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Description
Develop applications utilizing conversational language understanding, an advanced AI capability that interprets user intentions and extracts crucial details from informal dialogue. Design customizable intent classification and entity extraction models tailored to your specific terminology across 96 different languages, allowing for multilingual functionality without the need for retraining after initial training in one language. Swiftly generate intents and entities while tagging your own utterances, and incorporate prebuilt components from an extensive range of standard types. Assess your models using integrated quantitative metrics such as precision and recall to ensure optimal performance. A user-friendly dashboard simplifies the management of model deployments within the accessible language studio. Effortlessly integrate with various other features in Azure AI Language, alongside Azure Bot Service, to create a comprehensive conversational experience. This conversational language understanding represents the evolution of Language Understanding (LUIS) and enhances the way users interact with technology. As the demand for intuitive communication increases, leveraging this technology can significantly improve user engagement and satisfaction.
Description
Language Understanding (LUIS) is an advanced machine learning service designed to incorporate natural language capabilities into applications, bots, and IoT devices. It allows for the rapid creation of tailored models that enhance over time, enabling the integration of natural language features into your applications. LUIS excels at discerning important information within dialogues by recognizing user intentions (intents) and extracting significant details from phrases (entities), all contributing to a sophisticated language understanding model. It works harmoniously with the Azure Bot Service, simplifying the process of developing a highly functional bot. With robust developer resources and customizable pre-existing applications alongside entity dictionaries such as Calendar, Music, and Devices, users can swiftly construct and implement solutions. These dictionaries are enriched by extensive web knowledge, offering billions of entries that aid in accurately identifying key insights from user interactions. Continuous improvement is achieved through active learning, which ensures that the quality of models keeps getting better over time, making LUIS an invaluable tool for modern application development. Ultimately, this service empowers developers to create rich, responsive experiences that enhance user engagement.
API Access
Has API
API Access
Has API
Integrations
Azure AI Bot Service
Azure AI Services
Azure CLU
BotCore
Dydu
Geomant
Geomant Wallboard
Ideta
LUIS
Microsoft Azure
Integrations
Azure AI Bot Service
Azure AI Services
Azure CLU
BotCore
Dydu
Geomant
Geomant Wallboard
Ideta
LUIS
Microsoft Azure
Pricing Details
$2 per month
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/products/ai-services/conversational-language-understanding/
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
www.luis.ai/
Product 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
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
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