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What is Rabbit?
Modern personal computers mainly process straightforward commands rather than fully understanding complex human intentions. LAM, however, transforms natural language requests into actionable responses that the operating system can use right away. In contrast to conventional application programming interfaces (APIs), which typically have limited functionality, LAM interacts with user-centric interfaces across multiple mobile and desktop environments. Additionally, LAM goes beyond simply navigating applications to achieve particular objectives; it does so in a way that aligns with the user's experience, enhancing the intuitive and relatable nature of technology. This improvement in interaction not only facilitates a smoother incorporation of technology into everyday routines but also empowers users to engage more effectively with their devices. As a result, technology becomes an indispensable companion in navigating daily tasks.
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.
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
Rabbit
Company Website
www.rabbit.tech/
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
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
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
