Typewise

Customer submits a support request via email or chat.

The AI Supervisor Engine analyzes the request using NLP.

The AI identifies the intent and topic of the request.

The ticket is automatically routed to the appropriate AI Agent or human agent based on predefined rules.

The agent receives a summarized view of the issue.

AI analyzes customer interactions to detect sentiment and identify anomalies.

If a negative sentiment or potential issue is detected, the AI proactively suggests relevant knowledge base articles or support actions.

The AI initiates a chat or sends an email to the customer offering assistance.

The customer receives personalized support and potential issues are resolved quickly.

Customer submits a support request in their native language.

The AI automatically detects the language and translates the request into a language understood by the support team.

The AI Agent or human agent responds in the translated language.

The AI translates the response back into the customer's native language.

The customer receives support in their preferred language.

The AI analyzes the customer's message.

The AI searches the knowledge base for relevant information.

The AI generates a suggested reply based on the analysis and knowledge base content.

The agent reviews and edits the suggested reply as needed.

The agent sends the reply to the customer.

The AI analyzes customer data, including past interactions, preferences, and demographics.

The AI uses this data to personalize the support experience.

The AI tailors responses, offers, and recommendations to the individual customer.

The customer receives a highly personalized and relevant support experience.