IDP
Best IDP Software 2025: Expert Reviews
Feb 5, 2025
10 min read
The world will create over 394 zettabytes by 2028, finds a study by Statista. While the data growth was already steep, the pandemic and the following rapid digitization gave it a powerful springboard.
This data forms the foundation of future analytics and artificial intelligence (AI) projects. 72% of organizations that McKinsey surveyed had adopted AI last year (a dramatic increase over the past few years), with cost decrease and revenue increase being the most expected outcomes.
However, the biggest challenges in adopting AI org-wide tend to be data-related.
Quality: Data quality is a grave concern. Studies show that 77% of IT decision-makers don’t trust their own data.
Actionability: Sometimes, even with data, organizations fail to create actionable insights in time. As a result, 76% of decision-makers report missing out on revenue opportunities.
Availability: This is a key problem — easily solvable. Most data, i.e., valuable business information, is stored in the form of documents. Both current and historical contracts, statements of procedures (SOPs), invoices, research reports, whitepapers, etc. are stored as PDFs or Word documents.
Extracting and using data from these documents can be a huge challenge. This is what some of the best intelligent document processing software are solving today.
What is Intelligent Document Processing?
Intelligent document processing (IDP) is a technology that extracts, classifies and processes data from documents. Some of its defining characteristics are:
Technology: Modern IDP uses machine learning (ML), natural language processing (NLP) and advanced AI to extract, classify and process data. This makes it faster, more efficient and more accurate.
Context: With AI and NLP, intelligent document processing goes beyond just identifying text. It helps make connections between data points and view them in context.
Data: IDP can effectively process structured, semi-structured and unstructured documents. A hand-written note to a 500-page annual report—no sweat! It can also run verification and validation processes to ensure accuracy.
Automation: IDP offers a great starting point for workflow automation. For instance, you can receive an invoice via email, process it using IDP, automatically enter the information into the enterprise resource planning (ERP) systems and make it available to the relevant stakeholder for approval.
How does IDP work?
The IDP workflow can vary depending on the nature of your data, volume, structure and use case. However, a typical document processing workflow would be as follows.
Document ingestion
You can manually upload documents to an IDP system, or it can automatically receive them from sources like email or cloud storage. Either way, the first step is to accept PDFs, Word documents, Spreadsheets, emails, scanned documents, or handwritten notes.
Data extraction
The IDP might use optical character recognition (OCR) if the document contains images or handwritten text. Otherwise, NLP and ML technologies would be great for precise data extraction and parsing.
Let’s say we’re extracting data from a contract. IDP is good for field extraction, such as the execution date, validity period, signatories, etc. It can also extract information from unstructured data, such as contract clauses.
Document classification
Based on the extracted data, IDP will classify the document according to your nomenclature as an invoice, a purchase order or a receipt. This information is then used for downstream processes. For instance, if a document is identified as an invoice, it is sent to the right stakeholder for approval.
Data validation
To ensure accuracy, IDP validates the data based on your set parameters, which could be your own rules or external sources. For instance, IDP can verify each invoice against the purchase order to ensure there is no over- or under-charge.
Downstream integration
Once the IDP process is almost over, it’s time to prepare the data for business applications. This could be your analytics platform, complex document workflows, or generative AI needs.
For instance, we used IDP and related AI technologies to create a comprehensive proposal creation tool for a Middle Eastern events company. See how it works.
10 Best Intelligent Document Processing Software in 2025
From IBM Watson to Google and Amazons of the world, dozens of intelligent document processing software are available. In this section, we narrow it down to the ten best, in no particular order.
1. Tune AI IDP
Tune AI IDP is a powerful tool that combines computer vision, ML, NLP and AI to extract, classify and validate information from all kinds of complex documents with structured and unstructured data. Some of its unique features are:
Powerful: It can effortlessly extract data from unstructured document formats, like invoices, forms, and contracts
Customizability: Tune AI IDP comes pre-programmed to handle a wide range of document types. You can also customize it to your specific needs
Integrations: It has clean APIs to plug and play with any existing enterprise software
Flexibility: Tune AI IDP can be deployed to the public cloud, private cloud or on-prem
Security: Out of the box, it has features for data encryption, GDPR/CCPA/HIPAA compliance. It is also SOC2 and ISO27001 certified
Reviews
G2 rating: 4.4/5
Pricing
Tune AI offers custom deployment, unlimited users, single sign-on and 24x7 support. Contact sales for pricing.
2. Google Cloud Document AI
Google Cloud Document AI uses ML models to automate data extraction from documents. It offers pre-trained models for various document types, such as invoices, receipts, and contracts.
The platform can classify documents, extract relevant data, and convert unstructured content into structured data. It is perfect for users of Google Cloud services who need something that integrates natively.
Reviews
G2 rating: 4.2/5
Pricing
Google Cloud Document AI has a slightly complex structure, with pricing breakdowns for digitization, extraction, and chunking. As a result, the cost can vary significantly depending on the workload and models you use. See this page for more details.
3. Rossum
Rossum’s IDP offerings focus on transactional documents, such as invoices, receipts, purchase orders and payments. Rossum uses deep learning models trained exclusively on millions of transactional documents to interpret and extract data. It is a great tool if you’re looking to automate invoice processing, compliance reporting, etc.
