Amazon Web Services (AWS) Reviews, Ratings & Features 2026 | Gartner Peer Insights

Gartner defines intelligent document processing (IDP) solutions as specialized data integration tools that enable automated extraction of data from multiple formats and various layouts of document content. IDP solutions ingest data for dependent applications and workflows and can be provided as a software product and/or as a service. Organizations receive and process documents in multiple formats to enable activities such as onboarding new suppliers, receiving applications for loans or insurance claims. This results in large volumes of documents, the content of which is designed for human comprehension rather than machine processing. Extracting data from content is essential for document processing and the automated activities this supports. IDP solutions fulfill this role, augmented by and potentially replacing people. Documents are received in physical form, typically paper, which must be scanned for digitization, or in digital form, such as emails and PDFs. The content of these documents has varying layouts, ranging from structured formats, such as tabular or outline (e.g., list or hierarchy of headings) or invoices or contracts, to unstructured formats (i.e., free-flowing, such as an email). Layouts that fall between structured and unstructured, or mixing the two, are often referred to as semistructured.

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Find the top Intelligent Document Processing Solutions with Gartner. Compare and filter by verified product reviews and choose the software that’s right for your organization.

Intelligent Document Processing Solutions (Transitioning to Intelligent Document Processing)

Amazon Comprehend

Amazon Textract

Amazon Web Services (AWS)

Marketing Manager

We process social conversation data and help flag negative sentiment messages for escalation for our users along with language sorting for the same data. Comprehension has reduced the need for manual triaging to a large extent. 

<50M USD

50M - 250M USD

500M - 1B USD

3B - 10B USD

250M - 500M USD

10B - 30B USD

30B + USD

1B - 3B USD

Gov't/PS/ED <5,000 Employees

Gov't/PS/ED 5,000 - 50,000 Employees

ASSOCIATE PROFESSOR

The main reason for my average overall experience is that a single document analysis is limited to 5,000 bytes. This means that I have to break up larger documents. On the other hand it is good to have more options when it comes to large language models.

Data and Analytics Manager

Our experience with Amazon Comprehend has been broadly positive, with some clear caveats once you push into anything beyond the standard use cases. We picked it up because we needed NLP capabilities (entity extraction, sentiment, key phrase detection) without standing up a full ML team to train and host models, and on that front it has delivered. The biggest practical advantage is how little setup is involved. The pre-built models for English text are good enough for most general-purpose work, and being able to call them through a simple API meant we could fold NLP into existing pipelines within days rather than weeks. The pay-per-use pricing also made it easy to start small and scale once we'd validated that the output was good enough for the use case. The honest limitations: accuracy drops off when the text is heavy on technical or industry-specific vocabulary, and we've had to layer post-processing on top to catch the cases where the model misses or misclassifies. Language coverage is also narrower than we'd like, particularly for regional Indian languages beyond Hindi, which has been a real constraint for some of our work.

Google

Microsoft

Evolution AI

ABBYY

OpenText

Auditoria.AI

Docbyte

Automation Anywhere

Snowflake

Applica

Addepto

Other...

Appian

GTT Data (Antworks)

UiPath

Cinnamon AI

Docketry

ServiceNow

Golem.ai

DocDigitizer

Xtracta

Alkymi

Hamta

DataSnipper

Amantra

Docugami

Hyland

Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.

Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. The ultimate benefit of cloud computing, and AWS, is the ability to leverage a new business model and turn capital infrastructure expenses into variable costs. Businesses no longer need to plan and procure servers and other IT resources weeks or months in advance. Using AWS, businesses can take advantage of Amazon's expertise and economies of scale to access resources when their business needs them, delivering results faster and at a lower cost. Today, Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. With data center locations in the U.S., Europe, Singapore, and Japan, customers across all industries are taking advantage of our low cost, elastic, open and flexible, secure platform.

Reviews

Ratings Overview

Overall experience with

Favorable Review

Batch Processing And Custom Models Challenged By Limited Language Support And Pricing

Critical Review

Document Size Restriction Limits In-Depth Analysis to Only 5,000 Bytes

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