Ask your own data a question β and let a chatbot answer your clientsβ questions first.
Two AI surfaces on the same indexed platform: an internal assistant your team asks about any record, and a customer-facing chatbot that deflects the questions your knowledge base already answers. Neither trains on your data.
SUB-MODULES
A chat surface that can read the record you are looking at and act on it.
An embeddable widget that answers from your knowledge base before a ticket is ever raised.
Search by meaning across the whole platform, not by exact keyword in one module.
AI you can put in front of an auditor β off by default, bounded, and never training on you.
MODULE CONNECTIONS
Data flows between modules automatically β no manual exports, no copy-paste, no middleware.
Summarise a ticket, draft the reply, deflect the next one
View module βTriage feeds the autonomous playbook runner
View module βDocuments indexed for semantic retrieval
View module βSummarise an account before the call
View module βGraph context assembled into answers
View module βChatbot embedded in the client-facing portal
View module βREAL-WORLD WORKFLOWS
The questions that do not need a human stop being tickets.
Client asks the widget a question on your portal or site
Semantic search finds the article that answers it
Article served, or a ticket raised when it cannot help
Escalated ticket arrives with the conversation summarised
Engineer asks the assistant to draft the response and sends it