Reviews
G2 rating: 4.4/5
Pricing
Pricing for Rossum begins at $18,000 per year for the starter version, which includes unlimited seats, processing, 12 months of archive and API access. For more features, you can contact sales to get a quote.
4. IBM Watson Discovery
IBM Watson Discovery automates information discovery using natural language processing, machine learning, and data analytics. It can understand document structures, extract text from images or domain-specific entities and surface insights.
Reviews
G2 rating: 4.5/5
Pricing
IBM Watson Discovery pricing starts at $500 for 10,000 documents, pre-built connectors, table retrieval, reusable components and more. For more advanced features, contact IBM.
5. Amazon Textract
Amazon Textract is a fully-managed ML service from Amazon Web Services (AWS) that automatically extracts text, forms, and tables from documents. This can be scanned, printed or handwritten documents such as invoices, contracts, and receipts.
As part of the AWS suite, Textract is excellent if you already use their cloud services.
Reviews
G2 rating: 4.4/5
Pricing
You can get started on AWS Textract with the free tier for 3 months, which offers limited access to some APIs. For comprehensive pricing, check out their pricing calculator.
6. ABBYY
Abbyy is an AI and automation company that offers IDP products. Initially known for its OCR (Optical Character Recognition) technology, ABBYY has expanded its solutions to include intelligent document processing, AI, and machine learning technologies.
Within IDP, Abbyy Document AI offers products such as Vantage, FlexiCapture and FlexiCapture for invoices. They also offer OCR, process intelligence, and AI OCR development kits.
Reviews
G2 rating: 4.5/5
Pricing
Pricing for Abbyy products isn’t listed on their website. The best way to know more is to contact them directly.
7. Tungsten Automation (formerly Kofax)
Tungsten Automation is a leading provider of intelligent automation software. Approaching IDP from the angle of workflow automation, their product TotalAgility extracts data from documents, classifies it and integrates it into downstream processes.
In that endeavor, TotalAgility also includes a comprehensive document library with pre-built extraction models that support documents like bank statements, utility bills, IDs, air and sea waybills, etc.
Reviews
G2 rating: 4.3/5
Pricing
While the product pricing isn’t listed on the Tungsten website, you might get some reference from this G2 page, which lists the starter at $83 per staff member per month.
8. Automation Anywhere
Automation Anywhere is an established robotic process automation (RPA) company that has now integrated AI into its solutions. Their offerings include an open IDP platform that enables you to use Azure OpenAI Service and Anthropic on GCP or AWS.
Reviews
G2 rating: 4.5/5
Pricing
Here, too, the website doesn’t explicitly mention pricing. The best bet is to contact the sales team.
9. UiPath
UiPath is also from the same generation of RPA companies that are now incorporating AI capabilities into their systems. UiPath Document Understanding is the company’s IDP solution that extracts, interprets and processes data from PDFs, images, scanned documents and handwriting.
Reviews
G2 rating: 4.6/5
Pricing
UiPath Document Understanding automation developer license costs $420 a month per person. They also offer enterprise deals for which you need to contact sales.
10. HyperScience
The HyperScience platform performs intelligent document processing, data extraction, and automation. The platform promises 99.5% accuracy and 98% automation on any kind of document processing task. It also enables better control over model orchestration and management with a KPI-driven dashboard.
Reviews
G2 rating: 4.6/5
Pricing
On AWS, HyperScience pricing starts at $50,000 on a 12-month contract. They also offer 24-month and 36-month contracts. For more information, contact their sales.
Before you choose one over another, here are a few steps to simplify your consideration process.
Key features to look for in the best intelligent document processing software
If you’ve been paying attention so far, you already know that you must check for AI, NLP and technologies like that. We encourage you to go a bit deeper. Look for ways in which the intelligent document processing software is right for your needs. Here’s how.
Intelligent data extraction
Can it extract the kind of data you need from the documents you have?
While it might seem that all PDFs are the same, they are surely not. The content, layout, structure and data within each PDF can vary. This is especially true for unstructured or semi-structured data.
Look for software that can handle the documents you have. Running a pilot to test this is a great idea.
Self-learning
What happens once you’ve been onboarded and the vendor has gone?
The fundamental advantage of AI is that it is continuously learning. This has to happen with your IDP tool as well. As you ingest more documents and more types of data, the software needs to improve.
Look for the software’s continuous learning capabilities. Ask for case studies on improvement in accuracy or efficiency in the past.
Contextual understanding
Can the IDP tell the difference between an apple and a pear?
Within organizations, there are various similar documents. For instance, an employee offer letter might appear identical to an employment contract. Your IDP must be able to differentiate between the two in context.
Ask the vendor to demo instances where the software has contextual understanding. Give them two similar documents and ask for classification.
Industry expertise
Can the IDP tell the difference between a bank as in a financial institution and a river bank?
An extension of contextual understanding is industry jargon. The word ‘commit’ in software development has a specific meaning. So does ‘bleed’ within the context of a design. Intelligent document processing solutions must understand your industry and geography to process your documents accurately.
