Introducing Velou Commerce-1

A model trained where commerce actually happens

Domain data, not general web noise. Commerce-1 ingests 4 T tokens of retail-only text and imagery, then refines answers with reinforcement learning from merchandisers. That produces a model that knows “buffalo plaid” from “gingham,” “black-tie” from “white wedding,” and why “linen in Miami” beats “wool in July.”

Attribute-aware architecture. Dedicated attention heads track color, material, fit, and seasonality, letting the model generate structured attributes and variant groupings in milliseconds.

Built-in safety & brand tone. Price-integrity filters, compliance guards, and tone adapters ensure every generated title, schema tag, and chat reply is brand-safe and policy-correct.

This end-to-end, domain-specific recipe lets the model reason about fit, fabric, seasonality, and even regulatory label requirements with a fluency general-purpose LLMs simply don’t possess. In practice, Velou Commerce LLM produces more accurate tags, richer schema, and grounded Q&A,all while responding fast enough for real-time shopping assistance.

How much better is it?

We benchmarked the model against the strongest frontier LLMs available in May 2025. On core merchandising tasks, attribute extraction, variant clustering, and factual product Q&A, Velou Commerce LLM delivers double-digit accuracy gains and cuts hallucinations by more than half.

A panel of senior fashion merchants evaluated anonymized outputs from Commerce-1 and three leading frontier models across hundreds of real SKUs.

Built-in business impact, not just better BLEU scores

Because the model sees live catalog and click-stream data during continual fine-tunes, its improvements translate directly to bottom-line results:

• Higher conversion and lower ad waste – Cleaner titles, richer schema, and fewer feed disapprovals lift organic rank while shaving CPCs in Shopping campaigns.
  
• “Zero-ops” catalog management – New SKUs are automatically tagged, localized, and deduplicated in minutes, freeing merchants from days of manual spreadsheet work.
  
• Agentic storefronts that don’t hallucinate – Chat and voice assistants grounded in up-to-the-second inventory, size charts, and policies guide shoppers confidently from discovery to checkout‍
• Future-proofed data pipelines – The model re-trains nightly on fresh click signals, so product attributes evolve with trends and seasonality without an engineer in the loop.

Safety, brand voice, and compliance at the core

Commerce content is heavily regulated and fiercely brand-sensitive. Velou Commerce LLM layers multiple safeguards:

• Price-integrity checks ensure generated copy never conflicts with catalog pricing or active promotions.
  
• Brand-tone conditioning keeps every title, alt-text, and chat reply on-voice, whether the brand is minimalist or maximalist.
  
• Regulatory filters block prohibited health claims, age-restricted content, or regional compliance violations before output ever reaches production systems.

Try it today

Commerce-1 is available to all our existing customers with 1M free tokens to experiment with attribute extraction, feed rewrites, or chat demos. New users can join our early-access wait-list, priority goes to retailers with 50 K+ SKUs who want to co-shape the roadmap for multimodal vision, live-stream fine-tuning, and turnkey agent actions arriving later this year.

See it in action

Below you’ll find a three-minute launch video featuring Velou CEO Sadee, lead ML engineer Jayana, and customer-success lead Debby as they walk through the vision, features, and early customer results.