Marqo shipped Sibbi, and it’s not another shopping chatbot. One agent runs discovery, visual search, cart, order tracking, and returns — the entire shopper journey in a single conversation.
Upload a photo, type “find this in black,” and Sibbi resolves aesthetic intent that text-only search can’t touch. Then it adds to cart, tracks the order, handles the return. One agent replacing four vendors.
Per-retailer brain, not a GPT wrapper
Marqo trains a dedicated model for each retailer — visual attributes, semantic relationships, margin priorities, inventory state, all in one inference layer. Most “AI shopping assistants” are GPT wrappers bolted onto a Shopify search box. Sibbi is search, recommendation, cart, and support collapsed into one.
Receipts: $130M attributable revenue uplift for a single retailer, double-digit conversion gains in controlled A/B tests across fashion, electronics, footwear, jewelry, and sporting goods.
API-only, enterprise-only
Sibbi ships as an API for enterprise retailers, not a consumer app. Plug it in, Marqo trains the per-retailer brain, the agent runs end-to-end. For commerce teams paying four vendors for search, recommendation, chat, and returns, that’s four contracts collapsing into one.
Founders are ex-Amazon Robotics AI lead Jesse Clark and ex-AWS engineer Tom Hamer. Marqo has raised $17.8M from Lightspeed and Blackbird, with Cohere’s Aidan Gomez and Ivan Zhang on the cap table. The vector search company quietly became the agentic commerce company.
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