Ask for case studies or references of the vendor’s work in your industry. If they don’t have any, run a pilot to be sure.
Integration
Can the IDP work with your existing tech stack?
You shouldn’t have to buy a large set of new software just to make the IDP work. So, before you make any investment, ensure that the IDP software has two-way data transfer integrations with your existing systems, such as the ERP, customer relationship management (CRM), HR, finances, and other software to prevent manual data entry.
If the software has API capabilities, you’re mostly sorted.
Miscellany
What else do you need?
European organizations might need multi-language support. Healthcare enterprises might also need HIPAA compliance in addition to standard data security protocols. You might want to keep audit trails for all human-in-the-loop workflows, and you might need to set up document management.
In essence, there are things that are unique to you and your organization. Make a list and ask the vendor about them.
Based on these parameters, let’s examine some of the top intelligent document processing software available today.
How to choose the best intelligent document processing software for your business
While we’ve identified the top 10 for you, G2 lists 104 IDP platforms available today. Several automation and AI providers are adding IDP as a service or a solution. This means that you have a wide variety of options to choose from. On the other hand, choosing one can be a challenge.
Here is a framework we recommend you use to evaluate and shortlist IDP products for your organization.
Step 1: What documents?
Spend some time combing through all the kinds of documents you have. For a bank, this might be KYC documents. For an insurance provider, it could be a lot of handwritten forms. At a supply chain company, this would be purchase orders and invoices.
Think about the type and volume of documents you need processed.
Step 2: What features?
Do you need OCR for handwriting? Would security compliance be of primary importance to you? Is your domain too technical?
Think of all the features you need from your IDP.
Step 3: What purpose?
What is the purpose of intelligent document processing? For instance, one of our clients used data indexing to make research studies readily available to their customers. Another client used IDP to feed the generative AI engine to create future proposals.
What would you use this IDP solution for?
Step 4: What outcomes?
Consider the ROI you expect from buying IDP software and design your success metrics. For example, how much cost savings is worth the investment? What level of efficiency boost do you expect?
Step 5: What works?
Once you have that decision framework in your mind, evaluate products. Begin by shortlisting a few that make the most sense for your needs, systems and budget. Then, get a free trial or demo for at least three products before you finally choose.
Sometimes, the graphical user interface (GUI) or low-code interface can make the biggest difference to your non-tech teams, a feature that you never considered. So, try before you buy. A small pilot project is the best way to thoroughly evaluate the product and the company’s service and support.
Whether you have a clear requirement or are just shopping around, ping Tune AI’s experts for a chat. We help enterprise leaders find AI-based tech solutions to complex business problems.
Why do enterprises need IDP?
Intelligent document processing is a clear and straightforward way to capitalize on an organization's semi-structured and unstructured data. This has several significant benefits.
Faster processing: IDP can process hundreds of documents within seconds, which is impossible to do manually. This enables scalability without additional cost.
Accuracy: IDP can process documents 24/7 without the burdens of fatigue or distraction. Despite its scale, it maintains high levels of accuracy. When continuous learning protocols are programmed into the system, accuracy improves over time.
Cost efficiency: With its ability to process documents at scale, IDP dramatically reduces operational costs. One of our clients reduced the cost of indexing a document from $18 to ¢60 per hour.
Data enablement: Every enterprise has documents for its entire lifetime. Yet, all this historical data is stored away in the black hole of PDFs and emails. IDP frees this data and enables you to leverage it to gain a competitive advantage.
If you’re convinced to give that a go, let’s see how you can get started.
The world will create over 394 zettabytes by 2028, finds a study by Statista. While the data growth was already steep, the pandemic and the following rapid digitization gave it a powerful springboard.
This data forms the foundation of future analytics and artificial intelligence (AI) projects. 72% of organizations that McKinsey surveyed had adopted AI last year (a dramatic increase over the past few years), with cost decrease and revenue increase being the most expected outcomes.
However, the biggest challenges in adopting AI org-wide tend to be data-related.
Quality: Data quality is a grave concern. Studies show that 77% of IT decision-makers don’t trust their own data.
Actionability: Sometimes, even with data, organizations fail to create actionable insights in time. As a result, 76% of decision-makers report missing out on revenue opportunities.
Availability: This is a key problem — easily solvable. Most data, i.e., valuable business information, is stored in the form of documents. Both current and historical contracts, statements of procedures (SOPs), invoices, research reports, whitepapers, etc. are stored as PDFs or Word documents.
Extracting and using data from these documents can be a huge challenge. This is what some of the best intelligent document processing software are solving today.
What is Intelligent Document Processing?
Intelligent document processing (IDP) is a technology that extracts, classifies and processes data from documents. Some of its defining characteristics are:
Technology: Modern IDP uses machine learning (ML), natural language processing (NLP) and advanced AI to extract, classify and process data. This makes it faster, more efficient and more accurate.
Context: With AI and NLP, intelligent document processing goes beyond just identifying text. It helps make connections between data points and view them in context.
Data: IDP can effectively process structured, semi-structured and unstructured documents. A hand-written note to a 500-page annual report—no sweat! It can also run verification and validation processes to ensure accuracy.
