The product challenge
Customer conversations and knowledge often live in separate places. The product brings a chat widget, a shared inbox, and AI assistance into a single support workflow.
I approached backend.chat as a product engineering problem: connect the conversation experience people see with the real-time and knowledge systems behind it.
The approach
Connect real-time conversations to a knowledge base so AI assistance has relevant context, while keeping the support team close to the conversation.
A chat widget gives customers an entry point. The shared inbox brings those conversations together for the team. Knowledge-based assistance helps connect a question to the information that may answer it.
Real-time communication. Knowledge-based assistance.
Interface and system
A useful support experience depends on clear conversation state and understandable AI assistance. The engineering work spans the real-time layer, the inbox, stored knowledge, and the application interface.
The product model above explains how the pieces connect. It is an architecture illustration rather than a screenshot of a customer conversation.
The project brings together backend systems, applied AI, and the decisions that shape the interface. That connection is also where my design practice is growing.