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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 Google Cloud Natural Language API?

Employ cutting-edge machine learning methodologies for an in-depth analysis of text that facilitates the extraction, interpretation, and secure storage of textual information. Utilizing AutoML, one can effortlessly build high-performance custom machine learning models without needing to write any code. Enhance your applications by implementing natural language understanding via the Natural Language API, which significantly boosts their capabilities. By employing entity analysis, you can accurately identify and categorize various elements in documents such as emails, chats, and social media exchanges, followed by conducting sentiment analysis to assess customer feedback and generate actionable insights for enhancing products and user experiences. Moreover, the Natural Language API, paired with speech-to-text functionalities, allows you to gather meaningful insights from audio sources as well. The Vision API also adds to your toolkit by providing optical character recognition (OCR) to convert scanned documents into digital formats. Additionally, the Translation API broadens your understanding of sentiment across multiple languages, making it easier to connect with diverse audiences. With the ability to perform custom entity extraction, you can uncover specialized entities within your documents that might be overlooked by conventional models, thereby saving time and resources that would otherwise be spent on manual processing. Furthermore, this robust methodology allows you to train your own high-quality machine learning models, enabling precise classification, extraction, and sentiment assessment, which enhances the efficiency and focus of your analysis. Ultimately, this all-encompassing strategy guarantees a thorough understanding of both textual and audio data, equipping businesses with profound insights to drive better decision-making and strategies.

Media

Media

Integrations Supported

Dropbox
Gemini
Gemini 1.5 Pro
Gemini 2.0 Flash
Gemini Advanced
Gemini Nano
Gemini Pro
Google Cloud AutoML
Google Cloud Document AI
Google Cloud Platform
Google Cloud Speech-to-Text
Google Cloud Vision AI
Microsoft OneDrive
Microsoft SharePoint
Microsoft Teams
PubNub
Salesforce
Unremot
Vertex AI
n8n

Integrations Supported

Dropbox
Gemini
Gemini 1.5 Pro
Gemini 2.0 Flash
Gemini Advanced
Gemini Nano
Gemini Pro
Google Cloud AutoML
Google Cloud Document AI
Google Cloud Platform
Google Cloud Speech-to-Text
Google Cloud Vision AI
Microsoft OneDrive
Microsoft SharePoint
Microsoft Teams
PubNub
Salesforce
Unremot
Vertex AI
n8n

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

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/natural-language

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

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Natural Language Generation

Business Intelligence
CRM Data Analysis and Reports
Chatbot
Email Marketing
Financial Reporting
Multiple Language Support
SEO
Web Content

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

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

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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