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What is InfoNgen?

InfoNgen serves as an advanced text analytics and sentiment analysis platform that efficiently reveals actionable insights from vast amounts of information. By streamlining the process of making strategic decisions, teams can focus on sharing, analyzing, and disseminating only the most essential insights derived from both structured and unstructured data. With its innovative tools for sentiment analysis and text mining, InfoNgen enables users to identify significant patterns, trends, and anomalies within their datasets. Unlike other solutions, InfoNgen uniquely integrates its specialized use cases with robust functionalities, thereby enhancing decision-making capabilities for employees and accelerating their workflow. This powerful platform acts as a vital asset for businesses seeking to locate critical information quickly, featuring pre-built industry taxonomies alongside customizable delivery options to meet diverse needs. Consequently, organizations can leverage InfoNgen not only to improve efficiency but also to stay ahead in a competitive landscape.

What is DiscoverText?

DiscoverText combines collaborative text analytics for both machine learning and human input, offering a comprehensive suite of multilingual text mining and data science functionalities alongside human annotation and machine-learning features. Our cloud-based software tools empower users to efficiently and precisely analyze extensive text datasets, making it easier for customers to organize unstructured text typically encountered in market research. In addition, our platform enables users to incorporate relevant metadata from various sources such as customer feedback systems, CRMs, and chat interactions. Learn why we are the top choice in text and metadata analysis, as well as social network analysis support, with a trusted reputation among numerous academic research groups. With the capability to construct machine-learning classifiers in mere hours or even minutes through crowdsourcing, our service stands out in the industry. Moreover, we offer an API and facilitate seamless technical integrations with platforms like SurveyMonkey and Twitter, enhancing the overall user experience. Our dedication to innovation and customer satisfaction continues to drive our success.

Media

Media

Integrations Supported

AWS Elemental
Dropbox
Google Cloud Document AI
Microsoft OneDrive
Microsoft SharePoint
Microsoft Teams
Salesforce
SurveyMonkey
WordPress
X (Twitter)

Integrations Supported

AWS Elemental
Dropbox
Google Cloud Document AI
Microsoft OneDrive
Microsoft SharePoint
Microsoft Teams
Salesforce
SurveyMonkey
WordPress
X (Twitter)

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

EPAM Systems

Company Location

United States

Company Website

www.epam.com

Company Facts

Organization Name

Texifter

Date Founded

2009

Company Location

United States

Company Website

discovertext.com

Categories and Features

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Insight Engines

AI / Machine Learning
Augmented Analytics
Data Aggregation
Data Classification
Data Extraction
Data Source Connectors
Full Text Search
Intent Recognition
Multiple Data Sources
Search / Filter
Sentiment Analysis

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

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