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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 Komprehend?

Komprehend AI provides a comprehensive suite of document classification and natural language processing (NLP) APIs tailored for software developers. Utilizing sophisticated NLP models trained on an extensive collection of over a billion documents, we achieve exceptional accuracy across a wide array of common NLP tasks, such as sentiment analysis and emotion detection. You can try our free demo today to see how our Text Analysis API performs in practice, consistently offering high precision when extracting meaningful insights from unstructured text data. Suitable for diverse sectors, including finance and healthcare, our solutions also facilitate private cloud setups through Docker containers or can be deployed on-premise, ensuring your data's confidentiality. We strictly adhere to GDPR compliance standards, emphasizing the safeguarding of your sensitive information. By monitoring online conversations, you can gain a deeper understanding of the social sentiment related to your brand, product, or service. Sentiment analysis involves a detailed contextual review of text to uncover and extract subjective insights, thereby enriching your comprehension of audience opinions. Furthermore, our tools are designed for easy integration into current workflows, simplifying the process for developers to leverage the capabilities of NLP. With these advanced features, Komprehend AI empowers businesses to make data-driven decisions by providing clarity on public sentiment.

Media

Media

Integrations Supported

Docker
Quickwork
Unremot

Integrations Supported

Docker
Quickwork
Unremot

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$79 per month
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

Komprehend

Company Location

India

Company Website

komprehend.io

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

Emotion Recognition

Facial Emotions
Facial Expression Analysis
Machine Learning
Photo Emotions
Speech Emotions
Video Emotions
Written Text Emotions

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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