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Power Virtual Agents vs Botium: What are the differences?

Power Virtual Agents: Build chatbots with no code. It empowers teams to easily create powerful bots using a guided, no-code graphical interface without the need for data scientists or developers. It addresses many of the major issues with bot building in the industry today. It eliminates the gap between the subject matter experts and the development teams building the bots, and the long latency between teams recognizing an issue and updating the bot to address it. It removes the complexity of exposing teams to the nuances of conversational AI and the need to write complex code. And, it minimizes the IT effort required to deploy and maintain a custom conversational solution; Botium: Open-Source Stack for Testing and Analytics of Conversational AI. It is a suite of open source software components that support chatbot makers in training and quality assurance.

Power Virtual Agents and Botium belong to "Chatbot Platforms & Tools" category of the tech stack.

Some of the features offered by Power Virtual Agents are:

  • Easily create your own virtual agents
  • Empower virtual agents to take action
  • Measure performance

On the other hand, Botium provides the following key features:

  • Testing, training and quality assurance for chatbots
  • Selenium for Chatbots
  • Testing 100x faster

Botium is an open source tool with 144 GitHub stars and 44 GitHub forks. Here's a link to Botium's open source repository on GitHub.

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What is Botium?

It is a suite of open source software components that support chatbot makers in training and quality assurance.

What is Power Virtual Agents?

It empowers teams to easily create powerful bots using a guided, no-code graphical interface without the need for data scientists or developers. It addresses many of the major issues with bot building in the industry today. It eliminates the gap between the subject matter experts and the development teams building the bots, and the long latency between teams recognizing an issue and updating the bot to address it. It removes the complexity of exposing teams to the nuances of conversational AI and the need to write complex code. And, it minimizes the IT effort required to deploy and maintain a custom conversational solution.

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