Language Understanding (LUIS) is a cloud-based API service that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.
A client application for LUIS is any conversational application that communicates with a user in natural language to complete a task. Examples of client applications include social media apps, chat bots, and speech-enabled desktop applications.
At Rasa, we're building the standard infrastructure for conversational AI. With over half a million downloads since launch, our open source tools are loved by developers worldwide, and Rasa runs in production everywhere from startups to Fortune 500s. Our friendly community is growing fast, with developers from all over the world learning from each other and working together to make text- and voice-based AI assistants better.
Rasa's machine learning-based dialogue tools allow developers to automate contextual conversations. What are contextual conversations? Real back-and-forth dialogue that is handled seamlessly. Taking AI assistants beyond fixed question / answer pairs creates exciting new use cases for people and business. The tip of the iceberg include automation of sales & marketing, internal processes, and advanced customer service that integrates into existing backend systems. With Rasa, companies control their own destiny, investing in AI that they own and ship instead of relying on third parties.
Microsoft Azure Language Understanding is ranked 5th in Chatbot Development Platforms while Rasa is ranked 1st in Chatbot Development Platforms. Microsoft Azure Language Understanding is rated 0.0, while Rasa is rated 0.0. On the other hand, Microsoft Azure Language Understanding is most compared with IBM Watson Assistant and Google Dialogflow, whereas Rasa is most compared with IBM Watson Assistant, Amazon Lex and Google Dialogflow.
See our list of best Chatbot Development Platforms vendors.
We monitor all Chatbot Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.