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Description

Azure AI Language serves as a comprehensive managed service designed for the creation of natural language processing applications. It enables users to pinpoint important terms and phrases, evaluate sentiment, condense text, and construct interactive conversational interfaces. This service allows you to annotate, develop, assess, and deploy tailored AI models without needing extensive machine-learning knowledge. With ready-to-use entity categories applicable to various industries and text analytics tailored for the healthcare sector, its out-of-the-box functionalities promote rapid initiation while still permitting further customization and enhancement as necessary. To fine-tune your machine learning model for specific scenarios, you can provide several labeled examples. Additionally, custom multilingual models can be trained in a single language and effectively applied across several others. Through Language Studio, you can leverage advanced GPT-powered language models to promptly review and recommend labels for your content. Moreover, it facilitates the extraction, labeling, and redaction of critical information in text across diverse categories, making it a versatile tool for various applications. This combination of features ensures that users can efficiently manage their language processing needs regardless of their technical expertise.

Description

Collaborative text analytics for machine-learning and human. We offer a variety of multilingual, text mining and data science features, as well as human annotation and machine-learning capabilities. DiscoverText provides a variety of cloud-based software tools that allow users to quickly and accurately analyze large amounts of text data. Our customers use DiscoverText to sort unstructured text commonly found in market research. They also include associated metadata such as customer feedback platforms, CRMs and chats. Discover why we are ranked #1 in text, metadata, social network analysis support, and trusted by hundreds academic research groups. Machine-learning sifters can be created in just hours or minutes by crowdsourcing. We provide an API and support technical integrations to SurveyMonkey and Twitter.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Crestwood Cloud Yes 
Microsoft Azure Yes 
SurveyMonkey No 
WordPress No 
X (Twitter) No 

Integrations

Crestwood Cloud No 
Microsoft Azure No 
SurveyMonkey Yes 
WordPress Yes 
X (Twitter) Yes 

Pricing Details

$2 per month
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs No 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/products/ai-services/ai-language/

Vendor Details

Company Name

Texifter

Founded

2009

Country

United States

Website

discovertext.com

Product Features

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

Product Features

Text Mining

Boolean Queries Yes 
Document Filtering Yes 
Graphical Data Presentation Yes 
Language Detection Yes 
Predictive Modeling Yes 
Sentiment Analysis Yes 
Summarization No 
Tagging Yes 
Taxonomy Classification Yes 
Text Analysis Yes 
Topic Clustering No 

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