AutoShop, Connecting agents with customers-retail

Autonomous Store is an online outdoor-clothing shop that runs two loops by itself, with Gemma 4 on AMD doing the language work. The selling loop: a shopper asks in plain words, for example, "a warm waterproof jacket under $300". A TypeScript agent sends the request to Gemma 4 31B on AMD's hosted inference endpoint, which chooses tools to search the catalogue, compare items, suggest products others bought together, fill the bag and check out. Answers come back as product cards (one pick, a comparison or a grid). Prices and stock always come from the store's database, never from the model. The restocking loop: a simulated calendar brings daily demand and supplier deliveries. Every Monday, a Transformer demand forecast (PyTorch, ROCm-ready) and an order-up-to policy decide how much to reorder for each of 1,614 real products, and Gemma explains selected orders in one line. The merchant chooses whether orders go out automatically or wait for approval. Under the hood: a Go server and React app, Postgres with pgvector for keyword plus meaning-based search, and Neo4j graph algorithms for "also bought" suggestions. On simulated sales, replaying the same 21 days of demand, automatic reordering cut lost sales from 5,730 to 232 units compared with no reordering.