Amazon Lex
Dialogflow
IBM Watson Assistant
Microsoft Bot Framework
Botpress
Tars
Chatfuel
SentiOne
rasa NLU
Dialogflow
Microsoft Bot Framework
Botpress
Wit.ai
Chatfuel
spaCy
Voiceflow
Amazon Lex| Categories |
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|---|---|
| Website | aws.amazon.com |
| Pricing URL | - |
| Details $ | - |
rasa NLU| Categories |
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| Website | rasa.com |
| Pricing URL | Official rasa NLU Pricing |
| Details $ |
Based on our record, rasa NLU should be more popular than Amazon Lex. It has been mentiond 22 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Amazon's doesn't care about Mturk, they have their own AI that will eventually automate all their work too https://aws.amazon.com/lex/. Source: 11 months ago
Amazon Lex, AWS's natural language conversational AI service. With Amazon Connect, it seamlessly leverages Amazon Transcribe to understand what is being said (speech-to-text), and Amazon Polly to provide the verbal response (text-to-speech). We aren't really using the Natural Language powers of Lex, but it has other uses for us:. - Source: dev.to / over 1 year ago
AWS has three high-quality tools: Amazon Lex, Amazon Rekognition, and Amazon SageMaker. - Source: dev.to / over 1 year ago
Introducing DTMF slot settings within Amazon Lex.Amazon Lex is a service for building conversational interfaces into any application using voice and text. With Amazon Lex, you can quickly and easily build conversational bots ("chatbots"), virtual agents, and interactive voice response (IVR) systems. Amazon Lex is excited to launch DTMF-only slot settings and configurable session attributes within the Lex console. - Source: dev.to / over 1 year ago
The text processing is a bit more interesting, as we have the original text and some insights into the content and sentiment, but we need a response. So for this application Amazon Lex has been configured to do this. - Source: dev.to / over 1 year ago
Beyond raw language models, NLP engines like Rasa and Dialogflow offer frameworks for designing, building, and improving conversational flows. They help in intent recognition, entity extraction, and dialogue management, which are crucial for a coherent conversation structure. - Source: dev.to / about 1 month ago
There are frameworks out there for doing that kind of thing, see https://rasa.com/ for example. It's not using any LLMs at the moment, just BERT and DIET mostly but it's highly customizable and you could likely bring in an LLM for doing some interesting things to handle more complex messages from users. - Source: Hacker News / 11 months ago
Chatbot frameworks: Utilize chatbot frameworks such as Botpress, Rasa, or Microsoft Bot Framework to streamline development. - Source: dev.to / about 1 year ago
Rasa is a popular tool used right now to build these applications. If you're looking for a serious turn-key solution I would check out Vectara. Source: about 1 year ago
Another example is RASA, one of the most popular platforms for creating conversational AI assistants. On the accepted AI quality scale, RASA reaches levels 3 and 4. It means that the "robot" not only understands humans with high accuracy in a given contextual field but also learns to recognize contradictions and ulterior motives. - Source: dev.to / over 1 year ago
Dialogflow - Conversational UX Platform. (ex API.ai)
IBM Watson Assistant - Watson Assistant is an AI assistant for business.
Microsoft Bot Framework - Framework to build and connect intelligent bots.
Botpress - Open-source platform for developers to build high-quality digital assistants
Wit.ai - Easily create text or voice based bots that humans can chat with on their preferred messaging...
Tars - TARS enables users to create chatbots that replaces regular old webforms.
