🌐 Natural language chatbots

Natural language chatbots seem to be the future of customer support, marketing, and even sales – and can definitely help with more specific use cases like personal advice, reporting, analytics, etc.

Until recently, teaching a chatbot to understand the natural language was quite difficult – it required either advanced custom development with tools like Python / Javascript, or should be based on existing NLU (stands for “Natural Language Understanding”) providers like Dialogflow, Wit.ai, Rasa, etc.

These tools are great but still require quite a lot of developer knowledge, especially when it comes to integrating a chatbot to a real business or going beyond the simple “small talk” use case. And that’s where Activechat really shines!

We’ve built our visual chatbot platform as a tool that combines the power of modern AI natural language understanding and the simplicity of decision-tree based chatbot builders like Manychat or Chatfuel. Building smart natural language chatbots is really easy with Activechat, once you get some basic concepts and get used to the idea of chatbot skills that react to specific user intents.

So, let’s dive right in!

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