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Description
InfoNgen is a text analytics solution and sentiment analysis tool that automatically uncovers actionable insights in mountains of data. To dramatically reduce the time required to make informed strategic decisions, your teams will be able to share, analyze, and share only critical information from both structured and unstructured data. InfoNgen's proprietary tools for sentiment analysis and text analytics allow you to uncover patterns, trends, and anomalies deep within your data. InfoNgen is the only product that combines its unique use cases with powerful features. This will empower your employees to make better decisions and get there faster. InfoNgen provides businesses with a powerful resource for finding critical information. It has pre-built industry taxonomies and customizable delivery options.
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 Elemental
C
C#
C++
Dropbox
Google Cloud Document AI
Java
Lexalytics
Microsoft OneDrive
Integrations
.NET
AWS Elemental
C
C#
C++
Dropbox
Google Cloud Document AI
Java
Lexalytics
Microsoft OneDrive
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
EPAM Systems
Country
United States
Website
www.epam.com
Vendor Details
Company Name
Lexalytics
Country
United States
Website
www.lexalytics.com/salience/
Product 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
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