Automation: IDP offers a great starting point for workflow automation. For instance, you can receive an invoice via email, process it using IDP, automatically enter the information into the enterprise resource planning (ERP) systems and make it available to the relevant stakeholder for approval.
How does IDP work?
The IDP workflow can vary depending on the nature of your data, volume, structure and use case. However, a typical document processing workflow would be as follows.
Document ingestion
You can manually upload documents to an IDP system, or it can automatically receive them from sources like email or cloud storage. Either way, the first step is to accept PDFs, Word documents, Spreadsheets, emails, scanned documents, or handwritten notes.
Data extraction
The IDP might use optical character recognition (OCR) if the document contains images or handwritten text. Otherwise, NLP and ML technologies would be great for precise data extraction and parsing.
Let’s say we’re extracting data from a contract. IDP is good for field extraction, such as the execution date, validity period, signatories, etc. It can also extract information from unstructured data, such as contract clauses.
Document classification
Based on the extracted data, IDP will classify the document according to your nomenclature as an invoice, a purchase order or a receipt. This information is then used for downstream processes. For instance, if a document is identified as an invoice, it is sent to the right stakeholder for approval.
Data validation
To ensure accuracy, IDP validates the data based on your set parameters, which could be your own rules or external sources. For instance, IDP can verify each invoice against the purchase order to ensure there is no over- or under-charge.
Downstream integration
Once the IDP process is almost over, it’s time to prepare the data for business applications. This could be your analytics platform, complex document workflows, or generative AI needs.
For instance, we used IDP and related AI technologies to create a comprehensive proposal creation tool for a Middle Eastern events company. See how it works.
10 Best Intelligent Document Processing Software in 2025
From IBM Watson to Google and Amazons of the world, dozens of intelligent document processing software are available. In this section, we narrow it down to the ten best, in no particular order.
1. Tune AI IDP
Tune AI IDP is a powerful tool that combines computer vision, ML, NLP and AI to extract, classify and validate information from all kinds of complex documents with structured and unstructured data. Some of its unique features are:
Powerful: It can effortlessly extract data from unstructured document formats, like invoices, forms, and contracts
Customizability: Tune AI IDP comes pre-programmed to handle a wide range of document types. You can also customize it to your specific needs
Integrations: It has clean APIs to plug and play with any existing enterprise software
Flexibility: Tune AI IDP can be deployed to the public cloud, private cloud or on-prem
Security: Out of the box, it has features for data encryption, GDPR/CCPA/HIPAA compliance. It is also SOC2 and ISO27001 certified
Reviews
G2 rating: 4.4/5
Pricing
Tune AI offers custom deployment, unlimited users, single sign-on and 24x7 support. Contact sales for pricing.
2. Google Cloud Document AI
Google Cloud Document AI uses ML models to automate data extraction from documents. It offers pre-trained models for various document types, such as invoices, receipts, and contracts.
The platform can classify documents, extract relevant data, and convert unstructured content into structured data. It is perfect for users of Google Cloud services who need something that integrates natively.
Reviews
G2 rating: 4.2/5
Pricing
Google Cloud Document AI has a slightly complex structure, with pricing breakdowns for digitization, extraction, and chunking. As a result, the cost can vary significantly depending on the workload and models you use. See this page for more details.
3. Rossum
Rossum’s IDP offerings focus on transactional documents, such as invoices, receipts, purchase orders and payments. Rossum uses deep learning models trained exclusively on millions of transactional documents to interpret and extract data. It is a great tool if you’re looking to automate invoice processing, compliance reporting, etc.
Reviews
G2 rating: 4.4/5
Pricing
Pricing for Rossum begins at $18,000 per year for the starter version, which includes unlimited seats, processing, 12 months of archive and API access. For more features, you can contact sales to get a quote.
4. IBM Watson Discovery
IBM Watson Discovery automates information discovery using natural language processing, machine learning, and data analytics. It can understand document structures, extract text from images or domain-specific entities and surface insights.
Reviews
G2 rating: 4.5/5
Pricing
IBM Watson Discovery pricing starts at $500 for 10,000 documents, pre-built connectors, table retrieval, reusable components and more. For more advanced features, contact IBM.
5. Amazon Textract
Amazon Textract is a fully-managed ML service from Amazon Web Services (AWS) that automatically extracts text, forms, and tables from documents. This can be scanned, printed or handwritten documents such as invoices, contracts, and receipts.
As part of the AWS suite, Textract is excellent if you already use their cloud services.
Reviews
G2 rating: 4.4/5
Pricing
You can get started on AWS Textract with the free tier for 3 months, which offers limited access to some APIs. For comprehensive pricing, check out their pricing calculator.
6. ABBYY
Abbyy is an AI and automation company that offers IDP products. Initially known for its OCR (Optical Character Recognition) technology, ABBYY has expanded its solutions to include intelligent document processing, AI, and machine learning technologies.
Within IDP, Abbyy Document AI offers products such as Vantage, FlexiCapture and FlexiCapture for invoices. They also offer OCR, process intelligence, and AI OCR development kits.
Reviews
G2 rating: 4.5/5
Pricing
Pricing for Abbyy products isn’t listed on their website. The best way to know more is to contact them directly.
