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What is Azure Text Analytics?

Harness natural language processing to gain valuable insights from unstructured text without requiring any machine learning knowledge, by utilizing an array of features from the Cognitive Services for Language. Elevate your understanding of customer emotions through sentiment analysis and identify key phrases and entities such as people, places, and organizations to uncover common themes and patterns. Use specialized, pretrained models to classify medical terminology specific to various fields. Evaluate text across multiple languages and reveal essential concepts within the content, which include key phrases and named entities that highlight individuals, events, and organizations. Delve into customer feedback regarding your brand while examining sentiments linked to specific topics through opinion mining techniques. Additionally, derive critical insights from unstructured clinical documents, including doctors' notes, electronic health records, and patient intake forms, by applying text analytics tailored for healthcare settings, ultimately enhancing patient care and informing decision-making processes. By integrating these advanced capabilities, organizations can stay ahead of trends and better meet the needs of their stakeholders.

What is Atomic Intelligence?

Atomic Intelligence provides a digital platform designed for the automated analysis of written content. We sift through extensive datasets, which encompass news stories, social media updates, and regulatory documents, identifying expressed viewpoints along with mentions of companies, products, and various subjects. Our offerings are crucial for investment firms that utilize this information to refine their proprietary trading strategies, consumer goods companies looking to assess customer sentiment, and technology organizations aiming to outsource text analysis tasks. Atomic Intelligence diligently examines texts to reveal references to companies, products, sentiment, and a multitude of other factors. By employing cutting-edge natural language processing and machine learning techniques, we detect important mentions, whether they are overtly articulated or subtly suggested within the material. Furthermore, Atomic Intelligence can efficiently manage any type of unstructured data. Users have the option to upload files via our web interface or API, or they can configure Atomic for automated scheduled data retrieval from their chosen sources, thus simplifying the analysis workflow. This functionality not only enhances efficiency but also equips organizations with the tools needed to extract meaningful insights and make well-informed decisions grounded in thorough textual analysis. Ultimately, our goal is to transform the way organizations interact with text data, facilitating a deeper understanding of market sentiments and trends.

Media

Media

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

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

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

Company Facts

Organization Name

Atomic Intelligence

Date Founded

2003

Company Location

United States

Company Website

www.atomicintelligence.com

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

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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