Document Capture Software

Most online and offline documents can be categorized as semi-structured data. They are not immediately processable by machines. Initially, template based software attempted to bridge this gap and allow companies to automatically extract data from documents. However, templates enable limited levels of automation and are hard to maintain. Since the last few years, vendors have built machine learning models using millions of sample documents. These models are able to automatically extract data from documents with a high accuracy rate

To be categorized as a document capture software, a product must be able to

  • automatically extract data out of a specific type (e.g. invoice) or various different types of documents.
  • provide a confidence for the extracted data so users can decide to auto-process or manually validate the software output
  • provide a User Interface (UI) for manually validating and correcting extracted data

How are vendors scored in this category?

Data extraction performance is a key metric for these solutions. We have run a benchmark on the free trial/community edition software. In addition, we asked our clients for similar benchmarks.

  • The vertical (Y) axis is a normalized measure of correctly extracted fields per document.
  • The horizontal (X) axis is a normalized measure of extraction accuracy.
Innovators Specialists Leaders Challengers Market Presence Momentum

Compare Document Capture Software
Results: 21

AIMultiple is data driven. Evaluate 21 products based on comprehensive, transparent and objective AIMultiple scores. For any of our scores, click the icon to learn how it is calculated based on objective data.

Sort by:
top5 , top10
= 1 review
= 20 employees
= 100,000 visitors

Hypatos offers deep learning skills to automate document-based back office tasks to improve work and make organisations more efficient. The largest consumers of financial data including global manufacturing and retail leaders, the Big 4 and other Fortune 500 and technology companies rely on us. Hypatos outperforms industry standards by >10x and focuses on automation beyond data capture. Hypatos provides an enterprise grade automation module with on-prem, cloud deployment options and integrations to enterprise systems.

top5 , top10
= 1 review
= 20 employees
= 100,000 visitors

top5 , top10
= 1 review
= 20 employees
= 100,000 visitors

top5 , top10
= 1 review
= 20 employees
= 100,000 visitors

top5 , top10
= 1 review
= 20 employees
= 100,000 visitors


Searches with brand name

These are the number of queries on search engines which include the brand name of the product. Compared to other product based solutions, document capture software is less concentrated in terms of top 3 companies' share of search queries. Top 3 companies receive 76% (2% less than average) of search queries in this area.

Web Traffic

Document capture software is a less concentrated than average solution category in terms of web traffic. Top 3 companies receive 69% (8% less than average solution category) of the online visitors on document capture software company websites.


Document capture software is highly concentrated than average in terms of user reviews. Top 3 companies receive 80% (22% more than average solution category) of the reviews on document capture software company websites. Product satisfaction tends to be slightly higher for more popular document capture software products. Average rating for top 3 products is 4.4 vs 4.3 for average document capture software product review.

Leaders Average Review Score Number of Reviews


Number of Employees

Median number of employees that provide document capture software is 58 which is 5 less than the median number of employees for the average solution category.

In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 16 companies (31 less than average solution category) with >10 employees are offering document capture software. Top 3 products are developed by companies with a total of 501-1,000 employees. However, 2 of these top 3 companies have multiple products so only a portion of this workforce is actually working on these top 3 products.

Amazon Web Services (AWS)

Learn More About Document Capture Software

What is document capture software?

Document capture software is an application that can automate the process of scanning paper documents or importing electronic documents for capturing the relevant information for further operations. These tools can collect unstructured forms of data, turn them into actionable information to be used in specific business functions or intents, and store them in databases for future reference.

How does it work?

Here is how document capture software works:

  • Documents are imported to document capture software.
  • The text is transformed into a readable format by deskewing and cleaning the image and improving image quality.
  • The software reads and captures unstructured data that passes predefined tolerance levels. If a document fails, it is sent for manual verification.
  • The collected unstructured data is converted to structured data by leveraging machine learning algorithms. The data is classified and appropriately validated in this step.
  • The data is transferred to the database for further processes.
  • If needed, the captured data can be processed for further tasks like document generation. You can read more about this in our document automation guide.

Which documents to capture?

Most common business documents include:

    Finance Operations
    • Procure-to-Pay
      • Offers
      • Invoices
      • Bill of lading: Necessary for matching goods received and invoices received in IRGRC (invoices received goods received clearing)
    • Order-to-Cash
      • Order forms
    HR Operations
    • Travel and expense management
      • Receipts
      • Invoices for individual spending
      • Tickets
    • CV Screening
      • CVs
    Legal Processes
    • Tax Statements
    • Legal Contracts
    • Prescriptions
    • Medical records
    Other Processes
    • Loan Application forms
    • Payslips
    • W2 forms

What are the main benefits of document capture tools?

