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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
Conversational Intelligence offers a distinctive approach for human users to engage with machines, where individuals contribute their intuition while machines utilize their capacity to navigate data and reveal intriguing patterns. This synergy allows both humans and machines to leverage their respective strengths, facilitating the identification of valuable insights within data sets. With the innovative Conversational Intelligence technology developed by DataChat, users can seamlessly perform a wide variety of data analytics tasks—including exploratory data analysis, predictive analytics, structured querying, free search querying, visualization, and data wrangling—all from a single interface. Engaging with the platform is as simple as having a conversation in a controlled natural language. Experience the benefits of increased efficiency and speed, enabling teams to gain deeper insights from data swiftly, regardless of their size, and propel your business forward at an impressive pace. By harnessing this technology, you can enhance your competitive edge in the market. DataChat AI serves as a conversational and intuitive platform for data analytics.
API Access
Has API
API Access
Has API
Integrations
Azure AI Bot Service
Azure AI Services
LUIS
Microsoft Azure
Microsoft Bot Framework
Integrations
Azure AI Bot Service
Azure AI Services
LUIS
Microsoft Azure
Microsoft Bot Framework
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
DataChat
Founded
2017
Country
United States
Website
datachat.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
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
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
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis