A multi-brand retailer was waiting weeks for studio photography on every new SKU. We built a Flux.1-based generation pipeline with per-brand style LoRAs, scaled to 12,000 SKUs a day on their existing GPU cluster.
The client onboards 800–1,200 new SKUs a week across 14 sub-brands. Studio photography backlogs were running 3 weeks. Stock product shots looked nothing like the brand. Marketplace listings were going live with placeholder images, hurting conversion. They needed studio-quality, on-brand product imagery generated in minutes per SKU - and the look had to stay consistent across batches.
Trained 14 Flux.1 dev LoRAs, one per sub-brand. Each LoRA learned the brand's lighting, colour grade, background palette, and shot framing from 200–400 hero shots.
ControlNet conditioning on the supplier-provided product cutout, so the actual product geometry is never hallucinated. The LoRA only controls the surrounding scene and styling.
REST API accepting SKU + brand + scene preset. 4 variations generated per SKU, scored by a fine-tuned aesthetic model, top result auto-promoted.
Confidence-thresholded gating - anything below 0.85 routes to a human reviewer in a custom Streamlit tool. Reviewer feedback flows back into LoRA retraining.
Multi-GPU node with vLLM-style batching for Flux. ~6 seconds per image at 1024×1024 on H100. Generated assets pushed to their existing CDN within 2 minutes of approval.
“We finally have brand-consistent product photography that ships at the pace of merchandising - not at the pace of a studio.”
- VP Digital, multi-brand retailer (name withheld)
A 30-minute call. We'll tell you whether we can help - and if not, who can.