The main benefits include:

  • Faster processes
  • Reduced costs
  • Reduced errors
  • Improved customer satisfaction
  • Improved security
  • Better decision making

To read more about how document capture tools achieve these benefits, feel free to read the related section of our in-depth document capture guide.

What are typical document capture use cases?

Typical document capture use cases include:

  • Accounts Payable: In these processes, document capture tools can provide invoice automation and process invoice data like line item information, delivery dates, shipping costs, and discounts. To learn more about accounts payable automation, you can also read our in-depth guide.
  • Order Management: Document capture tools can handle a wide range of documents that order management departments use to carry out their activities. To learn more about order management, feel free to read our related article.
  • Auditing: To identify risks in real-time and identify compliance issues, companies can benefit from document capture tools.
  • Loan Applications: The software can provide automated examinations of payslips and bank statements of applicants to accelerate the processes.
  • Analytics & BI: Data stored in forms is not always captured by the business as manual data capture is prohibitively expensive. Analytics units can process historical documents, capture data and run analyses to gain insights on how the business is progressing over time and identify improvement opportunities.

For more use cases, you can visit the related section of our in-depth document capture guide.

Purchase guide: What is important to consider while choosing the right document capture solution?

The ideal document capture tool for your company should:

  • recognize a well-scanned document accurately and extract the data in structured data format
  • be robust in cases of inadequate image quality and handwriting,
  • be accurate in estimating its own accuracy.

Extracted data needs to come with confidence scores to enable STP. If scores are not accurate, you may auto process documents that need human in the loop resulting in mistakes or you may require human operators to look at documents that are already extracted correctly

Considering these factors, you should first decide on what kind of document capture tool you need. For example, some vendors can provide better results in handwritten documents while they might not be accurate enough in formatting. Then, you should create a shortlist of possible vendors based on your requirements. Besides software performance, you might also want to consider the following items to make a final decision:

  • Accuracy level of the solution evaluated based on a statistically significant, representative sample set from your documents
  • User-friendly interface
  • Cost and timeline of implementation
  • Ability to integrate with your current ECM (Enterprise Content Management) tools so you can implement the new solution without changing existing workflows. This is only relevant for companies that already rolled out and are satisfied with the performance of their ECM system
  • Vendor experience
  • Vendor support
  • Conforming to other requirements such as data privacy, security, auditability, scalability, monitoring/alerting capabilities etc.

What technologies do document capture tools leverage?

Document capture software leverages the following technologies to perform tasks:

  • Optical Character Recognition (OCR): Document capture tools need to recognize text in every document. To do that, OCR plays a critical role by benefiting from computer vision to text recognition and deep learning algorithms for identifying each character. You can read more about OCR in our in-depth guide.
  • Neural network algorithms: To classify the unstructured data that is captured from scanned documents, neural network algorithms are used. By continuously being used, document capture tools can increase their accuracy levels in time. These algorithms are used in OCR for precise character recognition, as well. With the rise of deep learning, deep learning architectures are commonly used in neural networks in this field.
  • Natural Language Processing (NLP) Algorithms: As part of entity recognition, NLP is used to process and understand natural language text and extract captured information within the documents.
  • Word Embedding: By clustering similar words together, document capture tools can classify different types of documents fastly and with reduced errors.

How will document capture tools evolve in the future?

While document capture tools manage a critical part of business operations by handling repetitive, low-skill tasks, the main challenge about these tools is to capture relevant data accurately. While document capture tools can work with high accuracy with typed documents today, they still require human in the loop to avoid any recognition errors.

Yet, active research on machine learning continues to overcome this challenge. Today, this research is mostly focused on handwritten documents and cursive texts, as they are harder to identify. In the future, we expect document capture tools to handle these tasks successfully and without any human intervention. You can read more about this in our current state of OCR technology article.

Besides improving data capture processes, converting unstructured data to structured data is still a developing process. While this process requires AI and machine learning algorithms to structure data accurately, many tools still require human intervention to avoid errors today. Both tech giants like Amazon and startups like Hypatos are investing in machine learning to improve the assignment of text to data entities and therefore converting images more accurately into structured data. As a result, we expect more accurate processes in the future's document capture tools.