• May 8, 2018

Atomic X Enters the Chatbot Market

Atomic X, an experiential artificial intelligence (AI) firm and consulting business, today entered the global AI marketplace with the launch of its flagship product, Rufus, an advanced chatbot combined with a traditional live-chat system.

Based on a proprietary blend of machine learning algorithms and human-curated language sets, Rufus applies AI techniques to conversations and text data for the marketing and customer service industries.

Highlights of Rufus include the following:

  • Direct integration into existing customer support tracking software;
  • Consumer insights through integrated conversation and behavior analytics;
  • Custom language sets and personas that match companies' brands and targeted audiences;
  • Live monitoring of automated bot conversations on desktop or through Atomic X's app; and
  • Proprietary browser control.

"Chatbots on the market today are based on fixed-language responses and pattern matching, so the closest thing you see to emotional responses comes through creative fixed-language responses," said Eric Moller, chief technology officer at Atomic X, in a statement. "What differentiates Rufus, is the creativity of our language sets and our willingness to take risks with our responses in order to create a more human-like connection. Applying AI to text and conversational systems is a very difficult problem. There's so much collective human experience embedded into our language, but in beta testing we witnessed an incredibly higher level of user engagement that blurs the lines of perception between humans and machines, something we are excited to be the first to do."

"Everything we've built has been with the end user or chat operator in mind," said Dan Cummins, CEO of Atomic X, in a statement. "The rise of AI and machine learning will impact virtually every business across most industries, and many organizations aren't prepared to benefit from the new opportunities available during the next wave of automation. We are thrilled to be applying machine learning to problems that were always impossible to tackle, using traditional computing paradigms and preparing organizations for the future."


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