The problem
A sneaker wholesaler in Surat was running inventory across multiple websites. Customers messaged on WhatsApp asking if a specific sneaker in a specific size was available, and someone on the team had to manually check every site before they could reply. With high message volume and stock spread across several platforms, response times were slow, mistakes were happening, and the team was spending hours a day on queries that should not require a human at all.
The approach
- Built a WhatsApp bot that connects directly to the client’s multi-site inventory system in real time
- When a customer sends a sneaker name and size, StockFindr queries the stock database across all connected websites and replies within seconds with availability status and a direct link to place the order
- The natural language parsing layer handles the variation in how people actually message — abbreviated sneaker names, wrong spellings, size formats that differ across markets — and normalizes all of it before hitting the inventory lookup, so no reformatting is required from the customer
The result
Stock queries that required manual checking across multiple websites now get answered in seconds with zero human involvement. Every reply includes availability status and a ready-to-click order link. Customer response time dropped from several minutes to under ten seconds. The client now handles higher message volume with less team effort than before.