7. Tungsten Automation (formerly Kofax)
Tungsten Automation is a leading provider of intelligent automation software. Approaching IDP from the angle of workflow automation, their product TotalAgility extracts data from documents, classifies it and integrates it into downstream processes.
In that endeavor, TotalAgility also includes a comprehensive document library with pre-built extraction models that support documents like bank statements, utility bills, IDs, air and sea waybills, etc.
Reviews
G2 rating: 4.3/5
Pricing
While the product pricing isn’t listed on the Tungsten website, you might get some reference from this G2 page, which lists the starter at $83 per staff member per month.
8. Automation Anywhere
Automation Anywhere is an established robotic process automation (RPA) company that has now integrated AI into its solutions. Their offerings include an open IDP platform that enables you to use Azure OpenAI Service and Anthropic on GCP or AWS.
Reviews
G2 rating: 4.5/5
Pricing
Here, too, the website doesn’t explicitly mention pricing. The best bet is to contact the sales team.
9. UiPath
UiPath is also from the same generation of RPA companies that are now incorporating AI capabilities into their systems. UiPath Document Understanding is the company’s IDP solution that extracts, interprets and processes data from PDFs, images, scanned documents and handwriting.
Reviews
G2 rating: 4.6/5
Pricing
UiPath Document Understanding automation developer license costs $420 a month per person. They also offer enterprise deals for which you need to contact sales.
10. HyperScience
The HyperScience platform performs intelligent document processing, data extraction, and automation. The platform promises 99.5% accuracy and 98% automation on any kind of document processing task. It also enables better control over model orchestration and management with a KPI-driven dashboard.
Reviews
G2 rating: 4.6/5
Pricing
On AWS, HyperScience pricing starts at $50,000 on a 12-month contract. They also offer 24-month and 36-month contracts. For more information, contact their sales.
Before you choose one over another, here are a few steps to simplify your consideration process.
Key features to look for in the best intelligent document processing software
If you’ve been paying attention so far, you already know that you must check for AI, NLP and technologies like that. We encourage you to go a bit deeper. Look for ways in which the intelligent document processing software is right for your needs. Here’s how.
Intelligent data extraction
Can it extract the kind of data you need from the documents you have?
While it might seem that all PDFs are the same, they are surely not. The content, layout, structure and data within each PDF can vary. This is especially true for unstructured or semi-structured data.
Look for software that can handle the documents you have. Running a pilot to test this is a great idea.
Self-learning
What happens once you’ve been onboarded and the vendor has gone?
The fundamental advantage of AI is that it is continuously learning. This has to happen with your IDP tool as well. As you ingest more documents and more types of data, the software needs to improve.
Look for the software’s continuous learning capabilities. Ask for case studies on improvement in accuracy or efficiency in the past.
Contextual understanding
Can the IDP tell the difference between an apple and a pear?
Within organizations, there are various similar documents. For instance, an employee offer letter might appear identical to an employment contract. Your IDP must be able to differentiate between the two in context.
Ask the vendor to demo instances where the software has contextual understanding. Give them two similar documents and ask for classification.
Industry expertise
Can the IDP tell the difference between a bank as in a financial institution and a river bank?
An extension of contextual understanding is industry jargon. The word ‘commit’ in software development has a specific meaning. So does ‘bleed’ within the context of a design. Intelligent document processing solutions must understand your industry and geography to process your documents accurately.
Ask for case studies or references of the vendor’s work in your industry. If they don’t have any, run a pilot to be sure.
Integration
Can the IDP work with your existing tech stack?
You shouldn’t have to buy a large set of new software just to make the IDP work. So, before you make any investment, ensure that the IDP software has two-way data transfer integrations with your existing systems, such as the ERP, customer relationship management (CRM), HR, finances, and other software to prevent manual data entry.
If the software has API capabilities, you’re mostly sorted.
Miscellany
What else do you need?
European organizations might need multi-language support. Healthcare enterprises might also need HIPAA compliance in addition to standard data security protocols. You might want to keep audit trails for all human-in-the-loop workflows, and you might need to set up document management.
In essence, there are things that are unique to you and your organization. Make a list and ask the vendor about them.
Based on these parameters, let’s examine some of the top intelligent document processing software available today.
How to choose the best intelligent document processing software for your business
While we’ve identified the top 10 for you, G2 lists 104 IDP platforms available today. Several automation and AI providers are adding IDP as a service or a solution. This means that you have a wide variety of options to choose from. On the other hand, choosing one can be a challenge.
Here is a framework we recommend you use to evaluate and shortlist IDP products for your organization.
Step 1: What documents?
Spend some time combing through all the kinds of documents you have. For a bank, this might be KYC documents. For an insurance provider, it could be a lot of handwritten forms. At a supply chain company, this would be purchase orders and invoices.
Think about the type and volume of documents you need processed.
Step 2: What features?
Do you need OCR for handwriting? Would security compliance be of primary importance to you? Is your domain too technical?
Think of all the features you need from your IDP.
Step 3: What purpose?
What is the purpose of intelligent document processing? For instance, one of our clients used data indexing to make research studies readily available to their customers. Another client used IDP to feed the generative AI engine to create future proposals.
