Fashion guesses. Brands commit to hundreds of pieces per style months before anyone buys; in 2023 the industry produced an estimated 2.5-5 billion items of excess stock (McKinsey & BoF), and since July 2026 large EU companies may no longer destroy unsold clothing. Small labels pay the bill, after hours of specs and supplier emails. Atelier flips the order: design fast, sell first, make what has sold. The designer keeps the four taste calls; AI agents do the paperwork. 1. Signal: Gemma 4 (Google's open model) on AMD GPUs reads a mood board and the designer's own sketch. 2. Direction: the designer briefs changes in plain words; Atelier reads them back. 3. Tech pack: an Evolus agent on the AMD-hosted model writes a costed spec, grounded in the brand book. 4. Suppliers: RFQs go to each mill in its own language through an Evolus workflow; the Evolus document extractor reads the quotes. 5. Guardrails: plain arithmetic checks margin, cost cap, lead time and MOQ. When a quote breaks a rule the agent stops and hands the call to a person, then negotiates at the exact target price. 6. Pre-order: a real Shopify product opens for pre-order. 7. Purchase order: only once real orders clear the threshold does the PO go to the mill through Evolus. A statistical forecast (no LLM) suggests the quantity. Measured on a live run: approval to RFQs sent in 1 min 54 s. In our recorded run a supplier quoted EUR 320 for a tunic priced at EUR 310; the agent stopped, negotiated, and only sent PO-00001 after pre-orders arrived. Nothing is mocked: every model call is measured, AI images are labelled. Live: atelier.netlayerlabs.com
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