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Description
Amazon Comprehend is an innovative natural language processing (NLP) tool that employs machine learning techniques to extract valuable insights and connections from text without requiring any prior machine learning knowledge.
Your unstructured data holds a wealth of possibilities, with sources like customer emails, support tickets, product reviews, social media posts, and even advertising content offering critical insights into customer sentiments that can drive your business forward. The challenge lies in how to effectively tap into this rich resource. Fortunately, machine learning excels at pinpointing specific items of interest within extensive text datasets—such as identifying company names in analyst reports—and can also discern the underlying sentiments in language, whether that involves recognizing negative reviews or acknowledging positive interactions with customer service representatives, all at an impressive scale.
By leveraging Amazon Comprehend, you can harness the power of machine learning to reveal the insights and relationships embedded within your unstructured data, empowering your organization to make more informed decisions.
Description
Explore the capabilities of text analytics and NLP software libraries that can be deployed on-premise or integrated seamlessly into your systems. You can incorporate Salience into your enterprise business intelligence framework or even customize it for your own data analytics solutions. With the ability to handle up to 200 tweets per second, Salience efficiently scales from individual cores to extensive data center infrastructures while maintaining a compact memory footprint. Choose from Java, Python, or .NET/C# bindings for user-friendly integration, or opt for the native C/C++ interface to achieve peak performance. Gain comprehensive control over the foundational technology, allowing you to fine-tune every aspect of text analytics and NLP functions, including tokenization, part of speech tagging, sentiment analysis, categorization, and thematic exploration. The platform is designed around a pipeline model consisting of NLP rules and machine learning algorithms, enabling you to pinpoint issues in the process easily. You can modify specific features without affecting the overall system's integrity. Moreover, Salience operates entirely on your own servers while remaining adaptable enough to transfer non-sensitive data to cloud environments, offering both security and versatility for your analytics needs. This flexibility empowers organizations to leverage advanced analytics features while ensuring data privacy and performance efficiency.
API Access
Has API
API Access
Has API
Integrations
.NET
AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon S3
Axon Ivy
C
C#
C++
Integrations
.NET
AWS AI Services
AWS App Mesh
AWS Lambda
Amazon Comprehend Medical
Amazon S3
Axon Ivy
C
C#
C++
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/comprehend/
Vendor Details
Company Name
Lexalytics
Country
United States
Website
www.lexalytics.com/salience/
Product Features
Natural Language Processing
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
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering
Product Features
Natural Language Processing
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
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering
