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What is SentioAI?

SentioAI stands out as a cutting-edge technological solution that harnesses the power of natural language processing, machine learning, and predictive analytics to quickly and effectively identify the most relevant documents from a large pool. By tackling the classification issues associated with Big Data through its distinctive proprietary techniques, SentioAI surpasses competing technologies, delivering faster and more accurate outcomes while remaining budget-friendly. The platform organizes documents based on their relevance, enabling users to examine and label a limited portion of the dataset. This labeled information is then utilized to train SentioAI's prediction engine, which consistently improves its accuracy with the introduction of each new document. The system is designed to intelligently determine when training is complete, after which it applies its models across the entire dataset, yielding thorough results. As a result, not only does SentioAI expedite the document retrieval process, but it also guarantees that users receive the most dependable information in a timely manner, enhancing overall productivity. With its innovative approach, SentioAI is positioned to revolutionize the way organizations handle information retrieval.

What is Azure AI Language?

Azure AI Language provides a robust managed service specifically designed for the development of applications centered around natural language processing. Users are equipped with tools to identify key terms and phrases, evaluate sentiment, summarize text, and create engaging conversational interfaces. The platform allows individuals to annotate, train, assess, and launch customizable AI models with minimal machine learning knowledge required. It features predefined entity categories relevant to various sectors, including specialized text analytics for healthcare, enabling quick setup while also offering opportunities for customization and enhancement as needed. To optimize the training of machine learning models for unique applications, users can provide multiple labeled examples. Furthermore, it supports the creation of custom multilingual models that can be developed in one language and effectively applied across others. Utilizing Language Studio, users gain access to sophisticated GPT-powered language models that analyze and suggest labels for their content efficiently. The platform also facilitates the extraction, labeling, and redaction of vital information within text across diverse categories, ensuring that sensitive information is managed properly. This adaptability positions Azure AI Language as a crucial asset for organizations aiming to improve their capabilities in natural language processing, ultimately driving innovation and efficiency in their operations. With its extensive features and user-friendly interface, the platform stands out as a leading choice for businesses in today's digital landscape.

Media

Media

Integrations Supported

Crestwood Cloud
Microsoft Azure

Integrations Supported

Crestwood Cloud
Microsoft Azure

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$2 per month
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

RINA Systems

Company Location

United States

Company Website

www.rinasystems.com/product/sentioAI.html

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

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

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

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

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