Sibbi runs on Marqo's Commerce Superintelligence, a per-retailer AI layer that understands catalog attributes, shopper behavior, and commercial signals like margin and inventory priority.

Key differentiators include visual and conversational discovery via image uploads and text, ongoing post-purchase revenue continuity, persistent contextual memory, and zero-shot product competency with new items from day one.

Industry implications for e-commerce include using unified agents to convert visual search and conversational intent into higher attribution and revenue across the purchase funnel.

Sibbi bridges the ecommerce gap where discovery ends at purchase and post-purchase support is handled by separate systems, creating a more cohesive customer experience.

Unified Commerce Agents consolidate discovery, purchase, and post-purchase interactions into one persistent interface to reduce fragmented touchpoints.

Sibbi acts as an autonomous guide that maintains the brand relationship after checkout by turning logistics tasks like order tracking and returns into ongoing discovery opportunities.

Marqo unveils Sibbi, a unified commerce agent powered by Commerce Superintelligence, designed to manage the entire shopper journey—from discovery to post-purchase—in a single conversational interface.

The concept of persistent context in customer support could cut resolution times and streamline returns and order inquiries.

Retail analytics and personalization can leverage continuous shopper context to build richer behavior models for hyper-relevant merchandising and lifetime-value forecasting.

End-to-end conversational commerce enables a seamless progression from visual discovery to checkout and order tracking within one dialogue.

Sibbi maintains persistent memory of each shopper’s intent, enabling actions like uploading a favorite image, requesting variations, adding to cart, purchasing, and checking status in chat without re-entering information.

Early validation shows notable results, including about $130 million in attributable revenue uplift for a retailer and double-digit improvements in search conversion across multiple categories, demonstrated through controlled production A/B tests.