Conversational Commerce Agent

Typical outcomes for this kind of engagement. Results depend on your data and starting point.

Shoppers describe what they want in their own words (something warm for a winter trip, a gift for a teenager, shoes that work for both office and weekend), and keyword search fails all of it.

• Keyword search failing shoppers who describe needs rather than product names
• Category navigation assuming knowledge of a taxonomy shoppers do not have
• Generic recommendations ignoring stated intent and context

CloudGate builds a conversational commerce assistant grounded in your catalogue, using semantic search over product attributes, descriptions and imagery so natural-language intent maps to actual products.

• Semantic search over catalogue attributes, descriptions and imagery
• Natural-language intent understanding including occasion and use-case queries
• Clarifying questions to narrow intent rather than returning an undifferentiated list