Ecommerce
Ecommerce search fails in a specific way: a shopper describes what they want in their own words and gets nothing, because the catalogue uses different words. Semantic retrieval fixes that directly.
What makes this sector hard
Search that misses intent
Keyword matching fails the moment a shopper describes rather than names.
Support volume spikes
Where-is-my-order traffic that swamps teams seasonally.
Catalogue quality
Thin, inconsistent product data across thousands of SKUs.
Return rates
Driven by mismatched expectations at the point of purchase.
Systems that fit the constraints
Semantic product search
Natural-language discovery that understands description, not just keywords.
Order support automation
Grounded answers wired into live order and logistics systems.
Catalogue enrichment
Generated descriptions and attributes from images and sparse source data.
Personalised merchandising
Recommendations based on behaviour and product semantics.
What we design around
Working in ecommerce?
Tell us the problem. We'll tell you honestly whether AI is the right tool, and what it would take.