E-commerce Support Chat Assistant
Conversational customer-support and order-assistance platform built with React and FastAPI
A closer lookat what we built
This project focused on making online-store support more conversational. Customers could ask questions in plain language instead of searching help pages or waiting for an email response. The assistant was designed to answer common product and support questions, retrieve order information, assist with returns, and stream responses in real time. The frontend was built in React and the backend in FastAPI, with WebSocket communication used for responsive conversations.
Real-time WebSocket support chat that resolves product, order and return questions without waiting on email.
From challenge toproduction outcome
The Challenge
E-commerce support sits at the intersection of product information, order data and customer-service policies. A useful assistant must understand what the customer is asking and then provide accurate, contextual information rather than simply producing a generic answer. Performance was also important: conversational interfaces feel slow when every message waits for a traditional request-response cycle.
Keycapabilities
Natural-language product and support questions
Order-status and order-detail assistance
Return and post-purchase support workflows
Real-time WebSocket-based responses
React conversational interface
FastAPI backend and asynchronous request handling
Context-aware responses based on available store information
Performance-focused API design
Clear separation between AI conversation and transactional business logic
The stack andarchitecture we chose
React was used for the customer-facing experience, FastAPI for the API and business-logic layer, and WebSockets for real-time response delivery. The design allows the conversational layer to be connected to product/order systems without making the UI dependent on slow polling or repeated full-page requests.
Real-worldmarket validation
The referenced ChatLab e-commerce platform publicly demonstrates product discovery, product recommendations, order-detail lookup and conversational customer support. Its documentation also describes integrations with platforms such as Shopify and WooCommerce and live order/product retrieval. These public capabilities were used as a reference for framing the problem and expected user experience, not as claims about the custom project's exact integrations.
