[context] AI answer for chat to support multiple KBs as source of knowledge
Situation: Currently, AI Answer for Chat only supports a single knowledge base, limiting its ability to draw from multiple sources of information. In scenarios where knowledge is spread across several external public knowledge bases, users cannot ...
AI-based features seem to support some languages but it's not guaranteed for many of them. cc https://help.front.com/en/articles/914304#prerequisites I'd be great if features like AI answer for chat, Suggested replies could leverage knowledge base...
Situation: Support teams can encounter multiple customer requests that are duplicates of previously resolved issues, leading to redundant work and decreased efficiency. Request: Implement a feature that automatically detects and flags duplicate cu...
Situation Description: Currently, users can only search for answers in a single knowledge base (KB) at a time. This limitation requires users to know which specific KB contains the relevant information, and if they don’t, they must manually search...
[action] Automatic AI Translation for Inbound and Outbound Messages
Situation Description: Currently, AI translation for inbound and outbound messages requires users to manually trigger the translation. This adds extra steps and actions that slow down their workflow, especially for users handling conversations in ...
[accuracy] Similar conversation based on a more specific entity (inquriy, ticket, order, shipment ...)
Situation: The current “similar conversation” feature in Front is based on semantic proximity. This approach can be inefficient, especially when users need to find conversations related to specific entities like a ticket number, order number, ship...
[context] Ai tagging based on entity in conversation (date, duration, amount...)
Situation & Request Wish to tag based on non-semantic values such as dates, amounts, and durations. Currently, the AI Tagging tool is not equipped to detect and apply tags based on these structured data types. Potential Solution Invest in enti...
[package] Automatic CSAT from conversation analysis
Context: Understanding customer satisfaction is important for our business, however, today's approaches are too imperfect: Survey : asking users directly. Response rate low (1-3%) and polarized (super happy or frustrated) Not representative of all...