Decision Trees

Decision Trees

The Inbenta Chatbot uses Decision Trees to define the flow of conversation that the system will take. This is similar to how Call Center Flows are used to define how agents have to handle every situation.

Chatbot Highlights

  • Unique Natural Language Processing engine with over ten years of lexical development
  • Works out of the box: no additional rephrasing or learning necessary
  • Webhook-based Decision Trees for a dynamic, context-sensitive conversational flow
  • Multiple entity-based detection method that interpret visitors’ intents
  • Scalable and expandable solution that integrates with CRMs, billing systems, and more...
  • Feature-rich transactional intelligence with seamless escalation to live conversation
  • Unique avatar options for a deeply personalized customer experience

Any intent can trigger an interim decision tree to help solve complex queries. At every step of the tree, the Inbenta Chatbot may ask Clarifying Questions to better understand the situation at hand. Eventually, the Chatbot might need to trigger back-office transactions with other systems and legacy applications through Webhooks. The results of these Webhooks can, in turn, determine the direction decision trees will take.

Inbenta’s Decision Trees have a unique feature, in that they can interpret context based on Natural Language. This means that if a user asks a question with great detail and enough context, the Inbenta Chatbot can make a direct match with a deep node of the decision tree, making the whole experience much faster and efficient for the end users, and much simpler to build.