+
+

Related Products

  • Google AI Studio
    30 Ratings
    Visit Website
  • Google Cloud Speech-to-Text
    366 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    985 Ratings
    Visit Website
  • Google Cloud Platform
    61,012 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • kama.ai
    9 Ratings
    Visit Website
  • ClickLearn
    67 Ratings
    Visit Website
  • XpertCoding
    42 Ratings
    Visit Website

About

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. No machine learning experience required. There is a treasure trove of potential sitting in your unstructured data. Customer emails, support tickets, product reviews, social media, even advertising copy represents insights into customer sentiment that can be put to work for your business. The question is how to get at it? As it turns out, Machine learning is particularly good at accurately identifying specific items of interest inside vast swathes of text (such as finding company names in analyst reports), and can learn the sentiment hidden inside language (identifying negative reviews, or positive customer interactions with customer service agents), at almost limitless scale. Amazon Comprehend uses machine learning to help you uncover the insights and relationships in your unstructured data.

About

Mine insights in unstructured text using NLP—no machine-learning expertise required—using text analytics, a collection of features from Cognitive Service for Language. Gain a deeper understanding of customer opinions with sentiment analysis. Identify key phrases and entities such as people, places, and organizations to understand common topics and trends. Classify medical terminology using domain-specific, pretrained models. Evaluate text in a wide range of languages. Identify important concepts in text, including key phrases and named entities such as people, events, and organizations. Examine what customers are saying about your brand and analyze sentiments around specific topics through opinion mining. Extract insights from unstructured clinical documents such as doctors' notes, electronic health records, and patient intake forms using text analytics for health.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Organizations that want a powerful solution that lets them discover insights and relationships in text

Audience

Businesses looking for an AI service to uncover insights like sentiment, entities, and key phrases in unstructured text

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 1.0 / 5
ease 4.0 / 5
features 3.0 / 5
design 3.0 / 5
support 3.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • Very easy to setup and train models. Endpoint were very easy to configure and get running. Built for developer ease of use.

Cons

  • The cost is outrageous. Most AWS products are reasonable in terms of cost especially their AI products. This one is so prohibitive we will be moving our infrastructure to another system. The costly part is their endpoints with cost as long as they are running. Our system needs to have 24/7 availability and was doing document analysis on 1000s of emails and documents per day. The cost for a single endpoint was ~$3400 USD. Very little traffic was being used by that endpoint at the time. AWS charged for total time not token based usage. Which made the costs skyrocket. Please avoid to save yourself money unless you can standup the endpoints and take them down frequently.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/comprehend/

Company Information

Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

Alternatives

Alternatives

Semantria

Semantria

Lexalytics

Categories

Categories

Natural Language Processing Features

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Integrations

AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon Quick Suite
Amazon S3
Amazon Web Services (AWS)
Axon Ivy
Azure Marketplace
Camunda
Datasaur
FormKiQ
Mantium
PubNub
Qlik Staige
Quickwork
TAS Insight Engine
Unremot
iText
n8n

Integrations

AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon Quick Suite
Amazon S3
Amazon Web Services (AWS)
Axon Ivy
Azure Marketplace
Camunda
Datasaur
FormKiQ
Mantium
PubNub
Qlik Staige
Quickwork
TAS Insight Engine
Unremot
iText
n8n
Claim Amazon Comprehend and update features and information
Claim Amazon Comprehend and update features and information
Claim Azure Text Analytics and update features and information
Claim Azure Text Analytics and update features and information