Conversational language understanding
A feature of Cognitive Service for Language that uses natural language understanding (NLU) so people can interact with your apps, bots, and IoT devices.
Add custom NLU to your apps
Build applications with conversational language understanding, a Cognitive Service for Language feature that understands natural language to interpret user goals and extracts 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.
Language studio simplifies creation, labeling, and deployment for your custom models.
No machine-learning experience required.
Configurable to return the best response from multiple language applications.
Enterprise-grade security and privacy applied to both your data and trained models.
Quickly build a custom, multilingual solution
Quickly create intents and entities and label your own utterances. Add prebuilt components from a wide variety of common 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.
Build a natural language processing solution
Use seamlessly with other features within Azure Cognitive Service for Language, as well as Azure Bot Service for an end-to-end conversational solution.
Improve your apps with the next generation of LUIS
Conversational language understanding is the next generation of Language Understanding (LUIS). It comes with state-of-the-art language models that understand the utterance's meaning and capture word variations, synonyms, and misspellings while being multilingual. It also automatically orchestrates bots powered by conversational language understanding, question answering, and classic LUIS.
Explore conversational language understanding scenarios
Build an enterprise-grade conversational bot
This reference architecture describes how to build an enterprise-grade conversational bot (chatbot) using the Azure Bot Service framework.
Together, Azure Bot Service and conversational language understanding enable developers to create conversational interfaces for various scenarios, such as banking, travel, and entertainment.
Controlling IoT devices using a voice assistant
Create seamless conversational interfaces that understand natural language with all your internet-accessible devices—from your connected television or fridge to devices in a connected power plant.
Conversational language understanding is the next generation of Language Understanding (LUIS)
Conversational language understanding
Language Understanding (LUIS)
|Transformer-based, state-of-the-art models||
|Train in one natural language and use the model in multiple languages without retraining||
|Orchestrate between multiple language application||
|Interoperable with Bot Framework SDK||
|Interoperable with Bot Framework Composer||
|Run on premises or at the edge with containers||
|Annotate, train, evaluate, and deploy models with language studio||
Comprehensive security and compliance, built in
Microsoft invests more than $1 billion annually on cybersecurity research and development.
We employ more than 3,500 security experts who are dedicated to data security and privacy.
Get the power, control, and customization you need with flexible pricing
Pay only for what you use, with no upfront costs. With Azure Cognitive Service for Language, pay as you go based on the number of transactions.
Get started with an Azure free account
After your credit, move to pay as you go to keep building with the same free services. Pay only if you use more than your free monthly amounts.
See how companies are applying Language Understanding (LUIS) and conversational language understanding models
Telefónica delivers an NLU- and AI-powered digital assistant
A telecommunications giant builds a digital assistant based on a natural language bot to engage with customers on a new level.
KPMG saves clients millions in compliance costs
"With Azure Cognitive Services, we're able to get transcription accuracy of 90 percent or better. It's supporting improved analytics services and leading to improved outcomes—for our clients and for us."
Steve Wells, Director, Forensic Data Analytics
Vodafone transforms its customer care strategy with digital assistant built on Azure Cognitive Services
"We used Azure Cognitive Services and Microsoft Bot Framework to deliver an instantly responsive, personal expert into our customers' pockets. Providing this constant access to help is key to our customer care strategy."
Paul Jacobs, Group Head of Operations Transformation
LaLiga boosts engagement with its own virtual assistant
"It's the easiest and most natural way for humans to interact, so we wanted to give our fans that option. They don't need to navigate through an app to find information, they just ask a question in plain language."
Alfredo Bermejo, Digital Strategy Director, LaLiga
Progressive extends Flo to better serve customers
"By using Microsoft Azure Bot Services and Cognitive Services… we've been able to continue our own Progressive journey of digital innovation and do it in an agile, fast, and cost-effective way."
Matt White, Marketing Manager, Personal Lines Acquisition Experience, Progressive Insurance
Documentation and resources
Frequently asked questions about conversational language understanding
Conversational language understanding is the next generation of LUIS. It comes with state-of-the-art language models and technology that understand the utterance's meaning and easily captures word variations, synonyms, and misspellings, all while being multilingual immediately out of the box. It also comes with orchestration for you to directly connect to conversational language understanding projects, custom question answering (formerly QnA Maker) knowledge bases, and even classic LUIS applications.
It uses native multilingual technology to train your intent classes and entity extractors. For example, train a project in English, and query it in French, German, or Italian, and still get the expected results for intents and entities. Add data in different languages in case the results of any of the languages aren't performing as well.
Complex conversational services like chatbots require more than just one language project to serve its scenarios. Create orchestration projects and connect to conversational language understanding projects, custom question answering knowledge bases, and classic LUIS apps. Each connection is mapped to an intent in the orchestration project. A query to the project will predict which intent is best suited to the query and route it to the connected project, and return with the connected project's response.
Follow the documentation for orchestration.
LUIS will continue to be supported and maintained as a GA service.