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Archive - 25.12.2019

Migration From DialogFlow to RASA: the missing part

Implementing DialogFlow chatbots is cool and convenient if you have something trivial and easy to prototype: fancy UI – easily, extracting base entities like name, surname and phone number – here is a tool if don’t want to install and deploy – cloud solution is at your service.
But what if you need to go deeper:

– Do you have a Japanese tokenizer, dear DialogFlow?
– Nope
– Transparent and customizable intent classification tool?
– Sorry, guys.
– Also I want to integrate my search index, knowledge graph and custom dialogue management policy.
– What are you talking about?

In a nutshell if you want fully controlled system, if you need custom advanced AI in your app, if you need natural language processing in your chatbot pipelines, if you want to scale your chatbot behaviour – on-premise solution is the way for a chatbot developer. And here it’s Rasa framework that really shines.

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