real estate documents.
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.
Rossum.ai is an artificial intelligence software for document processing and data extraction. Its main features include:
Rossum.ai uses AI and machine learning algorithms to extract data from invoices, receipts, and other documents in various formats.
Once data is parsed, Rossum.ai can extract specific fields such as dates, amounts, and company names.
Rossum.ai can integrate with other tools such as Zapier, Salesforce, and Microsoft Dynamics to automatically transfer extracted data.
Rossum.ai allows users to customize and configure their own extraction models to suit their specific data extraction needs.
Rossum.ai can automate data extraction and document processing processes, reducing manual labor and errors.
Rossum.ai allows multiple team members to collaborate on document processing tasks, increasing productivity and efficiency.
Rossum.ai provides analytics on document processing performance, including accuracy rates and processing time, to help users improve their processes.
Rossum.ai is secure and compliant with GDPR and other data privacy regulations.
Here are some additional use cases for Rossum.ai:
Automate the extraction of data from invoices and receipts, reducing manual labor and errors in data entry.
Rossum.ai can be used to extract data from resumes, applications, and other HR-related documents.
Capture data from shipping documents, such as bills of lading and delivery receipts.
Ask for pricing
Nanonets is a cloud-based platform for building custom deep learning models for image and text data. Some of the features of NanoNets are:
Nanonets allows you to create custom deep learning models using your own data without requiring a lot of expertise in deep learning.
The platform uses a proprietary AutoML algorithm to optimize your models for accuracy, speed, and efficiency.
Nanonets integrates with popular programming languages like Python, Java, and Ruby, making it easy to use with your existing codebase.
The platform supports both image and text data, allowing you to build models for a wide range of use cases.
Nanonets provides an easy-to-use API that allows you to integrate your models into your applications with just a few lines of code.
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.
Nanonets handles the end-to-end model training and deployment process, making it easy to get your models up and running quickly.
Nanonets is built on a cloud-based infrastructure, which means that you can easily scale your models as your data and usage grows.
Here are some of the use cases where NanoNets can be useful:
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.
Nanonets can be used to build OCR models that can recognize and extract text from images, PDFs, and other documents.
NanoNets can be used to build NLP models for tasks such as sentiment analysis, text classification, and language translation.
Build models for object detection and classification tasks in autonomous vehicles, such as identifying pedestrians, cars, and other objects in real-time.
Build models that can perform quality control checks on products, such as identifying defects in manufacturing processes.
Ask for pricing
As the next step, you need to get your management and the team on the same table, and ask yourself 5 questions:-
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.
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.
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.
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.
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.
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