Unlock hidden insights from unstructured text data.
Starts from $1Flat Rate Per Job, also offers free forever plan
Overview
Pricing
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Amazon Comprehend is a Natural Language Processing (NLP) Software that extracts structured information from text. It helps developers build applications that make sense of large volumes of unstructured data, such as text documents and PDFs. With Amazon Comprehend, user can use natural language processing (NLP) to automatically identify entities, topics, and sentiments in text data. This enables new types of applications relying on a deeper understanding of data.
Starts from $1Flat Rate Per Job
Individuals
Large Enterprises
Medium Business
Small Business
SaaS/Web/Cloud
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Amazon Comprehend was reviewed internally using user feedback, in-house testing, and market research to assess its performance, reliability, and user experience. Learn how we review products and our evaluation process.
Free Trial
Not available
Amazon Comprehend Pricing
Starts from $1Flat Rate Per Job
Offers free forever plan
Pricing Model
Freemium
Paid Plans (Quotation Based )
Pricing Plans
Free Tier
For each of the 7 APIs (Key Phrase Extraction, Sentiment Analysis, Entity Recognition, Language Detection, Syntax Analysis, Custom Entities, and Custom Classification) per month.
Key Phrase Extraction
Sentiment Analysis
Entity Recognition
Language Detection
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Topic Modeling
$1
Flat Rate Per Job
For the first 100 MB: $1 Flat Rate Per Job
For every MB above 100 MB: $0.004 Per MB
Key Phrase Extraction
Sentiment Analysis
Entity Recognition
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Custom Comprehend
For asynchronous classification and entity recognition: $0.0005 Per Unit
For synchronous classification: $0.0005 Per Second
For Model Training: $3 Per Hour
For Custom Model Management: $0.50
Key Phrase Extraction
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Screenshots of the Amazon Comprehend Pricing Page
Disclaimer: Pricing information for Amazon Comprehend is provided by the software vendor or sourced from publicly accessible materials. Final cost negotiations and purchasing must be handled directly with the seller. For the latest information on pricing, visit website. Pricing information was last updated on .
User Review
GP
Ganesh P
07/31/19
NLP Text analysis using Amazon Comprehend
What do you like best? Amazons comprehend is a better option when you need a Pre trained NLP text analysis AI engine, it gives you a lot's of ...
Read more
UI
User in Education Management
01/30/19
Amazon Comprehend is Awesome!
What do you like best? The portfolio of services offered under Amazon Comprehend--from Medical to Natural Language Processing is one of the best ...
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UI
User in Consumer Goods
01/22/19
Review
What do you like best? I really liked the simple api for nodejs. Additionally, the integration of python api is also very easy to use. What do ...
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AI
Administrator in Apparel & Fashion
01/22/19
Great automatic learning tool
What do you like best? What I like about it is it’s a great tool is that it can be intergrated with other great software What do you dislike? ...
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Roche
LexisNexis
Fred Hutchinson
Vibes
FINRA
Customer Service
Online
Location
Seattle, Washington
Stuck on something? We're here to help with all the questions and answers in one place.
Some top alternatives to Amazon Comprehend includes teX-ai, Tinq.ai, Amazon Lex, yellow.ai and SyTrue.
Yes, Amazon Comprehend provides API.
No, Amazon Comprehend doesn't provide mobile app.
Amazon Comprehend is located in Seattle, Washington
Amazon Comprehend offers Freemium, Quotation Based pricing models
The starting price of Amazon Comprehend is $1Flat Rate Per Job
This software is researched and edited by
Rajat Gupta is the founder of Spotsaas, where he reviews and compares software tools that help businesses work smarter. Over the past two years, he has analyzed thousands of products across CRM, HR, AI, and finance — combining real-world research with a strong foundation in commerce and the CFA program. He's especially curious about AI, automation, and the future of work tech. Outside of SpotSaaS, you'll find him on a badminton court or tracking the stock market.
Researched by Rajat Gupta
