Audience
Developers in need of an AI solution to provide customers with the tools interact with their apps, bots, and IoT devices
About Azure CLU
Build applications with conversational language understanding, an AI language feature that understands natural language to interpret user goals and extract key information from conversational phrases. Create multilingual, customizable intent classification and entity extraction models for your domain-specific keywords or phrases across 96 languages. Train in one natural language and use them in multiple languages without retraining. Quickly create intents and entities and label your own utterances. Add prebuilt components from a wide variety of commonly available types. Evaluate with built-in quantitative measurements like precision and recall. Use the simple dashboard to manage model deployments in the intuitive and user-friendly language studio. Use seamlessly with other features within Azure AI Language, as well as Azure Bot Service for an end-to-end conversational solution. Conversational language understanding is the next generation of Language Understanding (LUIS).
Pricing
Starting Price:
$2 per month
Free Trial:
Free Trial available.
Integrations
Company Information
Microsoft
Founded: 1975
United States
azure.microsoft.com/en-us/products/ai-services/conversational-language-understanding/
Videos and Screen Captures
HumanFirst
HumanFirst provides radically efficient infrastructure and workflows to explore, curate and scale your AI training data. We productize the capabilities to scale NLU & NLP. HumanFirst accelerates conversational AI. Real voice-of-the-customer data, always in the loop. HumanFirst Studio makes working with voice and text data to train and maintain natural language understanding NLU models a breeze. Replace costly, and ad-hoc data ingestion and labeling processes with a seamless experience that allows you to build and improve the performance of your AI with real data, immediately. Import your Search and Help Center requests, emails, live chat or voice call logs to continuously train AI that understands your customers. Discover intents and improve their accuracy. Guessing what intents you need to train, and coming up with training phrases manually is painful - and often leads to low coverage and accuracy of intents.
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Azure AI Language
Azure AI Language is a managed service for developing natural language processing applications. Identify key terms and phrases, analyze sentiment, summarize text, and build conversational interfaces. Use Language to annotate, train, evaluate, and deploy customizable AI models with minimal machine-learning expertise. From predefined entity categories for every business to text analytics for healthcare domains, out-of-box capabilities help you get started quickly with the ability to further customize and optimize when needed. Provide a few labeled examples to train your machine learning model for your specific use case. Custom multilingual models can be trained in one language and used for multiple other languages. Access GPT-powered advanced language models through Language Studio to quickly scan and suggest labels for your content. Extract, label, and redact vital information in text across multiple categories.
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LUIS
Language Understanding (LUIS): A machine learning-based service to build natural language into apps, bots, and IoT devices. Quickly create enterprise-ready, custom models that continuously improve. Add natural language to your apps. Designed to identify valuable information in conversations, LUIS interprets user goals (intents) and distills valuable information from sentences (entities), for a high quality, nuanced language model. LUIS integrates seamlessly with the Azure Bot Service, making it easy to create a sophisticated bot. Powerful developer tools are combined with customizable pre-built apps and entity dictionaries, such as Calendar, Music, and Devices, so you can build and deploy a solution more quickly. Dictionaries are mined from the collective knowledge of the web and supply billions of entries, helping your model to correctly identify valuable information from user conversations. Active learning is used to continuously improve the quality of the models.
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Azure Text Analytics
Mine insights in unstructured text using NLP—no machine-learning expertise required—using text analytics, a collection of features from Cognitive Service for Language. Gain a deeper understanding of customer opinions with sentiment analysis. Identify key phrases and entities such as people, places, and organizations to understand common topics and trends. Classify medical terminology using domain-specific, pretrained models. Evaluate text in a wide range of languages. Identify important concepts in text, including key phrases and named entities such as people, events, and organizations. Examine what customers are saying about your brand and analyze sentiments around specific topics through opinion mining. Extract insights from unstructured clinical documents such as doctors' notes, electronic health records, and patient intake forms using text analytics for health.
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SaaS
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