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What is Verint Text Analytics?

Unstructured information, including emails, chat messages, and phone notes, can be leveraged to derive valuable insights that enhance your customer experience (CX). By utilizing multichannel analytics, you can gain deeper insights into customers who interact through various platforms. These multichannel customers necessitate a holistic approach to employee and customer analytics across different channels. While voice communication continues to be significant, there is a noticeable shift as consumers increasingly prefer digital avenues such as chat, email, and social media. Incorporating Text Analytics provides a comprehensive evaluation of your customer engagement strategy, ensuring that no aspect is overlooked. This integration ultimately empowers businesses to make data-driven decisions that enhance interactions and foster loyalty.

What is Salience?

Delve into the powerful features of text analytics and natural language processing (NLP) software libraries that can be installed on-site or seamlessly integrated into existing systems. Salience can be embedded within your enterprise business intelligence framework or adapted to suit your specific data analytics requirements. Capable of processing up to 200 tweets per second, Salience efficiently scales from single-core setups to large-scale data center environments, all while keeping a minimal memory footprint. Users can choose from bindings in Java, Python, or .NET/C# for easy integration, or utilize the native C/C++ interface to achieve optimal performance. This platform grants you extensive control over the underlying technology, enabling precise adjustments to various aspects of text analytics and NLP tasks such as tokenization, part-of-speech tagging, sentiment detection, categorization, and thematic analysis. Designed around a pipeline model that incorporates NLP rules and machine learning algorithms, it allows for straightforward identification of process issues. You can adjust particular features without compromising the system's overall stability. Furthermore, Salience operates entirely on your servers, yet it is flexible enough to allow for the transfer of non-sensitive data to cloud platforms, striking a balance between security and adaptability for your analytics operations. This versatility not only enhances the organization’s ability to utilize sophisticated analytics capabilities but also prioritizes data privacy and operational efficiency, ensuring that businesses can achieve their analytical goals without sacrificing security. By leveraging these capabilities, organizations can stay ahead in their data-driven decision-making processes.

Media

Media

Integrations Supported

.NET
C
C#
C++
Java
Lexalytics
Python
Semantria

Integrations Supported

.NET
C
C#
C++
Java
Lexalytics
Python
Semantria

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Verint

Date Founded

1994

Company Location

United States

Company Website

www.verint.com/text-analytics/

Company Facts

Organization Name

Lexalytics

Company Location

United States

Company Website

www.lexalytics.com/salience/

Categories and Features

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

Categories and 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

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