What would you use this IDP solution for?
Step 4: What outcomes?
Consider the ROI you expect from buying IDP software and design your success metrics. For example, how much cost savings is worth the investment? What level of efficiency boost do you expect?
Step 5: What works?
Once you have that decision framework in your mind, evaluate products. Begin by shortlisting a few that make the most sense for your needs, systems and budget. Then, get a free trial or demo for at least three products before you finally choose.
Sometimes, the graphical user interface (GUI) or low-code interface can make the biggest difference to your non-tech teams, a feature that you never considered. So, try before you buy. A small pilot project is the best way to thoroughly evaluate the product and the company’s service and support.
Whether you have a clear requirement or are just shopping around, ping Tune AI’s experts for a chat. We help enterprise leaders find AI-based tech solutions to complex business problems.
Why do enterprises need IDP?
Intelligent document processing is a clear and straightforward way to capitalize on an organization's semi-structured and unstructured data. This has several significant benefits.
Faster processing: IDP can process hundreds of documents within seconds, which is impossible to do manually. This enables scalability without additional cost.
Accuracy: IDP can process documents 24/7 without the burdens of fatigue or distraction. Despite its scale, it maintains high levels of accuracy. When continuous learning protocols are programmed into the system, accuracy improves over time.
Cost efficiency: With its ability to process documents at scale, IDP dramatically reduces operational costs. One of our clients reduced the cost of indexing a document from $18 to ¢60 per hour.
Data enablement: Every enterprise has documents for its entire lifetime. Yet, all this historical data is stored away in the black hole of PDFs and emails. IDP frees this data and enables you to leverage it to gain a competitive advantage.
If you’re convinced to give that a go, let’s see how you can get started.
The world will create over 394 zettabytes by 2028, finds a study by Statista. While the data growth was already steep, the pandemic and the following rapid digitization gave it a powerful springboard.
This data forms the foundation of future analytics and artificial intelligence (AI) projects. 72% of organizations that McKinsey surveyed had adopted AI last year (a dramatic increase over the past few years), with cost decrease and revenue increase being the most expected outcomes.
However, the biggest challenges in adopting AI org-wide tend to be data-related.
Quality: Data quality is a grave concern. Studies show that 77% of IT decision-makers don’t trust their own data.
Actionability: Sometimes, even with data, organizations fail to create actionable insights in time. As a result, 76% of decision-makers report missing out on revenue opportunities.
Availability: This is a key problem — easily solvable. Most data, i.e., valuable business information, is stored in the form of documents. Both current and historical contracts, statements of procedures (SOPs), invoices, research reports, whitepapers, etc. are stored as PDFs or Word documents.
Extracting and using data from these documents can be a huge challenge. This is what some of the best intelligent document processing software are solving today.
What is Intelligent Document Processing?
Intelligent document processing (IDP) is a technology that extracts, classifies and processes data from documents. Some of its defining characteristics are:
Technology: Modern IDP uses machine learning (ML), natural language processing (NLP) and advanced AI to extract, classify and process data. This makes it faster, more efficient and more accurate.
Context: With AI and NLP, intelligent document processing goes beyond just identifying text. It helps make connections between data points and view them in context.
Data: IDP can effectively process structured, semi-structured and unstructured documents. A hand-written note to a 500-page annual report—no sweat! It can also run verification and validation processes to ensure accuracy.
Automation: IDP offers a great starting point for workflow automation. For instance, you can receive an invoice via email, process it using IDP, automatically enter the information into the enterprise resource planning (ERP) systems and make it available to the relevant stakeholder for approval.
How does IDP work?
The IDP workflow can vary depending on the nature of your data, volume, structure and use case. However, a typical document processing workflow would be as follows.
Document ingestion
You can manually upload documents to an IDP system, or it can automatically receive them from sources like email or cloud storage. Either way, the first step is to accept PDFs, Word documents, Spreadsheets, emails, scanned documents, or handwritten notes.
Data extraction
The IDP might use optical character recognition (OCR) if the document contains images or handwritten text. Otherwise, NLP and ML technologies would be great for precise data extraction and parsing.
Let’s say we’re extracting data from a contract. IDP is good for field extraction, such as the execution date, validity period, signatories, etc. It can also extract information from unstructured data, such as contract clauses.
Document classification
Based on the extracted data, IDP will classify the document according to your nomenclature as an invoice, a purchase order or a receipt. This information is then used for downstream processes. For instance, if a document is identified as an invoice, it is sent to the right stakeholder for approval.
Data validation
To ensure accuracy, IDP validates the data based on your set parameters, which could be your own rules or external sources. For instance, IDP can verify each invoice against the purchase order to ensure there is no over- or under-charge.
Downstream integration
Once the IDP process is almost over, it’s time to prepare the data for business applications. This could be your analytics platform, complex document workflows, or generative AI needs.
For instance, we used IDP and related AI technologies to create a comprehensive proposal creation tool for a Middle Eastern events company. See how it works.
10 Best Intelligent Document Processing Software in 2025
From IBM Watson to Google and Amazons of the world, dozens of intelligent document processing software are available. In this section, we narrow it down to the ten best, in no particular order.
1. Tune AI IDP
Tune AI IDP is a powerful tool that combines computer vision, ML, NLP and AI to extract, classify and validate information from all kinds of complex documents with structured and unstructured data. Some of its unique features are:
Powerful: It can effortlessly extract data from unstructured document formats, like invoices, forms, and contracts
Customizability: Tune AI IDP comes pre-programmed to handle a wide range of document types. You can also customize it to your specific needs
Integrations: It has clean APIs to plug and play with any existing enterprise software
Flexibility: Tune AI IDP can be deployed to the public cloud, private cloud or on-prem
Security: Out of the box, it has features for data encryption, GDPR/CCPA/HIPAA compliance. It is also SOC2 and ISO27001 certified
Reviews
G2 rating: 4.4/5
Pricing
Tune AI offers custom deployment, unlimited users, single sign-on and 24x7 support. Contact sales for pricing.
2. Google Cloud Document AI
Google Cloud Document AI uses ML models to automate data extraction from documents. It offers pre-trained models for various document types, such as invoices, receipts, and contracts.
The platform can classify documents, extract relevant data, and convert unstructured content into structured data. It is perfect for users of Google Cloud services who need something that integrates natively.
Reviews
G2 rating: 4.2/5
Pricing
Google Cloud Document AI has a slightly complex structure, with pricing breakdowns for digitization, extraction, and chunking. As a result, the cost can vary significantly depending on the workload and models you use. See this page for more details.
3. Rossum
Rossum’s IDP offerings focus on transactional documents, such as invoices, receipts, purchase orders and payments. Rossum uses deep learning models trained exclusively on millions of transactional documents to interpret and extract data. It is a great tool if you’re looking to automate invoice processing, compliance reporting, etc.
Reviews
G2 rating: 4.4/5
Pricing
Pricing for Rossum begins at $18,000 per year for the starter version, which includes unlimited seats, processing, 12 months of archive and API access. For more features, you can contact sales to get a quote.
4. IBM Watson Discovery
IBM Watson Discovery automates information discovery using natural language processing, machine learning, and data analytics. It can understand document structures, extract text from images or domain-specific entities and surface insights.
Reviews
G2 rating: 4.5/5
Pricing
IBM Watson Discovery pricing starts at $500 for 10,000 documents, pre-built connectors, table retrieval, reusable components and more. For more advanced features, contact IBM.
5. Amazon Textract
Amazon Textract is a fully-managed ML service from Amazon Web Services (AWS) that automatically extracts text, forms, and tables from documents. This can be scanned, printed or handwritten documents such as invoices, contracts, and receipts.
As part of the AWS suite, Textract is excellent if you already use their cloud services.
Reviews
G2 rating: 4.4/5
Pricing
You can get started on AWS Textract with the free tier for 3 months, which offers limited access to some APIs. For comprehensive pricing, check out their pricing calculator.
6. ABBYY
Abbyy is an AI and automation company that offers IDP products. Initially known for its OCR (Optical Character Recognition) technology, ABBYY has expanded its solutions to include intelligent document processing, AI, and machine learning technologies.
Within IDP, Abbyy Document AI offers products such as Vantage, FlexiCapture and FlexiCapture for invoices. They also offer OCR, process intelligence, and AI OCR development kits.
Reviews
G2 rating: 4.5/5
Pricing
Pricing for Abbyy products isn’t listed on their website. The best way to know more is to contact them directly.
7. Tungsten Automation (formerly Kofax)
Tungsten Automation is a leading provider of intelligent automation software. Approaching IDP from the angle of workflow automation, their product TotalAgility extracts data from documents, classifies it and integrates it into downstream processes.
In that endeavor, TotalAgility also includes a comprehensive document library with pre-built extraction models that support documents like bank statements, utility bills, IDs, air and sea waybills, etc.
Reviews
G2 rating: 4.3/5
Pricing
While the product pricing isn’t listed on the Tungsten website, you might get some reference from this G2 page, which lists the starter at $83 per staff member per month.
8. Automation Anywhere
Automation Anywhere is an established robotic process automation (RPA) company that has now integrated AI into its solutions. Their offerings include an open IDP platform that enables you to use Azure OpenAI Service and Anthropic on GCP or AWS.
Reviews
G2 rating: 4.5/5
Pricing
Here, too, the website doesn’t explicitly mention pricing. The best bet is to contact the sales team.
9. UiPath
UiPath is also from the same generation of RPA companies that are now incorporating AI capabilities into their systems. UiPath Document Understanding is the company’s IDP solution that extracts, interprets and processes data from PDFs, images, scanned documents and handwriting.
Reviews
G2 rating: 4.6/5
Pricing
UiPath Document Understanding automation developer license costs $420 a month per person. They also offer enterprise deals for which you need to contact sales.
10. HyperScience
The HyperScience platform performs intelligent document processing, data extraction, and automation. The platform promises 99.5% accuracy and 98% automation on any kind of document processing task. It also enables better control over model orchestration and management with a KPI-driven dashboard.
Reviews
G2 rating: 4.6/5
Pricing
On AWS, HyperScience pricing starts at $50,000 on a 12-month contract. They also offer 24-month and 36-month contracts. For more information, contact their sales.
