AI customer assistant answers live order queries and cuts call volumes — scalable across support journeys and channels.
Problem
Workwear Group was facing a high volume of customer service contacts related to order tracking — but "Where is my order?" wasn’t a single question. It spanned a range of specific scenarios including delivery ETA, partial shipments, approval delays, tracking link requests, and proof of delivery inquiries. These nuanced cases made it difficult to handle the query using traditional FAQ pages or simple chatbot flows.
The diversity of order statuses and customer types, e.g. B2B, B2C and EDI, meant that off-the-shelf automation tools could not effectively triage or respond with accurate, real-time data. A more intelligent and integrated solution was needed — one that could interpret natural language queries, determine order context, and query backend systems accordingly. Workwear Group needed to streamline support operations without compromising on customer experience.
Solution
We delivered a production-ready AI assistant designed to handle high-volume “Where is my order?” queries using live data from Workwear Group’s backend. The assistant uses LangGraph orchestration powered by LLMs to dynamically route queries and format responses based on real-time order tracking data.
The system was designed to be modular and extensible — with tracing, human handoff triggers, and future hooks for returns, cancellations, and SKU lookups. It is deployed in Microsoft Azure and integrates seamlessly into existing front-end environments. The architecture supports future expansion across journeys, user types such as EDI, SAP or Punch-Out, and channels.
Results
The AI assistant deflects significant volumes of inbound queries, with estimated savings in six figures annually based on historical call volume. Customers now receive instant answers to their most common question, improving satisfaction and reducing wait times.
This implementation proves the business value of conversational AI for support and sets the foundation for broader automation across customer service functions, including FAQs, returns, and delivery issues.
Technologies
