A First Look At Microsoft Power Virtual Agent
And How Does It Fit Into An Existing Chatbot Ecosystem
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Introduction
Companies introducing Conversational Interfaces are looking to scale as quick as possible. Huge focus is placed on the UX and CX and often due diligence is not followed regarding the chatbot framework and basic architecture.
As the chatbot in specific and the Conversational AI environment in general are growing, more often than not problems are encountered in scaling the chatbot. It becomes hard to extend the environment.
This is especially the case when a graphic environment is used for the dialog management and conversational node instead of native code.
The Problem of Code
Traditionally a chatbot ecosystem consist of of 3 components;
- Intents
- Entities
- Dialog Flow and Conversational Nodes
The Conversational nodes also including the Dialog. The Dialog being the wording displayed to the user, the output the chatbot gives the user.
Intents and Entities are defined within a GUI (Graphic User Interface) and often the output is a custom NLU API.
But then the conversational portion, is the hard work and takes the longest.
The folks at www.rasa.com are doing a great job in deprecating the dialog flow, or state machine, if you like. I hope to spend some time on the Rasa environment in stories to come.
Within the Microsoft environment, the tool available was the Bot Framework, with which a Digital Assistant could be created or Skills. This necessitated native code (C# in most cases).
The Achilles Heel Of Chatbot Ecosystems
IBM Watson Assistant has mastered this to some extend, where you can define your dialog within the Watson Assistant environment. You can also test…