Before you choose one over another, here are a few steps to simplify your consideration process.
Key features to look for in the best intelligent document processing software
If you’ve been paying attention so far, you already know that you must check for AI, NLP and technologies like that. We encourage you to go a bit deeper. Look for ways in which the intelligent document processing software is right for your needs. Here’s how.
Intelligent data extraction
Can it extract the kind of data you need from the documents you have?
While it might seem that all PDFs are the same, they are surely not. The content, layout, structure and data within each PDF can vary. This is especially true for unstructured or semi-structured data.
Look for software that can handle the documents you have. Running a pilot to test this is a great idea.
Self-learning
What happens once you’ve been onboarded and the vendor has gone?
The fundamental advantage of AI is that it is continuously learning. This has to happen with your IDP tool as well. As you ingest more documents and more types of data, the software needs to improve.
Look for the software’s continuous learning capabilities. Ask for case studies on improvement in accuracy or efficiency in the past.
Contextual understanding
Can the IDP tell the difference between an apple and a pear?
Within organizations, there are various similar documents. For instance, an employee offer letter might appear identical to an employment contract. Your IDP must be able to differentiate between the two in context.
Ask the vendor to demo instances where the software has contextual understanding. Give them two similar documents and ask for classification.
Industry expertise
Can the IDP tell the difference between a bank as in a financial institution and a river bank?
An extension of contextual understanding is industry jargon. The word ‘commit’ in software development has a specific meaning. So does ‘bleed’ within the context of a design. Intelligent document processing solutions must understand your industry and geography to process your documents accurately.
Ask for case studies or references of the vendor’s work in your industry. If they don’t have any, run a pilot to be sure.
Integration
Can the IDP work with your existing tech stack?
You shouldn’t have to buy a large set of new software just to make the IDP work. So, before you make any investment, ensure that the IDP software has two-way data transfer integrations with your existing systems, such as the ERP, customer relationship management (CRM), HR, finances, and other software to prevent manual data entry.
If the software has API capabilities, you’re mostly sorted.
Miscellany
What else do you need?
European organizations might need multi-language support. Healthcare enterprises might also need HIPAA compliance in addition to standard data security protocols. You might want to keep audit trails for all human-in-the-loop workflows, and you might need to set up document management.
In essence, there are things that are unique to you and your organization. Make a list and ask the vendor about them.
Based on these parameters, let’s examine some of the top intelligent document processing software available today.
How to choose the best intelligent document processing software for your business
While we’ve identified the top 10 for you, G2 lists 104 IDP platforms available today. Several automation and AI providers are adding IDP as a service or a solution. This means that you have a wide variety of options to choose from. On the other hand, choosing one can be a challenge.
Here is a framework we recommend you use to evaluate and shortlist IDP products for your organization.
Step 1: What documents?
Spend some time combing through all the kinds of documents you have. For a bank, this might be KYC documents. For an insurance provider, it could be a lot of handwritten forms. At a supply chain company, this would be purchase orders and invoices.
Think about the type and volume of documents you need processed.
Step 2: What features?
Do you need OCR for handwriting? Would security compliance be of primary importance to you? Is your domain too technical?
Think of all the features you need from your IDP.
Step 3: What purpose?
What is the purpose of intelligent document processing? For instance, one of our clients used data indexing to make research studies readily available to their customers. Another client used IDP to feed the generative AI engine to create future proposals.
What would you use this IDP solution for?
Step 4: What outcomes?
Consider the ROI you expect from buying IDP software and design your success metrics. For example, how much cost savings is worth the investment? What level of efficiency boost do you expect?
Step 5: What works?
Once you have that decision framework in your mind, evaluate products. Begin by shortlisting a few that make the most sense for your needs, systems and budget. Then, get a free trial or demo for at least three products before you finally choose.
Sometimes, the graphical user interface (GUI) or low-code interface can make the biggest difference to your non-tech teams, a feature that you never considered. So, try before you buy. A small pilot project is the best way to thoroughly evaluate the product and the company’s service and support.
Whether you have a clear requirement or are just shopping around, ping Tune AI’s experts for a chat. We help enterprise leaders find AI-based tech solutions to complex business problems.
Why do enterprises need IDP?
Intelligent document processing is a clear and straightforward way to capitalize on an organization's semi-structured and unstructured data. This has several significant benefits.
Faster processing: IDP can process hundreds of documents within seconds, which is impossible to do manually. This enables scalability without additional cost.
Accuracy: IDP can process documents 24/7 without the burdens of fatigue or distraction. Despite its scale, it maintains high levels of accuracy. When continuous learning protocols are programmed into the system, accuracy improves over time.
Cost efficiency: With its ability to process documents at scale, IDP dramatically reduces operational costs. One of our clients reduced the cost of indexing a document from $18 to ¢60 per hour.
Data enablement: Every enterprise has documents for its entire lifetime. Yet, all this historical data is stored away in the black hole of PDFs and emails. IDP frees this data and enables you to leverage it to gain a competitive advantage.
If you’re convinced to give that a go, let’s see how you can get started.
Written by
Anshuman Pandey
Co-founder and CEO
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